2023
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Wijayanto, Arif K; Junaedi, Ahmad; Sujaswara, Azwar A; Khamid, Miftakhul B. R.; Prasetyo, Lilik B; Hongo, Chiharu; Kuze, Hiroaki Machine Learning for Precise Rice Variety Classification in Tropical Environments Using UAV-Based Multispectral Sensing Journal Article In: AgriEngineering, vol. 5, pp. 2000-2019, 2023, ISSN: 2624-7402. @article{nokey,
title = {Machine Learning for Precise Rice Variety Classification in Tropical Environments Using UAV-Based Multispectral Sensing},
author = {Arif K Wijayanto and Ahmad Junaedi and Azwar A Sujaswara and Miftakhul B.R. Khamid and Lilik B Prasetyo and Chiharu Hongo and Hiroaki Kuze},
url = {http://algm.ipb.ac.id/wp-content/uploads/2025/02/agriengineering-05-00123.pdf},
doi = {10.3390/agriengineering5040123},
issn = {2624-7402},
year = {2023},
date = {2023-11-01},
urldate = {2023-11-01},
journal = {AgriEngineering},
volume = {5},
pages = {2000-2019},
abstract = {An efficient assessment of rice varieties in tropical regions is crucial for selecting cultivars suited to unique environmental conditions. This study explores machine learning algorithms that leverage multispectral sensor data from UAVs to evaluate rice varieties. It focuses on three paddy rice types at different ages (six, nine, and twelve weeks after planting), analyzing data from four spectral bands and vegetation indices using various algorithms for classification. The results show that the neural network (NN) algorithm is superior, achieving an area under the curve value of 0.804. The twelfth week post-planting yielded the most accurate results, with green reflectance the dominant predictor, surpassing the traditional vegetation indices. This study demonstrates the rapid and effective classification of rice varieties using UAV-based multispectral sensors and NN algorithms to enhance agricultural practices and global food security.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
An efficient assessment of rice varieties in tropical regions is crucial for selecting cultivars suited to unique environmental conditions. This study explores machine learning algorithms that leverage multispectral sensor data from UAVs to evaluate rice varieties. It focuses on three paddy rice types at different ages (six, nine, and twelve weeks after planting), analyzing data from four spectral bands and vegetation indices using various algorithms for classification. The results show that the neural network (NN) algorithm is superior, achieving an area under the curve value of 0.804. The twelfth week post-planting yielded the most accurate results, with green reflectance the dominant predictor, surpassing the traditional vegetation indices. This study demonstrates the rapid and effective classification of rice varieties using UAV-based multispectral sensors and NN algorithms to enhance agricultural practices and global food security. |
2022
|
Condro, Aryo Adhi; Prasetyo, Lilik B; Rushayati, Siti Badriyah; Santikayasa, I Putu; Iskandar, Entang Protected areas slow down tropical rainforest disturbance in the Leuser Ecosystem, Indonesia Journal Article In: Journal of Land Use Science, vol. 17, no. 1, pp. 454-470, 2022. @article{Condro2022,
title = {Protected areas slow down tropical rainforest disturbance in the Leuser Ecosystem, Indonesia},
author = {Aryo Adhi Condro and Lilik B Prasetyo and Siti Badriyah Rushayati and I Putu Santikayasa and Entang Iskandar},
url = {https://www.tandfonline.com/doi/full/10.1080/1747423X.2022.2115571https://algm.ipb.ac.id/wp-content/uploads/2022/08/Protected-areas-slow-down-tropical-rainforest-disturbance-in-the-Leuser-Ecosystem-Indonesia.pdf},
doi = {10.1080/1747423X.2022.2115571},
year = {2022},
date = {2022-08-25},
journal = {Journal of Land Use Science},
volume = {17},
number = {1},
pages = {454-470},
abstract = {Tropical rainforest ecosystems that function as biodiversity pools had been undermined because of anthropogenic activities. Research has shown that protected areas (PAs) have become the first safeguard for biodiversity. However, how to measure the effectiveness of PAs remains unclear. We present spatiotemporal changes within the PAs and non-PAs in the Leuser Ecosystem, which is one of the significant global landscapes, using intensity analysis during two time periods and propensity score matching to investigate the effectiveness of PAs. We classified land cover using machine learning based on remotely sensed data. Our results revealed the effectiveness of PAs compared with non-PAs. The new conservation intervention after 2008 resulted in the deacceleration of deforestation from 2000–2010 to 2010–2020. In addition, PAs can reduce deforestation two times more effectively than non-PAs. Therefore, PAs and good governance within the Leuser Ecosystem are crucial in maintaining the natural ecosystem to address global conservation targets.},
keywords = {leuser, rainforest},
pubstate = {published},
tppubtype = {article}
}
Tropical rainforest ecosystems that function as biodiversity pools had been undermined because of anthropogenic activities. Research has shown that protected areas (PAs) have become the first safeguard for biodiversity. However, how to measure the effectiveness of PAs remains unclear. We present spatiotemporal changes within the PAs and non-PAs in the Leuser Ecosystem, which is one of the significant global landscapes, using intensity analysis during two time periods and propensity score matching to investigate the effectiveness of PAs. We classified land cover using machine learning based on remotely sensed data. Our results revealed the effectiveness of PAs compared with non-PAs. The new conservation intervention after 2008 resulted in the deacceleration of deforestation from 2000–2010 to 2010–2020. In addition, PAs can reduce deforestation two times more effectively than non-PAs. Therefore, PAs and good governance within the Leuser Ecosystem are crucial in maintaining the natural ecosystem to address global conservation targets. |
Adinugroho, Wahyu Catur; Prasetyo, Lilik B; Kusmana, Cecep; Krisnawati, Haruni; Weston, Christopher J.; Volkova, Liubov Recovery of Carbon and Vegetation Diversity 23 Years after Fire in a Tropical Dryland Forest of Indonesia Journal Article In: Sustainability, vol. 14, no. 12, 2022. @article{Adinugroho2022,
title = {Recovery of Carbon and Vegetation Diversity 23 Years after Fire in a Tropical Dryland Forest of Indonesia},
author = {Wahyu Catur Adinugroho and Lilik B Prasetyo and Cecep Kusmana and Haruni Krisnawati and Christopher J. Weston and Liubov Volkova},
url = {https://www.mdpi.com/2071-1050/14/12/6964/htm},
doi = {10.3390/su14126964},
year = {2022},
date = {2022-06-07},
journal = {Sustainability},
volume = {14},
number = {12},
abstract = {Understanding the recovery rate of forest carbon stocks and biodiversity after disturbance, including fire, is vital for developing effective climate-change-mitigation policies and actions. In this study, live and dead carbon stocks aboveground, belowground, and in the soil to a 30 cm depth, as well as tree and shrub species diversity, were measured in a tropical lowland dry forest, 23 years after a fire in 1998, for comparison with adjacent unburned reference forests. The results showed that 23 years since the fire was insufficient, in this case, to recover live forest carbon and plant species diversity, to the level of the reference forests. The total carbon stock, in the recovering 23-year-old forest, was 199 Mg C ha−1 or about 90% of the unburned forest (220 Mg C ha−1), mainly due to the contribution of coarse woody debris and an increase in the 5–10 cm soil horizon’s organic carbon, in the burned forest. The carbon held in the live biomass of the recovering forest (79 Mg C ha−1) was just over half the 146 Mg C ha−1 of the reference forest. Based on a biomass mean annual increment of 6.24 ± 1.59 Mg ha−1 yr−1, about 46 ± 17 years would be required for the aboveground live biomass to recover to equivalence with the reference forest. In total, 176 plant species were recorded in the 23-year post-fire forest, compared with 216 in the unburned reference forest. The pioneer species Macaranga gigantea dominated in the 23-year post-fire forest, which was yet to regain the similar stand structural and compositional elements as those found in the adjacent unburned reference forest.},
keywords = {carbon, dryland},
pubstate = {published},
tppubtype = {article}
}
Understanding the recovery rate of forest carbon stocks and biodiversity after disturbance, including fire, is vital for developing effective climate-change-mitigation policies and actions. In this study, live and dead carbon stocks aboveground, belowground, and in the soil to a 30 cm depth, as well as tree and shrub species diversity, were measured in a tropical lowland dry forest, 23 years after a fire in 1998, for comparison with adjacent unburned reference forests. The results showed that 23 years since the fire was insufficient, in this case, to recover live forest carbon and plant species diversity, to the level of the reference forests. The total carbon stock, in the recovering 23-year-old forest, was 199 Mg C ha−1 or about 90% of the unburned forest (220 Mg C ha−1), mainly due to the contribution of coarse woody debris and an increase in the 5–10 cm soil horizon’s organic carbon, in the burned forest. The carbon held in the live biomass of the recovering forest (79 Mg C ha−1) was just over half the 146 Mg C ha−1 of the reference forest. Based on a biomass mean annual increment of 6.24 ± 1.59 Mg ha−1 yr−1, about 46 ± 17 years would be required for the aboveground live biomass to recover to equivalence with the reference forest. In total, 176 plant species were recorded in the 23-year post-fire forest, compared with 216 in the unburned reference forest. The pioneer species Macaranga gigantea dominated in the 23-year post-fire forest, which was yet to regain the similar stand structural and compositional elements as those found in the adjacent unburned reference forest. |
Prasetyo, Lilik B; Setiawan, Yudi; Condro, Aryo Adhi; Kustiyo,; Putra, Eriyanto Indra; Hayati, Nur; Wijayanto, Arif K; Ramadhi, Almi; Murdiyarso, Daniel Assessing Sumatran Peat Vulnerability to Fire under Various Condition of ENSO Phases Using Machine Learning Approaches Journal Article In: Forests, vol. 13, no. 6, 2022. @article{Prasetyo2022,
title = {Assessing Sumatran Peat Vulnerability to Fire under Various Condition of ENSO Phases Using Machine Learning Approaches},
author = {Lilik B Prasetyo and Yudi Setiawan and Aryo Adhi Condro and Kustiyo and Eriyanto Indra Putra and Nur Hayati and Arif K Wijayanto and Almi Ramadhi and Daniel Murdiyarso},
url = {https://www.mdpi.com/1999-4907/13/6/828},
doi = {10.3390/f13060828},
year = {2022},
date = {2022-05-25},
journal = {Forests},
volume = {13},
number = {6},
abstract = {In recent decades, catastrophic wildfire episodes within the Sumatran peatland have contributed to a large amount of greenhouse gas emissions. The El-Nino Southern Oscillation (ENSO) modulates the occurrence of fires in Indonesia through prolonged hydrological drought. Thus, assessing peatland vulnerability to fires and understanding the underlying drivers are essential to developing adaptation and mitigation strategies for peatland. Here, we quantify the vulnerability of Sumatran peat to fires under various ENSO conditions (i.e., El-Nino, La-Nina, and Normal phases) using correlative modelling approaches. This study used climatic (i.e., annual precipitation, SPI, and KBDI), biophysical (i.e., below-ground biomass, elevation, slope, and NBR), and proxies to anthropogenic disturbance variables (i.e., access to road, access to forests, access to cities, human modification, and human population) to assess fire vulnerability within Sumatran peatlands. We created an ensemble model based on various machine learning approaches (i.e., random forest, support vector machine, maximum entropy, and boosted regression tree). We found that the ensemble model performed better compared to a single algorithm for depicting fire vulnerability within Sumatran peatlands. The NBR highly contributed to the vulnerability of peatland to fire in Sumatra in all ENSO phases, followed by the anthropogenic variables. We found that the high to very-high peat vulnerability to fire increases during El-Nino conditions with variations in its spatial patterns occurring under different ENSO phases. This study provides spatially explicit information to support the management of peat fires, which will be particularly useful for identifying peatland restoration priorities based on peatland vulnerability to fire maps. Our findings highlight Riau’s peatland as being the area most prone to fires area on Sumatra Island. Therefore, the groundwater level within this area should be intensively monitored to prevent peatland fires. In addition, conserving intact forests within peatland through the moratorium strategy and restoring the degraded peatland ecosystem through canal blocking is also crucial to coping with global climate change.},
keywords = {ENSO, fire, land fire, peat land},
pubstate = {published},
tppubtype = {article}
}
In recent decades, catastrophic wildfire episodes within the Sumatran peatland have contributed to a large amount of greenhouse gas emissions. The El-Nino Southern Oscillation (ENSO) modulates the occurrence of fires in Indonesia through prolonged hydrological drought. Thus, assessing peatland vulnerability to fires and understanding the underlying drivers are essential to developing adaptation and mitigation strategies for peatland. Here, we quantify the vulnerability of Sumatran peat to fires under various ENSO conditions (i.e., El-Nino, La-Nina, and Normal phases) using correlative modelling approaches. This study used climatic (i.e., annual precipitation, SPI, and KBDI), biophysical (i.e., below-ground biomass, elevation, slope, and NBR), and proxies to anthropogenic disturbance variables (i.e., access to road, access to forests, access to cities, human modification, and human population) to assess fire vulnerability within Sumatran peatlands. We created an ensemble model based on various machine learning approaches (i.e., random forest, support vector machine, maximum entropy, and boosted regression tree). We found that the ensemble model performed better compared to a single algorithm for depicting fire vulnerability within Sumatran peatlands. The NBR highly contributed to the vulnerability of peatland to fire in Sumatra in all ENSO phases, followed by the anthropogenic variables. We found that the high to very-high peat vulnerability to fire increases during El-Nino conditions with variations in its spatial patterns occurring under different ENSO phases. This study provides spatially explicit information to support the management of peat fires, which will be particularly useful for identifying peatland restoration priorities based on peatland vulnerability to fire maps. Our findings highlight Riau’s peatland as being the area most prone to fires area on Sumatra Island. Therefore, the groundwater level within this area should be intensively monitored to prevent peatland fires. In addition, conserving intact forests within peatland through the moratorium strategy and restoring the degraded peatland ecosystem through canal blocking is also crucial to coping with global climate change. |
Kurniawan, Fery; Adrianto, Lukri; Bengen, Dietriech Geoffrey; Prasetyo, Lilik B Hypothetical effects assessment of tourism on coastal water quality in the Marine Tourism Park of the Gili Matra Islands, Indonesia Journal Article In: Environment, Development and Sustainability, 2022. @article{Kurniawan2022,
title = {Hypothetical effects assessment of tourism on coastal water quality in the Marine Tourism Park of the Gili Matra Islands, Indonesia},
author = {Fery Kurniawan and Lukri Adrianto and Dietriech Geoffrey Bengen and Lilik B Prasetyo},
url = {https://link.springer.com/article/10.1007/s10668-022-02382-8},
doi = {10.1007/s10668-022-02382-8},
year = {2022},
date = {2022-05-10},
journal = {Environment, Development and Sustainability},
abstract = {Tourism is one of the most important issues facing marine protected areas (MPAs) and small islands worldwide. Tourism development is considered a contribution to pollution levels in the environment. This paper aims to evaluate the hypothetical effects of tourism development on water quality spatially and temporally using the coastal water quality index (CWQI) and Geographic Information System (GIS) in search of improved management for marine conservation areas. This study showed significant tourism influences on the CWQI in the Marine Tourism Park of the Gili Matra Islands, Lombok, Indonesia. Water quality variability indicates a significant spatiotemporal difference (p < 0.05) in the two tourism seasons. During the peak season of tourism, the CWQI decreased to poor conditions, i.e., ranging from 9.95 to 21.49 for marine biota and from 7.98 to 30.42 for marine tourism activities in 2013, and ranging from 39.52 to 44.42 for marine biota and from 44.13 to 47.28 for marine tourism activities, which were below the standard for both marine biota and marine tourism activities. On the contrary, it showed a better level (from poor to moderate) during the low season of tourism (ranging from 41.92 to 61.84 for marine biota and from 48.06 to 65.27 for marine tourism activities in 2014), providing a more acceptable condition for both aspects. The study proved that massive tourism development in the MPA and small islands could reduce water quality and increase vulnerability. Accordingly, integrated tourism management and the environment, waters, and land will be needed to develop sustainable tourism. The CWQI and GIS were applicable to assess water quality, both spatially and temporally, and become a quick reference in monitoring and initial evaluation of impact management.},
keywords = {coastal, tourism},
pubstate = {published},
tppubtype = {article}
}
Tourism is one of the most important issues facing marine protected areas (MPAs) and small islands worldwide. Tourism development is considered a contribution to pollution levels in the environment. This paper aims to evaluate the hypothetical effects of tourism development on water quality spatially and temporally using the coastal water quality index (CWQI) and Geographic Information System (GIS) in search of improved management for marine conservation areas. This study showed significant tourism influences on the CWQI in the Marine Tourism Park of the Gili Matra Islands, Lombok, Indonesia. Water quality variability indicates a significant spatiotemporal difference (p < 0.05) in the two tourism seasons. During the peak season of tourism, the CWQI decreased to poor conditions, i.e., ranging from 9.95 to 21.49 for marine biota and from 7.98 to 30.42 for marine tourism activities in 2013, and ranging from 39.52 to 44.42 for marine biota and from 44.13 to 47.28 for marine tourism activities, which were below the standard for both marine biota and marine tourism activities. On the contrary, it showed a better level (from poor to moderate) during the low season of tourism (ranging from 41.92 to 61.84 for marine biota and from 48.06 to 65.27 for marine tourism activities in 2014), providing a more acceptable condition for both aspects. The study proved that massive tourism development in the MPA and small islands could reduce water quality and increase vulnerability. Accordingly, integrated tourism management and the environment, waters, and land will be needed to develop sustainable tourism. The CWQI and GIS were applicable to assess water quality, both spatially and temporally, and become a quick reference in monitoring and initial evaluation of impact management. |
Rahadian, Aswin; Kusmana, Cecep; Setiawan, Yudi; Prasetyo, Lilik B Adaptive Mangrove Ecosystem Rehabilitation Plan based on Coastal Typology and Ecological Dynamics Approach Journal Article In: HAYATI Journal of Biosciences, vol. 29, no. 4, pp. 445-458, 2022, ISSN: 1978-3019. @article{Rahadian2022,
title = {Adaptive Mangrove Ecosystem Rehabilitation Plan based on Coastal Typology and Ecological Dynamics Approach},
author = {Aswin Rahadian and Cecep Kusmana and Yudi Setiawan and Lilik B Prasetyo},
url = {https://journal.ipb.ac.id/index.php/hayati/article/view/39193},
doi = {10.4308/hjb.29.4.445-458},
issn = {1978-3019},
year = {2022},
date = {2022-03-30},
journal = {HAYATI Journal of Biosciences},
volume = {29},
number = {4},
pages = {445-458},
abstract = {Mangrove rehabilitation has implications for important ecological, social and economic values for coastal communities. The mangroves ecosystem Karawang Regency is still under pressure due to the management and utilization that does not pay attention to the sustainability aspect. The rehabilitation plan to mangrove management must be adapted to the nature and characteristics of the habitat. This study aims to formulate technical considerations for the direction of a rehabilitation plan based on an ecological approach and the dynamics of the mangrove ecosystem. The methods used in this study were geospatial approach that integrated with field quanitative and qualitative data. The results show that the total of mangrove potential area in Karawang Regency was 19,139.53 ha, consisting of 421.95 ha (2.2%) of vegetated area and 18,717.58 ha (97.8%) of unvegetated area. We integrate mangrove typology, mangrove stand density, physical parameters, and land use as the basis for determining the direction of rehabilitation planning. In the estuarine deltaic mangrove typology, we aim at protecting with natural regeneration. In infringe areas, we recommend constructing natural coastal structures before planting. On the backward for intensive planting. Furthermore, mangroves with low density, medium density, and high density are recommended for planting, species enrichment, and protecting respectively, and on the pond with implementing the mixed mangrove-aquaculture system to bridge between rehabilitation effort and economic needs of coastal communities.},
keywords = {coastal, mangrove},
pubstate = {published},
tppubtype = {article}
}
Mangrove rehabilitation has implications for important ecological, social and economic values for coastal communities. The mangroves ecosystem Karawang Regency is still under pressure due to the management and utilization that does not pay attention to the sustainability aspect. The rehabilitation plan to mangrove management must be adapted to the nature and characteristics of the habitat. This study aims to formulate technical considerations for the direction of a rehabilitation plan based on an ecological approach and the dynamics of the mangrove ecosystem. The methods used in this study were geospatial approach that integrated with field quanitative and qualitative data. The results show that the total of mangrove potential area in Karawang Regency was 19,139.53 ha, consisting of 421.95 ha (2.2%) of vegetated area and 18,717.58 ha (97.8%) of unvegetated area. We integrate mangrove typology, mangrove stand density, physical parameters, and land use as the basis for determining the direction of rehabilitation planning. In the estuarine deltaic mangrove typology, we aim at protecting with natural regeneration. In infringe areas, we recommend constructing natural coastal structures before planting. On the backward for intensive planting. Furthermore, mangroves with low density, medium density, and high density are recommended for planting, species enrichment, and protecting respectively, and on the pond with implementing the mixed mangrove-aquaculture system to bridge between rehabilitation effort and economic needs of coastal communities. |
Purnomo, Danang Wahyu; Prasetyo, Lilik B; Widyatmoko, Didik; Rushayati, Siti Badriyah; Supriyatna, Ikar; Yani, Akhmad Diversity and carbon sequestration capacity of naturally growth vegetation in ex-nickel mining area in Kolaka, Southeast Sulawesi, Indonesia Journal Article In: Biodiversitas, vol. 23, no. 3, pp. 1433-1442, 2022, ISSN: 2085-4722. @article{Purnomo2022,
title = {Diversity and carbon sequestration capacity of naturally growth vegetation in ex-nickel mining area in Kolaka, Southeast Sulawesi, Indonesia},
author = {Danang Wahyu Purnomo and Lilik B Prasetyo and Didik Widyatmoko and Siti Badriyah Rushayati and Ikar Supriyatna and Akhmad Yani},
url = {https://smujo.id/biodiv/article/view/10518},
doi = {10.13057/biodiv/d230330},
issn = {2085-4722},
year = {2022},
date = {2022-02-22},
journal = {Biodiversitas},
volume = {23},
number = {3},
pages = {1433-1442},
abstract = {Diversity and carbon sequestration capacity of naturally growth vegetation in ex-nickel mining area in Kolaka, Southeast Sulawesi, Indonesia. Biodiversitas 23: 1433-1442. Efforts to restore forest integrity on ex-mining lands are essential to improve environmental quality and sequester carbon. One such effort is through revegetation of post-mined land including in ex-nickel mining in Southeast Sulawesi. This research analyzes the diversity of naturally regenerating plant species in the ex-nickel mining area in Kolaka, Southeast Sulawesi and determines several local tree species with the potential for carbon sequestration. Vegetation survey was conducted using a systematic nested sampling method at the post-mined site with three vegetation types: secondary forest, shrubs and bushes, and a reference/control site (i.e., natural forest in the nearby Lamedai Nature Reserve). Different types of vegetation were analyzed based on factors using Discriminant Analysis. Vegetation composition was analyzed using the Importance Value Index. Furthermore, biodiversity indicators were analyzed using Shannon-Wiener Diversity Index, Species Evenness Index, and Sorensen Similarity Index. Carbon absorption was measured using the leaf sample method and carbohydrate test. The results showed that the condition of the research site had been disturbed, and the succession process was still ongoing. The species diversity at all plant levels was classified as moderate category and the distribution of the community was unstable. At the tree level, the undisturbed areas had higher diversity. Eradication of Chromolaena odorata was needed to preserve the native vegetation and accelerate forest succession. Tree species recommended for restoring the ex-nickel mining area and carbon sequestration as core plants include Vitex glabrata R.Br., Alstonia macrophylla Wall. ex G.Don, Lithocarpus celebicus (Miq.) Rehder, Callicarpa pentandra Roxb., Dacryodes rugosa (Blume) H.J.Lam, Cananga odorata (Lam.) Hook.f. & Thomson, Glochidion rubrum Blume, Terminalia bellirica (Gaertn.) Roxb., and Psychotria calocarpa Ruiz & Pav., and other pioneer plants of Mallotus paniculatus (Lam.) Müll.Arg., Macaranga peltata (Roxb.) Müll.Arg., and Macaranga hispida (Blume) Müll.Arg.},
keywords = {carbon, mining, nickel},
pubstate = {published},
tppubtype = {article}
}
Diversity and carbon sequestration capacity of naturally growth vegetation in ex-nickel mining area in Kolaka, Southeast Sulawesi, Indonesia. Biodiversitas 23: 1433-1442. Efforts to restore forest integrity on ex-mining lands are essential to improve environmental quality and sequester carbon. One such effort is through revegetation of post-mined land including in ex-nickel mining in Southeast Sulawesi. This research analyzes the diversity of naturally regenerating plant species in the ex-nickel mining area in Kolaka, Southeast Sulawesi and determines several local tree species with the potential for carbon sequestration. Vegetation survey was conducted using a systematic nested sampling method at the post-mined site with three vegetation types: secondary forest, shrubs and bushes, and a reference/control site (i.e., natural forest in the nearby Lamedai Nature Reserve). Different types of vegetation were analyzed based on factors using Discriminant Analysis. Vegetation composition was analyzed using the Importance Value Index. Furthermore, biodiversity indicators were analyzed using Shannon-Wiener Diversity Index, Species Evenness Index, and Sorensen Similarity Index. Carbon absorption was measured using the leaf sample method and carbohydrate test. The results showed that the condition of the research site had been disturbed, and the succession process was still ongoing. The species diversity at all plant levels was classified as moderate category and the distribution of the community was unstable. At the tree level, the undisturbed areas had higher diversity. Eradication of Chromolaena odorata was needed to preserve the native vegetation and accelerate forest succession. Tree species recommended for restoring the ex-nickel mining area and carbon sequestration as core plants include Vitex glabrata R.Br., Alstonia macrophylla Wall. ex G.Don, Lithocarpus celebicus (Miq.) Rehder, Callicarpa pentandra Roxb., Dacryodes rugosa (Blume) H.J.Lam, Cananga odorata (Lam.) Hook.f. & Thomson, Glochidion rubrum Blume, Terminalia bellirica (Gaertn.) Roxb., and Psychotria calocarpa Ruiz & Pav., and other pioneer plants of Mallotus paniculatus (Lam.) Müll.Arg., Macaranga peltata (Roxb.) Müll.Arg., and Macaranga hispida (Blume) Müll.Arg. |
Condro, Aryo Adhi; Syartinilia, Syartinilia; Higuchi, Hiroyoshi; Mulyani, Yeni A; Raffiudin, Rika; Rusniarsyah, Luthfi; Setiawan, Yudi; Prasetyo, Lilik B Climate change leads to range contraction for Japanese population of the Oriental Honey-Buzzards: Implications for future conservation strategies Journal Article In: Global Ecology and Conservation, vol. 34, 2022. @article{Condro2022b,
title = {Climate change leads to range contraction for Japanese population of the Oriental Honey-Buzzards: Implications for future conservation strategies},
author = {Aryo Adhi Condro and Syartinilia Syartinilia and Hiroyoshi Higuchi and Yeni A Mulyani and Rika Raffiudin and Luthfi Rusniarsyah and Yudi Setiawan and Lilik B Prasetyo},
url = {https://www.sciencedirect.com/science/article/pii/S2351989422000464},
doi = {10.1016/j.gecco.2022.e02044},
year = {2022},
date = {2022-02-01},
journal = {Global Ecology and Conservation},
volume = {34},
abstract = {Over the past decades, global environmental changes have led to unfavorable effects on migratory birds. However, many species that encounter climate change are listed as least concern by International Union for Conservation of Nature. Using species distribution models, we quantified the redistributions of breeding and wintering sites of oriental honey buzzards, OHB (Pernis ptilorhynchus), a long-distance migratory raptor that often preys on the larvae of wasps and bees under changing climate based on shared socio-economic pathways scenarios. We also incorporated climate and land use risks based on climate anomalies and vegetation dynamics to assess future conservation strategies. The results revealed a significant range contraction on the wintering and breeding areas of the OHB species by 2050 and 2100. Our results suggest that the migration distance will likely increase under all scenarios. In addition, we found many high-risk areas across OHB habitats while refugia areas were relatively only covered a small proportion. Habitat restoration and developing new protected areas become a fundamental strategy for OHB conservation. Our approaches have provided comprehensive insights into broad biogeographic dynamics under multifaceted threats and how to tackle global changes through the specific landscape management for long-distance migrants.},
keywords = {honey bee},
pubstate = {published},
tppubtype = {article}
}
Over the past decades, global environmental changes have led to unfavorable effects on migratory birds. However, many species that encounter climate change are listed as least concern by International Union for Conservation of Nature. Using species distribution models, we quantified the redistributions of breeding and wintering sites of oriental honey buzzards, OHB (Pernis ptilorhynchus), a long-distance migratory raptor that often preys on the larvae of wasps and bees under changing climate based on shared socio-economic pathways scenarios. We also incorporated climate and land use risks based on climate anomalies and vegetation dynamics to assess future conservation strategies. The results revealed a significant range contraction on the wintering and breeding areas of the OHB species by 2050 and 2100. Our results suggest that the migration distance will likely increase under all scenarios. In addition, we found many high-risk areas across OHB habitats while refugia areas were relatively only covered a small proportion. Habitat restoration and developing new protected areas become a fundamental strategy for OHB conservation. Our approaches have provided comprehensive insights into broad biogeographic dynamics under multifaceted threats and how to tackle global changes through the specific landscape management for long-distance migrants. |
2021
|
Rizal, Muhammad; Saleh, Muhammad Buce; Prasetyo, Lilik B Biomass Estimation Model For Peat Swamp Forest Ecosystem Using LiDAR (Light Detection And Ranging) Journal Article In: TELKOMNIKA, vol. 19, no. 3, 2021, ISSN: 2302-9293. @article{Rizal2021,
title = {Biomass Estimation Model For Peat Swamp Forest Ecosystem Using LiDAR (Light Detection And Ranging)},
author = {Muhammad Rizal and Muhammad Buce Saleh and Lilik B Prasetyo},
url = {http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/18152},
doi = {10.12928/telkomnika.v19i3.18152},
issn = {2302-9293},
year = {2021},
date = {2021-06-01},
journal = {TELKOMNIKA},
volume = {19},
number = {3},
abstract = {Peat swamp forest plays avery important role in absorbing and storing large amounts of terrestrial carbon, both above ground and in the soil. There has been a lot of research on the estimation of the amount of biomass above the ground, but a little on peat swamp ecosystems using LIDAR technology, especially in Indonesia. The purpose of this study is to build a biomass estimation model based on LIDAR (Light Detection and Ranging) data. This technology can obtain information about the structure and characteristics of any vegetation in detail and in real time. Data was obtained from the East Kotawaringin Regency, Central Kalimantan. Biomass field was generated from the available allometry, and Point cloud of LiDAR was extracted into Canopy Cover (CC), and data on tree height, using the FRCI and Local Maxima (LM) method, respectively. The CC and tree height data were then used as independent variables in building the regression model. The best-fitted model was obtained after the scoring and ranking of several regression forms such as linear, quadratic, power, exponential and logarithmic. This research concluded that the quadratic regression model, with R2 of 72.16% and RMSE (Root Mean Square Error) of 0.0003% is the best-fitted estimation model (BK). Finally, the biomass value from the models was 244.510 tons/ha.},
keywords = {biomass, LiDAR, peat swamp},
pubstate = {published},
tppubtype = {article}
}
Peat swamp forest plays avery important role in absorbing and storing large amounts of terrestrial carbon, both above ground and in the soil. There has been a lot of research on the estimation of the amount of biomass above the ground, but a little on peat swamp ecosystems using LIDAR technology, especially in Indonesia. The purpose of this study is to build a biomass estimation model based on LIDAR (Light Detection and Ranging) data. This technology can obtain information about the structure and characteristics of any vegetation in detail and in real time. Data was obtained from the East Kotawaringin Regency, Central Kalimantan. Biomass field was generated from the available allometry, and Point cloud of LiDAR was extracted into Canopy Cover (CC), and data on tree height, using the FRCI and Local Maxima (LM) method, respectively. The CC and tree height data were then used as independent variables in building the regression model. The best-fitted model was obtained after the scoring and ranking of several regression forms such as linear, quadratic, power, exponential and logarithmic. This research concluded that the quadratic regression model, with R2 of 72.16% and RMSE (Root Mean Square Error) of 0.0003% is the best-fitted estimation model (BK). Finally, the biomass value from the models was 244.510 tons/ha. |
2020
|
Setiawan, Yudi; Rushayati, Siti Badriyah; Hermawan, Rachmad; Prasetyo, Lilik B; Wijayanto, Arif K The effect of utilization patterns of green open space on the dynamics change of air quality due to the Covid-19 pandemic in Jabodetabek region Journal Article In: Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management), vol. 10, no. 4, pp. 559-567, 2020, ISSN: 2460-5824. @article{Setiawan2020,
title = {The effect of utilization patterns of green open space on the dynamics change of air quality due to the Covid-19 pandemic in Jabodetabek region},
author = {Yudi Setiawan and Siti Badriyah Rushayati and Rachmad Hermawan and Lilik B Prasetyo and Arif K Wijayanto},
url = {https://journal.ipb.ac.id/index.php/jpsl/article/view/32550},
doi = {10.29244/jpsl.10.4.559-567},
issn = {2460-5824},
year = {2020},
date = {2020-12-31},
journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)},
volume = {10},
number = {4},
pages = {559-567},
abstract = {The Covid-19 pandemic has had a global impact on all sectors including the environment. The spread of covid-19 is very much influenced by human activity and mobility. Human activities are also closelyrelated to air pollutant emissions. High concentrations of air pollutants during the Covid-19 pandemic will increase the risk of being exposed to Covid-19. Jakarta and its surroundingarea (known locally as Jabodetabek) havehigh population density. Thesecities are economic and industrial centers. Air pollutant emissions in these cities are very high. High concentrations of air pollutants during the Covid-19 pandemic will increase the risk of being exposed to Covid. To anticipate this problem, the government made a Large-Scale Social Restriction Policy (PSBB). Limited human activities, in addition to having an impact on reducing the risk of humans being exposed to Covid-19 from the droplets released by tested-positive of Covid-19, also have an impact on reducing emissions of air pollutants so that they can reduce the risk of being exposed to Covid-19. Several variables that influence vulnerability and risk to exposure to Covid-19 are the distribution of settlements, roads, economic centers (markets, business centers, industrial centers), and human mobility. In this study, we will also analyze the role of green open space on the risk of exposure to Covid-19. Green open space plays an important role in reducing air pollutants so that it will also affect the risk of being exposed to Covid-19. This study aimedto 1) examine the distribution of air pollutants based on the vulnerability and risk of COVID-19 in Jakarta,Bogor, Depok, Tangerang, and Bekasi (Jabodetabek), and 2) examine the results of the overlay between land cover and vulnerability and risk to Covid-19},
keywords = {Covid-19, Kualitas udara, ruang terbuka hujau},
pubstate = {published},
tppubtype = {article}
}
The Covid-19 pandemic has had a global impact on all sectors including the environment. The spread of covid-19 is very much influenced by human activity and mobility. Human activities are also closelyrelated to air pollutant emissions. High concentrations of air pollutants during the Covid-19 pandemic will increase the risk of being exposed to Covid-19. Jakarta and its surroundingarea (known locally as Jabodetabek) havehigh population density. Thesecities are economic and industrial centers. Air pollutant emissions in these cities are very high. High concentrations of air pollutants during the Covid-19 pandemic will increase the risk of being exposed to Covid. To anticipate this problem, the government made a Large-Scale Social Restriction Policy (PSBB). Limited human activities, in addition to having an impact on reducing the risk of humans being exposed to Covid-19 from the droplets released by tested-positive of Covid-19, also have an impact on reducing emissions of air pollutants so that they can reduce the risk of being exposed to Covid-19. Several variables that influence vulnerability and risk to exposure to Covid-19 are the distribution of settlements, roads, economic centers (markets, business centers, industrial centers), and human mobility. In this study, we will also analyze the role of green open space on the risk of exposure to Covid-19. Green open space plays an important role in reducing air pollutants so that it will also affect the risk of being exposed to Covid-19. This study aimedto 1) examine the distribution of air pollutants based on the vulnerability and risk of COVID-19 in Jakarta,Bogor, Depok, Tangerang, and Bekasi (Jabodetabek), and 2) examine the results of the overlay between land cover and vulnerability and risk to Covid-19 |
Jarulis,; Solihin, Dedy Duryadi; Mardiastuti, Ani; Prasetyo, Lilik B CHARACTERS OF MITOCHONDRIAL DNA D-LOOP HYPERVARIABLE III FRAGMENTS OF INDONESIAN RHINOCEROS HORNBILL (BUCEROS RHINOCEROS) (AVES: BUCEROTIDAE) Journal Article In: TREUBIA (A JOURNAL ON ZOOLOGY OF THE INDO-AUSTRALIAN ARCHIPELAGO), vol. 47, no. 2, pp. 99-110, 2020, ISSN: 2337 -876X. @article{Jarulis2020,
title = {CHARACTERS OF MITOCHONDRIAL DNA D-LOOP HYPERVARIABLE III FRAGMENTS OF INDONESIAN RHINOCEROS HORNBILL (BUCEROS RHINOCEROS) (AVES: BUCEROTIDAE)},
author = {Jarulis and Dedy Duryadi Solihin and Ani Mardiastuti and Lilik B Prasetyo},
url = {https://e-journal.biologi.lipi.go.id/index.php/treubia/article/view/3971/3261},
doi = {10.14203/treubia.v47i2.3971},
issn = {2337 -876X},
year = {2020},
date = {2020-12-30},
journal = {TREUBIA (A JOURNAL ON ZOOLOGY OF THE INDO-AUSTRALIAN ARCHIPELAGO)},
volume = {47},
number = {2},
pages = {99-110},
abstract = {The rhinoceros hornbill (Buceros rhinoceros) genetic characteristics consist of nucleotide polymorphisms, haplotypes, genetic distances, and relationships which are important for their conservation effort in Indonesia. We sequenced mitochondrial DNA D-loop hypervariable III fragments from five rhinoceros hornbill individuals at Safari Park Indonesia I and Ragunan Zoo, which were isolated using Dneasy® Blood and Tissue Kit Spin-Column Protocol, Qiagen. D-loop fragment replication was done by PCR technique using DLBuce_F (5'-TGGCCTTTCTCCAAGGTCTA-3') and DLBuce_R (5'-TGAAGG AGT TCATGGGCTTAG-3') primer. Thirty SNP sites were found in 788 bp D-loop sequences of five rhinoceros hornbill individuals and each individual had a different haplotype. The average genetic distance between individuals was 3.09% and all individuals were categorized into two groups (Group I: EC6TS, EC1RG, EC2TS and Group II: EC9TS, EC10TS) with a genetic distance of 3.99%. This result indicated that the two groups were distinct subspecies. The genetic distance between Indonesian and Thai rhinoceros hornbills was 10.76%. Five Indonesian rhinoceros hornbill individuals at Safari Park Indonesia I and Ragunan Zoo probably came from different populations, ancestors, and two different islands. This study can be of use for management consideration in captive breeding effort at both zoos. The D-loop sequence obtained is a useful character to distinguish three rhinoceros hornbill subspecies in Indonesia.},
keywords = {hornbill, rhinoceros},
pubstate = {published},
tppubtype = {article}
}
The rhinoceros hornbill (Buceros rhinoceros) genetic characteristics consist of nucleotide polymorphisms, haplotypes, genetic distances, and relationships which are important for their conservation effort in Indonesia. We sequenced mitochondrial DNA D-loop hypervariable III fragments from five rhinoceros hornbill individuals at Safari Park Indonesia I and Ragunan Zoo, which were isolated using Dneasy® Blood and Tissue Kit Spin-Column Protocol, Qiagen. D-loop fragment replication was done by PCR technique using DLBuce_F (5'-TGGCCTTTCTCCAAGGTCTA-3') and DLBuce_R (5'-TGAAGG AGT TCATGGGCTTAG-3') primer. Thirty SNP sites were found in 788 bp D-loop sequences of five rhinoceros hornbill individuals and each individual had a different haplotype. The average genetic distance between individuals was 3.09% and all individuals were categorized into two groups (Group I: EC6TS, EC1RG, EC2TS and Group II: EC9TS, EC10TS) with a genetic distance of 3.99%. This result indicated that the two groups were distinct subspecies. The genetic distance between Indonesian and Thai rhinoceros hornbills was 10.76%. Five Indonesian rhinoceros hornbill individuals at Safari Park Indonesia I and Ragunan Zoo probably came from different populations, ancestors, and two different islands. This study can be of use for management consideration in captive breeding effort at both zoos. The D-loop sequence obtained is a useful character to distinguish three rhinoceros hornbill subspecies in Indonesia. |
Ramadhan, Rizky; Hermawan, Rachmad; Setiawan, Yudi Estimation of tree carbon stocks based on the typology of region in Depok City, West Java Province Conference SPIE, 2020. @conference{Ramadhan2020,
title = {Estimation of tree carbon stocks based on the typology of region in Depok City, West Java Province},
author = {Rizky Ramadhan and Rachmad Hermawan and Yudi Setiawan},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2542709/Estimation-of-tree-carbon-stocks-based-on-the-typology-of/10.1117/12.2542709.short?SSO=1&tab=ArticleLink},
doi = {10.1117/12.2542709},
year = {2020},
date = {2020-12-24},
publisher = {SPIE},
abstract = {Urbanization has triggered an increasing of population rate and the contribution of gas emissions consequently due to of human activities is also increased. Green Open Space (GOS) is a balancer of an urban environment and able to create a microclimate. Research objective is to assess a carbon stock in urban trees according to regional typologies, characteristics and development in Depok City. In this study, the type of area was distinguished into typology of region based on three main criteria, namely: population density, income and road density. Sample of GOS has been selected visually using ARCGIS 10.5 software, then field observation was conducted to collect some supporting data through interview and questionnaire distribution. The results showed that the higher area’s type the value of carbon stock is increasing, and GOS for green belt is the biggest contributor of carbon stock with 5.37 tons / km2. The community and government strongly support the movement of GOS development towards a Low Carbon City so that they need guidance and assistance from experts.},
keywords = {carbon stock},
pubstate = {published},
tppubtype = {conference}
}
Urbanization has triggered an increasing of population rate and the contribution of gas emissions consequently due to of human activities is also increased. Green Open Space (GOS) is a balancer of an urban environment and able to create a microclimate. Research objective is to assess a carbon stock in urban trees according to regional typologies, characteristics and development in Depok City. In this study, the type of area was distinguished into typology of region based on three main criteria, namely: population density, income and road density. Sample of GOS has been selected visually using ARCGIS 10.5 software, then field observation was conducted to collect some supporting data through interview and questionnaire distribution. The results showed that the higher area’s type the value of carbon stock is increasing, and GOS for green belt is the biggest contributor of carbon stock with 5.37 tons / km2. The community and government strongly support the movement of GOS development towards a Low Carbon City so that they need guidance and assistance from experts. |
Kusrini, Mirza Dikari; Khairunnisa, Luna Raftika; Nusantara, Aria; Kartono, Agus Priyono; Prasetyo, Lilik B; Ayuningrum, Novi Tri; Faz, Fata Habiburrahman Diversity of Amphibians and Reptiles in Various Anthropogenic Disturbance Habitats in Nantu Forest, Sulawesi, Indonesia Journal Article In: Jurnal Manajemen Hutan Tropika, vol. 26, no. 3, pp. 291-302, 2020, ISSN: 2089-2063. @article{Kusrini2020,
title = {Diversity of Amphibians and Reptiles in Various Anthropogenic Disturbance Habitats in Nantu Forest, Sulawesi, Indonesia},
author = {Mirza Dikari Kusrini and Luna Raftika Khairunnisa and Aria Nusantara and Agus Priyono Kartono and Lilik B Prasetyo and Novi Tri Ayuningrum and Fata Habiburrahman Faz},
url = {http://journal.ipb.ac.id/index.php/jmht/article/view/31437},
doi = {10.7226/jtfm.26.3.291},
issn = {2089-2063},
year = {2020},
date = {2020-12-12},
journal = {Jurnal Manajemen Hutan Tropika},
volume = {26},
number = {3},
pages = {291-302},
abstract = {The Nantu Forest in Gorontalo Province, Sulawesi, Indonesia holds one of the few remaining pristine habitats in the island. The reserve is surrounded by human habituation which provide opportunity to study the impact of forest lost on biodversity. In addition, data on Nantu mostly focused on big mammals, as there is no previous herpetofauna survey at the area. Sampling of amphibian and reptile was conducted in June 2013 and in May–June 2014 using Visual Encounter Survey method, glue traps and transect sampling in seven different sites at the eastern part of Nantu. We categorized four habitat types based on human disturbances: high disturbed habitat (HDH), moderate disturbed habitat (MDH), low disturbed habitat (LDH) and pristine habitat (PH). A total of 680 individual amphibians (4 families; 17 species) and 119 individual reptiles (9 families; 29 species) were recorded. Species richness and species composition for amphibians and reptiles differs according to the level of human disturbances. Low level disturbances habitat demonstrated the highest diversity of amphibians and reptiles, whereas as expected, high distubed habitat showed the lowest diversity. Anthropogenic pressures in forest will decrease species richness of amphibian and reptiles. Although most amphibian and reptiles will be able to persist in low disturbances habitat, forest-dependent species will be lost when pristine forests are disturbed.},
keywords = {anthropogenic disturbances, biodiversity, herpetofauna, Nantu Wildlife Sanctuary, Sulawesi},
pubstate = {published},
tppubtype = {article}
}
The Nantu Forest in Gorontalo Province, Sulawesi, Indonesia holds one of the few remaining pristine habitats in the island. The reserve is surrounded by human habituation which provide opportunity to study the impact of forest lost on biodversity. In addition, data on Nantu mostly focused on big mammals, as there is no previous herpetofauna survey at the area. Sampling of amphibian and reptile was conducted in June 2013 and in May–June 2014 using Visual Encounter Survey method, glue traps and transect sampling in seven different sites at the eastern part of Nantu. We categorized four habitat types based on human disturbances: high disturbed habitat (HDH), moderate disturbed habitat (MDH), low disturbed habitat (LDH) and pristine habitat (PH). A total of 680 individual amphibians (4 families; 17 species) and 119 individual reptiles (9 families; 29 species) were recorded. Species richness and species composition for amphibians and reptiles differs according to the level of human disturbances. Low level disturbances habitat demonstrated the highest diversity of amphibians and reptiles, whereas as expected, high distubed habitat showed the lowest diversity. Anthropogenic pressures in forest will decrease species richness of amphibian and reptiles. Although most amphibian and reptiles will be able to persist in low disturbances habitat, forest-dependent species will be lost when pristine forests are disturbed. |
Wijayanto, Arif K; Rushayati, Siti Badriyah; Hermawan, Rachmad; Setiawan, Yudi; Prasetyo, Lilik B Jakarta and Surabaya land surface temperature before and during the Covid-19 pandemic Journal Article In: AES Bioflux, vol. 12, no. 3, pp. 213-221, 2020, ISSN: 2066-7647. @article{Wijayanto2020,
title = {Jakarta and Surabaya land surface temperature before and during the Covid-19 pandemic},
author = {Arif K Wijayanto and Siti Badriyah Rushayati and Rachmad Hermawan and Yudi Setiawan and Lilik B Prasetyo},
url = {http://www.aes.bioflux.com.ro/docs/2020.213-221.pdf},
issn = {2066-7647},
year = {2020},
date = {2020-12-02},
journal = {AES Bioflux},
volume = {12},
number = {3},
pages = {213-221},
abstract = {The first incidence of the novel coronavirus or Covid-19 was reported in late 2019, and in the following year, the disease was declared a global pandemic. In Indonesia, the first case was reported in early March, 2020, and ever since, the government has appealed to the public to reduce outdoor activities in order to curtail the spread of the virus. Consequently, many companies and institutions implemented the ‘Work from Home’ (WFH) policy. At the end of April, the provincial government of Jakarta issued large-scale social restrictions, locally called PSBB. These restrictions were later implemented in other cities such as Surabaya. Jakarta was the epicentre of the spread of the virus in Indonesia, followed by Surabaya, the second largest city in the country. Therefore, this study aimed to analyze the Thermal Humidity Index (THI) of both cities, before and during the pandemic. Data were obtained from the MODIS Terra Land Surface Temperature and Emissivity 8-Day Global 1km, from the 1st to 14th May, 2019 (before the pandemic), and during the same period the following year (during the pandemic). Furthermore, data analysis was carried out using Google Earth Engine (GEE), a cloud-based platform for geo-spatial data analysis. The hypothesis in this study was that the social restriction policy caused a difference in the THI before and during the pandemic. Therefore, this hypothesis was proven by the results, as the policy caused a decrease in the THI during the pandemic.},
keywords = {Covid-19, Land Surface Temperature, urban heat island},
pubstate = {published},
tppubtype = {article}
}
The first incidence of the novel coronavirus or Covid-19 was reported in late 2019, and in the following year, the disease was declared a global pandemic. In Indonesia, the first case was reported in early March, 2020, and ever since, the government has appealed to the public to reduce outdoor activities in order to curtail the spread of the virus. Consequently, many companies and institutions implemented the ‘Work from Home’ (WFH) policy. At the end of April, the provincial government of Jakarta issued large-scale social restrictions, locally called PSBB. These restrictions were later implemented in other cities such as Surabaya. Jakarta was the epicentre of the spread of the virus in Indonesia, followed by Surabaya, the second largest city in the country. Therefore, this study aimed to analyze the Thermal Humidity Index (THI) of both cities, before and during the pandemic. Data were obtained from the MODIS Terra Land Surface Temperature and Emissivity 8-Day Global 1km, from the 1st to 14th May, 2019 (before the pandemic), and during the same period the following year (during the pandemic). Furthermore, data analysis was carried out using Google Earth Engine (GEE), a cloud-based platform for geo-spatial data analysis. The hypothesis in this study was that the social restriction policy caused a difference in the THI before and during the pandemic. Therefore, this hypothesis was proven by the results, as the policy caused a decrease in the THI during the pandemic. |
Rahman, Dede Aulia; Setiawan, Yudi; Wijayanto, Arif K; Aziz, Ahmad Abdul; Martiyani, Trisna Rizky Possibility of applying unmanned aerial vehicle and thermal imaging in several canopy cover class for wildlife monitoring – preliminary results Conference vol. 211, E3S Web Conf., 2020, ISSN: 2267-1242. @conference{Rahman2020b,
title = {Possibility of applying unmanned aerial vehicle and thermal imaging in several canopy cover class for wildlife monitoring – preliminary results},
author = {Dede Aulia Rahman and Yudi Setiawan and Arif K Wijayanto and Ahmad Abdul Aziz and Trisna Rizky Martiyani},
url = {https://www.e3s-conferences.org/articles/e3sconf/abs/2020/71/e3sconf_jessd2020_04007/e3sconf_jessd2020_04007.html},
doi = {10.1051/e3sconf/202021104007},
issn = {2267-1242},
year = {2020},
date = {2020-11-25},
volume = {211},
publisher = {E3S Web Conf.},
abstract = {Tropical rainforests are one of the important habitats on earth but are rarely explored because they are difficult to access, making their cryptic animals challenging to monitor. Unmanned aerial vehicle (UAV) with thermal infrared imaging (TIR) technology is gaining entry into wildlife research and monitoring. The researcher tested the possibility of applying DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to wildlife in the five tree density classes in the IPB University Campus. To assess the effectiveness of using drones in detecting wildlife, the researcher measured the optimum flying height, sound level, temperature, and optimum flight time in each canopy cover class. The optimum height for animal detection is <50 m HAGL with a sound level that animals can still tolerate. Wildlife detected had body temperatures around 27 °C and were conspicuous in the thermal infrared imagery at night and early morning when the forest canopy was cool (15–27°C), but were difficult to detect by mid-day. By that time, the direct sunshine had heated up canopy vegetation to over 30°C. Species were difficult to identify from thermal infrared imagery alone but could be recognized from synchronized visual images taken during the daytime.},
keywords = {drone, UAV},
pubstate = {published},
tppubtype = {conference}
}
Tropical rainforests are one of the important habitats on earth but are rarely explored because they are difficult to access, making their cryptic animals challenging to monitor. Unmanned aerial vehicle (UAV) with thermal infrared imaging (TIR) technology is gaining entry into wildlife research and monitoring. The researcher tested the possibility of applying DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to wildlife in the five tree density classes in the IPB University Campus. To assess the effectiveness of using drones in detecting wildlife, the researcher measured the optimum flying height, sound level, temperature, and optimum flight time in each canopy cover class. The optimum height for animal detection is <50 m HAGL with a sound level that animals can still tolerate. Wildlife detected had body temperatures around 27 °C and were conspicuous in the thermal infrared imagery at night and early morning when the forest canopy was cool (15–27°C), but were difficult to detect by mid-day. By that time, the direct sunshine had heated up canopy vegetation to over 30°C. Species were difficult to identify from thermal infrared imagery alone but could be recognized from synchronized visual images taken during the daytime. |
Rahman, Dede Aulia; Setiawan, Yudi; Wijayanto, Arif K; Aziz, Ahmad Abdul; Martiyani, Trisna Rizky An experimental approach to exploring the feasibility of unmanned aerial vehicle and thermal imaging in terrestrial and arboreal mammals research Conference vol. 211, E3S Web Conf., 2020, ISSN: 2267-1242. @conference{Rahman2020,
title = {An experimental approach to exploring the feasibility of unmanned aerial vehicle and thermal imaging in terrestrial and arboreal mammals research},
author = {Dede Aulia Rahman and Yudi Setiawan and Arif K Wijayanto and Ahmad Abdul Aziz and Trisna Rizky Martiyani},
url = {https://www.e3s-conferences.org/articles/e3sconf/abs/2020/71/e3sconf_jessd2020_02010/e3sconf_jessd2020_02010.html},
doi = {10.1051/e3sconf/202021102010},
issn = {2267-1242},
year = {2020},
date = {2020-11-25},
volume = {211},
publisher = {E3S Web Conf.},
abstract = {The visual camouflage of many species living in the dense cover of the tropical rainforest become obstacles to conducting species monitoring. Unmanned aerial vehicles (drones) combined with thermal infrared imaging (TIR) can rapidly scan large areas from above and detect wildlife that has a body temperature that contrasts with its surrounding environment. This research tested the feasibility of DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to detect terrestrial and arboreal mammals in the five tree density classes in the remaining natural environment on the IPB University campus. This study demonstrated that large-size terrestrial mammal thermal signatures are visible in sparse vegetation at daytime and in the area under the canopy at night monitoring. In contrast, arboreal mammals were better detected in at early morning and night. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. The drones allow safe operation at low altitudes with low levels of disturbance to animals. Both terrestrial and arboreal mammals are well detected and easily identified when the drone is flying at an altitude < 50 m HAGL. Our preliminary results indicated that thermal surveys from drones are a promising method.},
keywords = {drone, UAV},
pubstate = {published},
tppubtype = {conference}
}
The visual camouflage of many species living in the dense cover of the tropical rainforest become obstacles to conducting species monitoring. Unmanned aerial vehicles (drones) combined with thermal infrared imaging (TIR) can rapidly scan large areas from above and detect wildlife that has a body temperature that contrasts with its surrounding environment. This research tested the feasibility of DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to detect terrestrial and arboreal mammals in the five tree density classes in the remaining natural environment on the IPB University campus. This study demonstrated that large-size terrestrial mammal thermal signatures are visible in sparse vegetation at daytime and in the area under the canopy at night monitoring. In contrast, arboreal mammals were better detected in at early morning and night. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. The drones allow safe operation at low altitudes with low levels of disturbance to animals. Both terrestrial and arboreal mammals are well detected and easily identified when the drone is flying at an altitude < 50 m HAGL. Our preliminary results indicated that thermal surveys from drones are a promising method. |
Repi, Terri; Masy'ud, Burhanuddin; Mustari, Abdul Haris; Prasetyo, Lilik B Population density, geographical distribution and habitat of Talaud bear cuscus (Ailurops melanotis Thomas, 1898) Journal Article In: Biodiversitas, vol. 21, no. 12, pp. 5621-5631, 2020. @article{Repi2020,
title = {Population density, geographical distribution and habitat of Talaud bear cuscus (Ailurops melanotis Thomas, 1898)},
author = {Terri Repi and Burhanuddin Masy'ud and Abdul Haris Mustari and Lilik B Prasetyo},
url = {https://smujo.id/biodiv/article/view/6833},
doi = {10.13057/biodiv/d211207},
year = {2020},
date = {2020-11-06},
journal = {Biodiversitas},
volume = {21},
number = {12},
pages = {5621-5631},
abstract = {The Talaud bear cuscus (Ailurops melanotis) has been reported from Sangihe (the largest island in the Sangihe Island group) and Salibabu (within the Talaud Islands). As an endemic species of Indonesia, this species is rare and there is no certainty regarding its precise geographic distribution or population size. This research aimed to estimate population density and provide the first preliminary data on its geographical distribution, as well as general description of its habitat. Our research shows that A. melanotis occurs on three islands: Salibabu Island, Nusa Island, and Bukide Island, and probably also exists in the Sahandaruman mountain on Sangihe Island. Our population surveys estimate, population density on each island as: Salibabu: 3.69 ± 2.54 ind/km2, with an estimated total population of 28.95 individuals, Nusa Island: was 12.31 ± 2.58 ind/km2, with an estimated population of 19.08 individuals, and Bukide Island: 7.17 ± 1.79/km2, with an estimated population of 10.40 individuals. Information regarding population is a key guiding factor in conservation efforts, where population size is related to extinction risk (threat status) and its geographical distribution, this can help to determine conservation priorities for species or habitats.},
keywords = {Ailurops melanotis, conservation, density, distribution, habitat, population},
pubstate = {published},
tppubtype = {article}
}
The Talaud bear cuscus (Ailurops melanotis) has been reported from Sangihe (the largest island in the Sangihe Island group) and Salibabu (within the Talaud Islands). As an endemic species of Indonesia, this species is rare and there is no certainty regarding its precise geographic distribution or population size. This research aimed to estimate population density and provide the first preliminary data on its geographical distribution, as well as general description of its habitat. Our research shows that A. melanotis occurs on three islands: Salibabu Island, Nusa Island, and Bukide Island, and probably also exists in the Sahandaruman mountain on Sangihe Island. Our population surveys estimate, population density on each island as: Salibabu: 3.69 ± 2.54 ind/km2, with an estimated total population of 28.95 individuals, Nusa Island: was 12.31 ± 2.58 ind/km2, with an estimated population of 19.08 individuals, and Bukide Island: 7.17 ± 1.79/km2, with an estimated population of 10.40 individuals. Information regarding population is a key guiding factor in conservation efforts, where population size is related to extinction risk (threat status) and its geographical distribution, this can help to determine conservation priorities for species or habitats. |
Septiana, Wardi; Munawir, Ahmad; Pairah,; Erlan, Mochamad; Irawan, Yosi; Santosa, Yanto; Prasetyo, Lilik B Distribution and Characteristics of Javan Hawk Eagle Nesting Trees in Gunung Halimun Salak National Park, Indonesia Journal Article In: Jurnal Biodjati, vol. 5, no. 2, pp. 182-190, 2020, ISSN: 2541-4208. @article{Septiana2020,
title = {Distribution and Characteristics of Javan Hawk Eagle Nesting Trees in Gunung Halimun Salak National Park, Indonesia},
author = {Wardi Septiana and Ahmad Munawir and Pairah and Mochamad Erlan and Yosi Irawan and Yanto Santosa and Lilik B Prasetyo},
url = {https://journal.uinsgd.ac.id/index.php/biodjati/article/view/8481},
doi = {10.15575/biodjati.v5i2.8481},
issn = {2541-4208},
year = {2020},
date = {2020-11-01},
journal = {Jurnal Biodjati},
volume = {5},
number = {2},
pages = {182-190},
abstract = {Javan Hawk Eagle is one of the three keys species of the Gunung Halimun Salak National Park and endemic to the island of Java. Protecting the active Javan Hawk Eagle nesting tree is one of the efforts to increase the success rate of Java Hawk Eagle breeding so that information on the distribution and characteris-tics of Javan Hawk Eagle nesting tree is needed. Field exploration was carried out to determine the existence of the Javan Hawk Eagle nest. There were 10 individuals of Javan Hawk Eagle nesting trees which consisted of 5 species namely Rasamala, Huru, Damar, Leng-sar and Manggong with tree architecture models of rauh, massart, scarrone and aubreville, tree height between 26-55 m and height of nests between 18-41m. The Javan Hawk Eagle nesting trees grow in primary, secondary, and plantation forests in a height between 670- 1295 masl, with a steep and very steep slope, the majority of the dis-tance from the river is less than 100 m and the majority of the dis-tance with ecotone is less than 600 m. Javan Hawk Eagle nest on Damar is the first finding at Gunung Halimun Salak National Park. },
keywords = {Gunung Halimun Salak National Park, Javan Hawk Eagle},
pubstate = {published},
tppubtype = {article}
}
Javan Hawk Eagle is one of the three keys species of the Gunung Halimun Salak National Park and endemic to the island of Java. Protecting the active Javan Hawk Eagle nesting tree is one of the efforts to increase the success rate of Java Hawk Eagle breeding so that information on the distribution and characteris-tics of Javan Hawk Eagle nesting tree is needed. Field exploration was carried out to determine the existence of the Javan Hawk Eagle nest. There were 10 individuals of Javan Hawk Eagle nesting trees which consisted of 5 species namely Rasamala, Huru, Damar, Leng-sar and Manggong with tree architecture models of rauh, massart, scarrone and aubreville, tree height between 26-55 m and height of nests between 18-41m. The Javan Hawk Eagle nesting trees grow in primary, secondary, and plantation forests in a height between 670- 1295 masl, with a steep and very steep slope, the majority of the dis-tance from the river is less than 100 m and the majority of the dis-tance with ecotone is less than 600 m. Javan Hawk Eagle nest on Damar is the first finding at Gunung Halimun Salak National Park. |
Atmoko, Tri; Mardiastuti, Ani; Bismark, M; Prasetyo, Lilik B; Iskandar, Entang Habitat suitability of Proboscis monkey (Nasalis larvatus) in Berau Delta, East Kalimantan, Indonesia Journal Article In: Biodiversitas, vol. 21, no. 11, pp. 5155-5163, 2020. @article{Atmoko2020,
title = {Habitat suitability of Proboscis monkey (Nasalis larvatus) in Berau Delta, East Kalimantan, Indonesia},
author = {Tri Atmoko and Ani Mardiastuti and M Bismark and Lilik B Prasetyo and Entang Iskandar},
url = {https://smujo.id/biodiv/article/view/6873},
doi = {10.13057/biodiv/d211121},
year = {2020},
date = {2020-10-14},
journal = {Biodiversitas},
volume = {21},
number = {11},
pages = {5155-5163},
abstract = {The proboscis monkey (Nasalis larvatus) is an endemic species to Borneos’ island and is largely confined to mangrove, riverine, and swamp forest. Most of their habitat is outside the conservation due to degraded and habitat converted. Habitat loss is a significant threat to a decreased in the monkey's population. Berau Delta is an unprotected habitat of proboscis monkey, lacking in attention and experiencing a lot of disturbances. This study was conducted on April – August 2019; with aims of the study is to determine Species Distribution Modeling (SDM) for identifying proboscis monkey habitat suitability in Delta Berau, East Kalimantan. The MaxEnt algorithm was used to produce a habitat suitability map based on this species’ occurrence records and environmental predictors. We built the models using 208 points of proboscis monkey presence and 12 environment variables within the study area. Model performance was assessed by examining the area under the curve. The variables most influencing the habitat suitability model were the riverine habitat (60.9%), distance from the pond (16.0%), and distance from the coastline (5.2%). The proboscis monkey suitable habitat is only 9.32% (8,726.58 ha) from 93,631.41 ha total area. The appropriate habitat areas are Sapinang Island, Bungkung Island, Sambuayan Island, Saodang Kecil Island, Besing Island, Lati River, Bebanir Lama, Batu-Batu, and Semanting Bay. We provide some suggestions for the proboscis monkey conservation, which are local protection of uninhabited islands, participatory ecotourism management, and company involvement in protection and management efforts.},
keywords = {Colobinae, MaxEnt, primate conservation, riverine forest, Species Distribution Model},
pubstate = {published},
tppubtype = {article}
}
The proboscis monkey (Nasalis larvatus) is an endemic species to Borneos’ island and is largely confined to mangrove, riverine, and swamp forest. Most of their habitat is outside the conservation due to degraded and habitat converted. Habitat loss is a significant threat to a decreased in the monkey's population. Berau Delta is an unprotected habitat of proboscis monkey, lacking in attention and experiencing a lot of disturbances. This study was conducted on April – August 2019; with aims of the study is to determine Species Distribution Modeling (SDM) for identifying proboscis monkey habitat suitability in Delta Berau, East Kalimantan. The MaxEnt algorithm was used to produce a habitat suitability map based on this species’ occurrence records and environmental predictors. We built the models using 208 points of proboscis monkey presence and 12 environment variables within the study area. Model performance was assessed by examining the area under the curve. The variables most influencing the habitat suitability model were the riverine habitat (60.9%), distance from the pond (16.0%), and distance from the coastline (5.2%). The proboscis monkey suitable habitat is only 9.32% (8,726.58 ha) from 93,631.41 ha total area. The appropriate habitat areas are Sapinang Island, Bungkung Island, Sambuayan Island, Saodang Kecil Island, Besing Island, Lati River, Bebanir Lama, Batu-Batu, and Semanting Bay. We provide some suggestions for the proboscis monkey conservation, which are local protection of uninhabited islands, participatory ecotourism management, and company involvement in protection and management efforts. |
Condro, Aryo Adhi; Setiawan, Yudi; Prasetyo, Lilik B; Pramulya, Rahmat; Siahaan, Lasriama Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform Journal Article In: Land, vol. 9, no. 10, pp. 377, 2020. @article{Condro2020,
title = {Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform},
author = {Aryo Adhi Condro and Yudi Setiawan and Lilik B Prasetyo and Rahmat Pramulya and Lasriama Siahaan},
url = {https://www.mdpi.com/2073-445X/9/10/377https://algm.ipb.ac.id/wp-content/uploads/2020/11/land-09-00377.pdf},
doi = {10.3390/land9100377},
year = {2020},
date = {2020-10-08},
journal = {Land},
volume = {9},
number = {10},
pages = {377},
abstract = {Indonesia has the most favorable climates for agriculture because of its location in the tropical climatic zones. The country has several commodities to support economics growth that are driven by key export commodities—e.g., oil palm, rubber, paddy, cacao, and coffee. Thus, identifying the main commodities in Indonesia using spatially-explicit tools is essential to understand the precise productivity derived from the agricultural sectors. Many previous studies have used predictions developed using binary maps of general crop cover. Here, we present national commodity maps for Indonesia based on remote sensing data using Google Earth Engine. We evaluated a machine learning algorithm—i.e., Random Forest to parameterize how the area in commodity varied in Indonesia. We used various predictors to estimate the productivity of various commodities based on multispectral satellite imageries (36 predictors) at 30-meters spatial resolution. The national commodity map has a relatively high accuracy, with an overall accuracy of about 95% and Kappa coefficient of about 0.90. The results suggest that the oil palm plantation was the highest commodity product that occupied the largest land of Indonesia. However, this study also showed that the land area in rubber, rice paddies, and cacao commodities was underestimated due to its lack of training samples. Improvement in training data collection for each commodity should be done to increase the accuracy of the commodity maps. The commodity data can be viewed online (website can be found in the end of conclusions). This data can further provide significant information related to the agricultural sectors to investigate food provisioning, particularly in Indonesia.},
keywords = {commodity, GEE},
pubstate = {published},
tppubtype = {article}
}
Indonesia has the most favorable climates for agriculture because of its location in the tropical climatic zones. The country has several commodities to support economics growth that are driven by key export commodities—e.g., oil palm, rubber, paddy, cacao, and coffee. Thus, identifying the main commodities in Indonesia using spatially-explicit tools is essential to understand the precise productivity derived from the agricultural sectors. Many previous studies have used predictions developed using binary maps of general crop cover. Here, we present national commodity maps for Indonesia based on remote sensing data using Google Earth Engine. We evaluated a machine learning algorithm—i.e., Random Forest to parameterize how the area in commodity varied in Indonesia. We used various predictors to estimate the productivity of various commodities based on multispectral satellite imageries (36 predictors) at 30-meters spatial resolution. The national commodity map has a relatively high accuracy, with an overall accuracy of about 95% and Kappa coefficient of about 0.90. The results suggest that the oil palm plantation was the highest commodity product that occupied the largest land of Indonesia. However, this study also showed that the land area in rubber, rice paddies, and cacao commodities was underestimated due to its lack of training samples. Improvement in training data collection for each commodity should be done to increase the accuracy of the commodity maps. The commodity data can be viewed online (website can be found in the end of conclusions). This data can further provide significant information related to the agricultural sectors to investigate food provisioning, particularly in Indonesia. |
Juniyanti, Lila; Prasetyo, Lilik B; Aprianto, Dwi Putra; Purnomo, Herry; Kartodiharjo, Hariadi Perubahan penggunaan dan tutupan lahan, serta faktor penyebabnya di Pulau Bengkalis, Provinsi Riau (periode 1990-2019) Journal Article In: Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan, vol. 10, no. 3, pp. 419-435, 2020. @article{Juniyanti2020,
title = {Perubahan penggunaan dan tutupan lahan, serta faktor penyebabnya di Pulau Bengkalis, Provinsi Riau (periode 1990-2019)},
author = {Lila Juniyanti and Lilik B Prasetyo and Dwi Putra Aprianto and Herry Purnomo and Hariadi Kartodiharjo},
url = {http://journal.ipb.ac.id/index.php/jpsl/article/view/31164},
doi = {10.29244/jpsl.10.3.419-435},
year = {2020},
date = {2020-10-01},
journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan},
volume = {10},
number = {3},
pages = {419-435},
abstract = {Indonesia is one of the countries with dynamic land cover changes because the country's economy is sourced from land-based resource management. On the other hand, it has negative impacts such as social conflict and environmental damage. This paper observed patterns of land change and explores its driving forces during 1900-2019 on Bengkalis Island, Indonesia to monitor and provide information that can be used as a base for reducing uncontrolled land-use changes in an area. We reviewed previous reports and research, observed land cover conditions in the field, carried out focus group discussions, and deep interviews. We implemented GIS to capture time-series land cover and land-use changes. The results showed that the forest cover has declined sharply since 1990. After 2000, the area of mixed garden was larger than the forest cover. The area of oil palm and forest plantations began to increase. The transmigration policy has triggered masive land clearing on Bengkalis Island. Land clearing by transmigrants and the economic crisis have led to greater land clearing by spontaneous transmigrants.},
keywords = {direct causes, spatial analysis, time-series, underlying causes},
pubstate = {published},
tppubtype = {article}
}
Indonesia is one of the countries with dynamic land cover changes because the country's economy is sourced from land-based resource management. On the other hand, it has negative impacts such as social conflict and environmental damage. This paper observed patterns of land change and explores its driving forces during 1900-2019 on Bengkalis Island, Indonesia to monitor and provide information that can be used as a base for reducing uncontrolled land-use changes in an area. We reviewed previous reports and research, observed land cover conditions in the field, carried out focus group discussions, and deep interviews. We implemented GIS to capture time-series land cover and land-use changes. The results showed that the forest cover has declined sharply since 1990. After 2000, the area of mixed garden was larger than the forest cover. The area of oil palm and forest plantations began to increase. The transmigration policy has triggered masive land clearing on Bengkalis Island. Land clearing by transmigrants and the economic crisis have led to greater land clearing by spontaneous transmigrants. |
Suyamto, Desi; Condro, Aryo Adhi; Prasetyo, Lilik B; Wijayanto, Arif K Assessing the Agreement between Deforestation Maps of Kalimantan from Various Sources Conference vol. 556, no. 1, IOP Conf. Ser.: Earth Environ. Sci, 2020. @conference{Suyamto2020,
title = {Assessing the Agreement between Deforestation Maps of Kalimantan from Various Sources},
author = {Desi Suyamto and Aryo Adhi Condro and Lilik B Prasetyo and Arif K Wijayanto},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/556/1/012011/pdf},
doi = {10.1088/1755-1315/556/1/012011},
year = {2020},
date = {2020-09-22},
volume = {556},
number = {1},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {Due to its multiscale impacts, deforestation of tropical rainforests had become a global concern. A number of stakeholders comprising government, research agencies, and NGOs; ranging from local to international levels; have developed their own forest monitoring systems for detecting forest loss. However, discrepancies on deforestation reports from various producers often trigger public debates; which mostly degenerate the productivity of efforts in providing salient, legitimate and credible data on deforestation. Thus, we should reconcile the dispute by acknowledging the deforestation data from all sources. This study assessed the agreement between deforestation maps from various sources. In this case, deforestation maps of Kalimantan within 2009-2013 period from 4 sources were used; i.e. deforestation maps from European Space Agency - Climate Change Initiative (ESA-CCI), Forest Watch Indonesia (FWI), Global Forest Watch (GFW), and Indonesian Ministry of Environment and Forestry (MoEF). We found that the inter-rater agreement between deforestation maps were relatively low, as indicated by Cohen's kappa (κ), ranging from slight (κ=0.18 between ESA-CCI and GFW) to fair (0.24 ≤ κ ≤ 0.35 for other pairs of sources); due to omission/commission disagreements (47.82% to 87.58%). It suggests that in order to reconcile the dispute, we should remove the omission disagreement by forming the union of deforestation maps. The results from further analyses proved that the union of deforestation maps increased the agreement to moderate (κ=0.44 between union map and FWI) and even substantial (κ=0.79 between union map and GFW). Findings of this study should support the implementation of one map policy.},
keywords = {deforestation},
pubstate = {published},
tppubtype = {conference}
}
Due to its multiscale impacts, deforestation of tropical rainforests had become a global concern. A number of stakeholders comprising government, research agencies, and NGOs; ranging from local to international levels; have developed their own forest monitoring systems for detecting forest loss. However, discrepancies on deforestation reports from various producers often trigger public debates; which mostly degenerate the productivity of efforts in providing salient, legitimate and credible data on deforestation. Thus, we should reconcile the dispute by acknowledging the deforestation data from all sources. This study assessed the agreement between deforestation maps from various sources. In this case, deforestation maps of Kalimantan within 2009-2013 period from 4 sources were used; i.e. deforestation maps from European Space Agency - Climate Change Initiative (ESA-CCI), Forest Watch Indonesia (FWI), Global Forest Watch (GFW), and Indonesian Ministry of Environment and Forestry (MoEF). We found that the inter-rater agreement between deforestation maps were relatively low, as indicated by Cohen's kappa (κ), ranging from slight (κ=0.18 between ESA-CCI and GFW) to fair (0.24 ≤ κ ≤ 0.35 for other pairs of sources); due to omission/commission disagreements (47.82% to 87.58%). It suggests that in order to reconcile the dispute, we should remove the omission disagreement by forming the union of deforestation maps. The results from further analyses proved that the union of deforestation maps increased the agreement to moderate (κ=0.44 between union map and FWI) and even substantial (κ=0.79 between union map and GFW). Findings of this study should support the implementation of one map policy. |
Irlan,; Saleh, Muhammad Buce; Prasetyo, Lilik B; Setiawan, Yudi Evaluation of Tree Detection and Segmentation Algorithms in Peat Swamp Forest Based on LiDAR Point Clouds Data Journal Article In: Jurnal Manajemen Hutan Tropika, vol. 26, no. 2, pp. 123-132, 2020, ISSN: 2089-2063. @article{Irlan2020,
title = {Evaluation of Tree Detection and Segmentation Algorithms in Peat Swamp Forest Based on LiDAR Point Clouds Data},
author = {Irlan and Muhammad Buce Saleh and Lilik B Prasetyo and Yudi Setiawan},
url = {http://journal.ipb.ac.id/index.php/jmht/article/view/30179},
doi = {10.7226/jtfm.26.2.123},
issn = {2089-2063},
year = {2020},
date = {2020-08-13},
journal = {Jurnal Manajemen Hutan Tropika},
volume = {26},
number = {2},
pages = {123-132},
abstract = {Application of LiDAR for tree detection and tree canopy segmentation has been widely used in conifer plantation forest in temperate countries with high accuracy, however its application on tropical natural forest especially peat swamp forest hardly found. The objective of this study was evaluated algorithms of individual tree detection and canopy segmentation used LiDAR data in peat swamp forest. The algorithms included (a) Local Maxima (LM) with various variable window size combined with growing region, (b) LM with various variable window size combined with Voronoi Tessellation, (c) LM with various fixed window size combined with growing region, (d) LM with various fixed window size combined with Voronoi Tessellation, and (e) Tree Relative Distance algorithm. The results show that algorithm with the best accuracy was the Tree Relative Distance algorithm with the highest overall F-score of 0.63. The tree relative distance algorithm also provides the highest accuracy in determining three tree parameters which are position, height and diameter of tree canopy with a RMSE value 1.08 m, 6.45 m and 1.19 m, respectively.},
keywords = {LiDAR, peat swamp, segmentation},
pubstate = {published},
tppubtype = {article}
}
Application of LiDAR for tree detection and tree canopy segmentation has been widely used in conifer plantation forest in temperate countries with high accuracy, however its application on tropical natural forest especially peat swamp forest hardly found. The objective of this study was evaluated algorithms of individual tree detection and canopy segmentation used LiDAR data in peat swamp forest. The algorithms included (a) Local Maxima (LM) with various variable window size combined with growing region, (b) LM with various variable window size combined with Voronoi Tessellation, (c) LM with various fixed window size combined with growing region, (d) LM with various fixed window size combined with Voronoi Tessellation, and (e) Tree Relative Distance algorithm. The results show that algorithm with the best accuracy was the Tree Relative Distance algorithm with the highest overall F-score of 0.63. The tree relative distance algorithm also provides the highest accuracy in determining three tree parameters which are position, height and diameter of tree canopy with a RMSE value 1.08 m, 6.45 m and 1.19 m, respectively. |
Irlan,; Saleh, Muhammad Buce; Prasetyo, Lilik B Evaluation of Tree Detection and Segmentation Algorithms in Peat Swamp Forest Based on LiDAR Point Clouds Data Journal Article In: Jurnal Manajemen Hutan Tropika, vol. 26, no. 2, pp. 123, 2020, ISSN: 2089-2063. @article{Irlan2020b,
title = {Evaluation of Tree Detection and Segmentation Algorithms in Peat Swamp Forest Based on LiDAR Point Clouds Data},
author = {Irlan and Muhammad Buce Saleh and Lilik B Prasetyo},
url = {https://journal.ipb.ac.id/index.php/jmht/article/view/30179},
doi = {10.7226/jtfm.26.2.123},
issn = {2089-2063},
year = {2020},
date = {2020-08-13},
journal = {Jurnal Manajemen Hutan Tropika},
volume = {26},
number = {2},
pages = {123},
abstract = {Application of LiDAR for tree detection and tree canopy segmentation has been widely used in conifer plantation forest in temperate countries with high accuracy, however its application on tropical natural forest especially peat swamp forest hardly found. The objective of this study was evaluated algorithms of individual tree detection and canopy segmentation used LiDAR data in peat swamp forest. The algorithms included (a) Local Maxima (LM) with various variable window size combined with growing region, (b) LM with various variable window size combined with Voronoi Tessellation, (c) LM with various fixed window size combined with growing region, (d) LM with various fixed window size combined with Voronoi Tessellation, and (e) Tree Relative Distance algorithm. The results show that algorithm with the best accuracy was the Tree Relative Distance algorithm with the highest overall F-score of 0.63. The tree relative distance algorithm also provides the highest accuracy in determining three tree parameters which are position, height and diameter of tree canopy with a RMSE value 1.08 m, 6.45 m and 1.19 m, respectively.},
keywords = {LiDAR, peat swamp, point cloud},
pubstate = {published},
tppubtype = {article}
}
Application of LiDAR for tree detection and tree canopy segmentation has been widely used in conifer plantation forest in temperate countries with high accuracy, however its application on tropical natural forest especially peat swamp forest hardly found. The objective of this study was evaluated algorithms of individual tree detection and canopy segmentation used LiDAR data in peat swamp forest. The algorithms included (a) Local Maxima (LM) with various variable window size combined with growing region, (b) LM with various variable window size combined with Voronoi Tessellation, (c) LM with various fixed window size combined with growing region, (d) LM with various fixed window size combined with Voronoi Tessellation, and (e) Tree Relative Distance algorithm. The results show that algorithm with the best accuracy was the Tree Relative Distance algorithm with the highest overall F-score of 0.63. The tree relative distance algorithm also provides the highest accuracy in determining three tree parameters which are position, height and diameter of tree canopy with a RMSE value 1.08 m, 6.45 m and 1.19 m, respectively. |
Oktavia, Reno Catelya Dira; Siregar, Hermanto; Sunarminto, Totok; Hermawan, Rachmad Analysis of Social and Psychological Factors Determining Satisfaction of Visitors to Urban Parks and Urban Forests Parks in DKI Jakarta Journal Article In: Media Konservasi, vol. 25, no. 2, pp. 156-166, 2020. @article{Oktavia2020,
title = {Analysis of Social and Psychological Factors Determining Satisfaction of Visitors to Urban Parks and Urban Forests Parks in DKI Jakarta},
author = {Reno Catelya Dira Oktavia and Hermanto Siregar and Totok Sunarminto and Rachmad Hermawan},
url = {https://jurnal.ipb.ac.id/index.php/konservasi/article/view/32467},
doi = {10.29244/medkon.25.2.156-166},
year = {2020},
date = {2020-08-04},
journal = {Media Konservasi},
volume = {25},
number = {2},
pages = {156-166},
abstract = {Faktor sosial dan psikologi sangat berpengaruh terhadap tingkat kepuasan pengunjung selama berekreasi di taman kota dan taman hutan kota (THK) dalam wilayah DKI Jakarta. Penelitian ini bertujuan untuk menganalisis faktor sosial dan psikologi di dalam taman kota dan THK dalam kaitannya dengan tingkat kepuasan pengunjung. Data penelitian dikumpulkan dari responden dengan alat bantu kuesioner, menerapkan pola One Score One Indicator Scoring System. Jumlah responden sebanyak 600 orang dengan metode purposive sampling. Analisis data menggunakan metode importance performance analysis, customer satisfaction index, analisis statistik korelasi dan regresi. Hasil penelitian menunjukkan bahwa terdapat lima aspek sosial dan psikologi yang mempengaruhi tingkat kepuasan pengunjung. Aspek yang memiliki nilai kepentingan tinggi dan nilai kepuasan tinggi adalah aspek atmosfer berkegiatan, sedangkan yang bernilai rendah adalah aspek keamanan dan keselamatan. Analisis korelasi Spearman menunjukkan bahwa dari kelima aspek sosial dan psikologi tersebut satu sama lain memiliki tingkat asosiasi atau hubungan yang sangat dekat dengan nilai koefisien yang positif. Berdasarkan analisis regresi kepuasan pengunjung; aspek atmosfer berkegiatan, aspek aktivitas rekreasi, aspek kenyamanan berpengaruh secara signifikan, sedangkan aspek kontak sosial dan faktor keamanan dan keselamatan tidak berpengaruh signifikan terhadap kepuasan pengunjung. },
keywords = {urban forest, urban park},
pubstate = {published},
tppubtype = {article}
}
Faktor sosial dan psikologi sangat berpengaruh terhadap tingkat kepuasan pengunjung selama berekreasi di taman kota dan taman hutan kota (THK) dalam wilayah DKI Jakarta. Penelitian ini bertujuan untuk menganalisis faktor sosial dan psikologi di dalam taman kota dan THK dalam kaitannya dengan tingkat kepuasan pengunjung. Data penelitian dikumpulkan dari responden dengan alat bantu kuesioner, menerapkan pola One Score One Indicator Scoring System. Jumlah responden sebanyak 600 orang dengan metode purposive sampling. Analisis data menggunakan metode importance performance analysis, customer satisfaction index, analisis statistik korelasi dan regresi. Hasil penelitian menunjukkan bahwa terdapat lima aspek sosial dan psikologi yang mempengaruhi tingkat kepuasan pengunjung. Aspek yang memiliki nilai kepentingan tinggi dan nilai kepuasan tinggi adalah aspek atmosfer berkegiatan, sedangkan yang bernilai rendah adalah aspek keamanan dan keselamatan. Analisis korelasi Spearman menunjukkan bahwa dari kelima aspek sosial dan psikologi tersebut satu sama lain memiliki tingkat asosiasi atau hubungan yang sangat dekat dengan nilai koefisien yang positif. Berdasarkan analisis regresi kepuasan pengunjung; aspek atmosfer berkegiatan, aspek aktivitas rekreasi, aspek kenyamanan berpengaruh secara signifikan, sedangkan aspek kontak sosial dan faktor keamanan dan keselamatan tidak berpengaruh signifikan terhadap kepuasan pengunjung. |
Tompodung, Tirza Carol Gracia; Rushayati, Siti Badriyah; Aidi, M Nur EFEKTIVITAS PROGRAM ADIWIYATA TERHADAP PERILAKU RAMAH LINGKUNGAN WARGA SEKOLAH DI KOTA DEPOK Journal Article In: Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan, vol. 8, no. 2, pp. 170-177, 2020, ISSN: 2460-4639. @article{Tompodung2020,
title = {EFEKTIVITAS PROGRAM ADIWIYATA TERHADAP PERILAKU RAMAH LINGKUNGAN WARGA SEKOLAH DI KOTA DEPOK},
author = {Tirza Carol Gracia Tompodung and Siti Badriyah Rushayati and M Nur Aidi},
url = {https://jurnal.ipb.ac.id/index.php/jpsl/article/view/17706},
doi = {10.29244/jpsl.8.2.170-177},
issn = {2460-4639},
year = {2020},
date = {2020-08-01},
journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan},
volume = {8},
number = {2},
pages = {170-177},
abstract = {Since 2006, Ministry of Environment has promote environmental education, within the framework of a program for education for sustainable development to raise enviromental knowledge and awareness called Adiwiyata. Adiwiyata program runs on a voluntary and formal school in Indonesia. The Adiwiyata school program aims to encourage schools to adopt behaviours that are respectful towards the environment. As a prize of appreciation, the Ministry of Environment gives Adiwiyata awards to a schools that has succeed to met the criteria of green school environment. In 2014, Depok City government proposed nine schools to become National Adiwiyata School, but only six schools has pass the verification of healthy, clean, and beautiful encvironment and was awarded National Adiwiyata thropy and certificate. The study was conducted in order to test the level of knowledge, attitudes and behaviour of the school community that implemented Adiwiyata program, as well as the effectiveness of the program is to improve the knowledge and awaraness through policy insight, implementation of environmental based curriculum, environmental participatory based activity, and sustainable management of supporting facilitie, to support the responsible for the protection and management of environment. The study concluded that Adiwiyata program evident effective to change the green behaviors of school community.},
keywords = {adiwiyata},
pubstate = {published},
tppubtype = {article}
}
Since 2006, Ministry of Environment has promote environmental education, within the framework of a program for education for sustainable development to raise enviromental knowledge and awareness called Adiwiyata. Adiwiyata program runs on a voluntary and formal school in Indonesia. The Adiwiyata school program aims to encourage schools to adopt behaviours that are respectful towards the environment. As a prize of appreciation, the Ministry of Environment gives Adiwiyata awards to a schools that has succeed to met the criteria of green school environment. In 2014, Depok City government proposed nine schools to become National Adiwiyata School, but only six schools has pass the verification of healthy, clean, and beautiful encvironment and was awarded National Adiwiyata thropy and certificate. The study was conducted in order to test the level of knowledge, attitudes and behaviour of the school community that implemented Adiwiyata program, as well as the effectiveness of the program is to improve the knowledge and awaraness through policy insight, implementation of environmental based curriculum, environmental participatory based activity, and sustainable management of supporting facilitie, to support the responsible for the protection and management of environment. The study concluded that Adiwiyata program evident effective to change the green behaviors of school community. |
Maulana, F. A.; Rushayati, Siti Badriyah; Setiawan, Yudi Characteristics of forest and land fires in Baluran National Park, Situbondo Regency, East Java Conference vol. 528, no. 1, IOP Conf. Ser.: Earth Environ. Sci., 2020. @conference{Maulana2020,
title = {Characteristics of forest and land fires in Baluran National Park, Situbondo Regency, East Java},
author = {F.A. Maulana and Siti Badriyah Rushayati and Yudi Setiawan
},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/528/1/012059},
doi = {10.1088/1755-1315/528/1/012059},
year = {2020},
date = {2020-07-21},
volume = {528},
number = {1},
publisher = {IOP Conf. Ser.: Earth Environ. Sci.},
abstract = {Fire events of Baluran National Park occured periodically in the dry season. The impacts of the fires was a changes in physical, chemical and biological aspects of the ecosystem that can be illustrated as the fire severity. Important information for habitat management, is vegetation and air temperature as biological and physical aspects. This study aims to identify burned areas and classes of fire severity and to explain the character of fires based vegetation's aspects and air temperature during the fire periods. The character of the fires was described by analysis of normalized burn ratio (NBR), normalized difference vegetation index (NDVI), and the calculation of air temperature under conditions prefires, postfires, and the delta's value. Burned areas in Baluran National Park were identified as 1798.92 ha which classified into fire severity class as low class (1252.71 ha), medium class (543.79 ha), and severe class (2.43 ha). Savanna has a value of dNDVI of 0.2543 which is caused by logging acacia wood for firewood and dNBR of 0.0677 that indicated by burning by the local people for grass growth as livestock's feed. Changes in the air temperature of the savanna of 8.6 0C. Increasing of air temperature is followed by decreasing of vegetation index (dNDVI an dNBR), but changes in air temperature tend to follow the dNBR's trend rather than the dNDVI's trend.},
keywords = {land fire},
pubstate = {published},
tppubtype = {conference}
}
Fire events of Baluran National Park occured periodically in the dry season. The impacts of the fires was a changes in physical, chemical and biological aspects of the ecosystem that can be illustrated as the fire severity. Important information for habitat management, is vegetation and air temperature as biological and physical aspects. This study aims to identify burned areas and classes of fire severity and to explain the character of fires based vegetation's aspects and air temperature during the fire periods. The character of the fires was described by analysis of normalized burn ratio (NBR), normalized difference vegetation index (NDVI), and the calculation of air temperature under conditions prefires, postfires, and the delta's value. Burned areas in Baluran National Park were identified as 1798.92 ha which classified into fire severity class as low class (1252.71 ha), medium class (543.79 ha), and severe class (2.43 ha). Savanna has a value of dNDVI of 0.2543 which is caused by logging acacia wood for firewood and dNBR of 0.0677 that indicated by burning by the local people for grass growth as livestock's feed. Changes in the air temperature of the savanna of 8.6 0C. Increasing of air temperature is followed by decreasing of vegetation index (dNDVI an dNBR), but changes in air temperature tend to follow the dNBR's trend rather than the dNDVI's trend. |
Saninah, Tsamarah Nada; Rushayati, Siti Badriyah; Hermawan, Rachmad Urban forest development at landside of Hang Nadim Batam Airport based on the microclimate and noise study Conference vol. 528, IOP Conf. Ser.: Earth Environ. Sci, 2020. @conference{Saninah2020,
title = {Urban forest development at landside of Hang Nadim Batam Airport based on the microclimate and noise study},
author = {Tsamarah Nada Saninah and Siti Badriyah Rushayati and Rachmad Hermawan},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/528/1/012064/meta},
doi = {10.1088/1755-1315/528/1/012064},
year = {2020},
date = {2020-07-21},
volume = {528},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {The landside of Hang Nadim Batam Airport can be adapted to urban forests to reduce emissions, stabilize the microclimate, and reduce noise. The purpose of this research are to study the microclimate and noise around the Hang Nadim Batam Airport, and develop landside based on the condition of the airport urban forest. Research was conducted on April, 8th-15th 2019 based on the density of vegetation. Location determining, characteristics of trees and leaf area index, air temperature and humidity, and noise were used as the methods of this research. The factors that analyzed by this research were NDVI, tree profile diagrams, LAI, air temperature and humidity, thermal humidity, and noise. The result showed that there were 55 trees of 11 species from 6 families. The profile diagram showed the densest vegetation was at point F, one of the points of measurements with dense vegetation category, seen by horizontally and vertically. The highest air temperature and thermal humidity was at point E and the lowest was at point F. The highest humidity was at point F and the lowest was at point E. The highest noise was at rare vegetation and the lowest was at dense vegetation. Landside development needs to look at ecology, technical, and aesthetic.},
keywords = {microclimate, noise, urban forest},
pubstate = {published},
tppubtype = {conference}
}
The landside of Hang Nadim Batam Airport can be adapted to urban forests to reduce emissions, stabilize the microclimate, and reduce noise. The purpose of this research are to study the microclimate and noise around the Hang Nadim Batam Airport, and develop landside based on the condition of the airport urban forest. Research was conducted on April, 8th-15th 2019 based on the density of vegetation. Location determining, characteristics of trees and leaf area index, air temperature and humidity, and noise were used as the methods of this research. The factors that analyzed by this research were NDVI, tree profile diagrams, LAI, air temperature and humidity, thermal humidity, and noise. The result showed that there were 55 trees of 11 species from 6 families. The profile diagram showed the densest vegetation was at point F, one of the points of measurements with dense vegetation category, seen by horizontally and vertically. The highest air temperature and thermal humidity was at point E and the lowest was at point F. The highest humidity was at point F and the lowest was at point E. The highest noise was at rare vegetation and the lowest was at dense vegetation. Landside development needs to look at ecology, technical, and aesthetic. |
Maulana, Sandhi I; Syaufina, Lailan; Prasetyo, Lilik B; Aidi, M N A spatial decision support system for peatland fires prediction and prevention in Bengkalis Regency, Indonesia Conference vol. 528, IOP Conf. Ser.: Earth Environ. Sci, 2020. @conference{Maulana2020b,
title = {A spatial decision support system for peatland fires prediction and prevention in Bengkalis Regency, Indonesia},
author = {Sandhi I Maulana and Lailan Syaufina and Lilik B Prasetyo and M N Aidi},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/528/1/012052/meta},
doi = {10.1088/1755-1315/528/1/012052},
year = {2020},
date = {2020-07-21},
volume = {528},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {A Spatial decision support system (SDSS) is an integrated computer-based system that can be used to support decision makers in addressing spatial problems through iterative approaches with functionality for handling both of spatial and non-spatial databases, analytical modelling capabilities, decision making support, as well as effective data and information presentation utilities. Previously, many studies have proven that this kind of decision support system is also useful in addressing wildfires problems effectively. Considering this technological advancement, this study is primarily aimed to develop a peatland fires management system by implementing the concept of SDSS. Developed system in this study is consisting of two separate sub-system, namely prediction and prevention sub-systems, which are then integrated into one whole working scheme using loose coupling method. Overall, it can be concluded that such integrated prediction and prevention system has various advantages. Firstly, it is useful to establish rapid coordination among involved stakeholders in deciding suitable approaches to prevent peatland fires. Secondly, promoting a more pro-active fire management system that is relied on predict-and-prevent approach. Thirdly, avoiding further delay on fires prevention while minimizing error in resources allocation. Lastly, this kind of decision support system can be rapidly updated following on-going technological and field situation developments.},
keywords = {Bengkalis, DSS, fire, peat land, Riau},
pubstate = {published},
tppubtype = {conference}
}
A Spatial decision support system (SDSS) is an integrated computer-based system that can be used to support decision makers in addressing spatial problems through iterative approaches with functionality for handling both of spatial and non-spatial databases, analytical modelling capabilities, decision making support, as well as effective data and information presentation utilities. Previously, many studies have proven that this kind of decision support system is also useful in addressing wildfires problems effectively. Considering this technological advancement, this study is primarily aimed to develop a peatland fires management system by implementing the concept of SDSS. Developed system in this study is consisting of two separate sub-system, namely prediction and prevention sub-systems, which are then integrated into one whole working scheme using loose coupling method. Overall, it can be concluded that such integrated prediction and prevention system has various advantages. Firstly, it is useful to establish rapid coordination among involved stakeholders in deciding suitable approaches to prevent peatland fires. Secondly, promoting a more pro-active fire management system that is relied on predict-and-prevent approach. Thirdly, avoiding further delay on fires prevention while minimizing error in resources allocation. Lastly, this kind of decision support system can be rapidly updated following on-going technological and field situation developments. |
Kamal, Muhammad; Farda, Nur Mohammad; Jamaluddin, Ilham; Parela, Artha; Wikantika, Ketut; Prasetyo, Lilik B; Irawan, Bambang A preliminary study on machine learning and google earth engine for mangrove mapping Conference vol. 500, IOP Conf. Ser.: Earth Environ. Sci, 2020. @conference{Kamal2020,
title = {A preliminary study on machine learning and google earth engine for mangrove mapping},
author = {Muhammad Kamal and Nur Mohammad Farda and Ilham Jamaluddin and Artha Parela and Ketut Wikantika and Lilik B Prasetyo and Bambang Irawan},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/500/1/012038/meta},
doi = {10.1088/1755-1315/500/1/012038},
year = {2020},
date = {2020-07-03},
volume = {500},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {The alarming rate of global mangrove forest degradation corroborates the need for providing fast, up-to-date and accurate mangrove maps. Conventional scene by scene image classification approach is inefficient and time consuming. The development of Google Earth Engine (GEE) provides a cloud platform to access and seamlessly process large amount of freely available satellite imagery. The GEE also provides a set of the state-of-the-art classifiers for pixel-based classification that can be used for mangrove mapping. This study is an initial effort which is aimed to combine machine learning and GEE for mapping mangrove extent. We used two Landsat 8 scenes over Agats and Timika Papua area as pilot images for this study; path 102 row 64 (2014/10/19) and path 103 row 63 (2013/05/16). The first image was used to develop local training areas for the machine learning classification, while the second one was used as a test image for GEE on the cloud. A total of 838 points samples were collected representing mangroves (244), non-mangroves (161), water bodies (311), and cloud (122) class. These training areas were used by support vector machine classifier in GEE to classify the first image. The classification result show mangrove objects could be efficiently delineated by this algorithm as confirmed by visual checking. This algorithm was then applied to the second image in GEE to check the consistency of the result. A simultaneous view of both classified images shows a corresponding pattern of mangrove forest, which mean the mangrove object has been consistently delineated by the algorithm.},
keywords = {GEE, machine learning, mangrove},
pubstate = {published},
tppubtype = {conference}
}
The alarming rate of global mangrove forest degradation corroborates the need for providing fast, up-to-date and accurate mangrove maps. Conventional scene by scene image classification approach is inefficient and time consuming. The development of Google Earth Engine (GEE) provides a cloud platform to access and seamlessly process large amount of freely available satellite imagery. The GEE also provides a set of the state-of-the-art classifiers for pixel-based classification that can be used for mangrove mapping. This study is an initial effort which is aimed to combine machine learning and GEE for mapping mangrove extent. We used two Landsat 8 scenes over Agats and Timika Papua area as pilot images for this study; path 102 row 64 (2014/10/19) and path 103 row 63 (2013/05/16). The first image was used to develop local training areas for the machine learning classification, while the second one was used as a test image for GEE on the cloud. A total of 838 points samples were collected representing mangroves (244), non-mangroves (161), water bodies (311), and cloud (122) class. These training areas were used by support vector machine classifier in GEE to classify the first image. The classification result show mangrove objects could be efficiently delineated by this algorithm as confirmed by visual checking. This algorithm was then applied to the second image in GEE to check the consistency of the result. A simultaneous view of both classified images shows a corresponding pattern of mangrove forest, which mean the mangrove object has been consistently delineated by the algorithm. |
Hultera,; Prasetyo, Lilik B; Setiawan, Yudi Spatial Model Of The Deforestation Potential 2020 & 2024 And The Prevention Approach, Kutai Barat District Journal Article In: Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan, vol. 10, no. 2, pp. 294-306, 2020, ISSN: 2086-4639. @article{Hultera2020,
title = {Spatial Model Of The Deforestation Potential 2020 & 2024 And The Prevention Approach, Kutai Barat District},
author = {Hultera and Lilik B Prasetyo and Yudi Setiawan},
url = {https://journal.ipb.ac.id/index.php/jpsl/article/view/29821},
doi = {10.29244/jpsl.10.2.294-306},
issn = {2086-4639},
year = {2020},
date = {2020-07-03},
journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan},
volume = {10},
number = {2},
pages = {294-306},
abstract = {Kutai Barat have high forest cover and high deforestation rates. The study purpose to make spatial model, potential distribution of deforestation 2020 and 2024, analysis of the drivers of deforestation, compile and map the approach to reducing deforestation. Deforestation modeling done using MaxEnt and Zonation software. Deforestation sample data used from land cover maps 2009, 2013 and 2016. Deforestation rates used to estimate potential deforestation 2020 and 2024. The drivers of deforestation analyze from land cover change matrix. Prevention strategy approach by overlaying potential deforestation modeling results with RTRW maps. The model has good performance with AUC value 0.873. The validation show very good accuracy for the prediction of area to be deforested by 94%, the accuracy of the spatial distribution of the model 31%. Environmental variables have the highest contribution to the model is the distance from previous deforestation 37.4%. The potential of deforestation 2020 is 85,908 ha and 171,778 ha 2024. Oil palm, agriculture, rubber, HTI and mining are the driver of deforestation. Social forestry is expected to prevent potential deforestation 120,861 ha. Others expected programs to contribute to the deforestation reduction are community land intensification 30,316 ha and implementation of the HCV in plantation 20,120 ha.},
keywords = {deforestation},
pubstate = {published},
tppubtype = {article}
}
Kutai Barat have high forest cover and high deforestation rates. The study purpose to make spatial model, potential distribution of deforestation 2020 and 2024, analysis of the drivers of deforestation, compile and map the approach to reducing deforestation. Deforestation modeling done using MaxEnt and Zonation software. Deforestation sample data used from land cover maps 2009, 2013 and 2016. Deforestation rates used to estimate potential deforestation 2020 and 2024. The drivers of deforestation analyze from land cover change matrix. Prevention strategy approach by overlaying potential deforestation modeling results with RTRW maps. The model has good performance with AUC value 0.873. The validation show very good accuracy for the prediction of area to be deforested by 94%, the accuracy of the spatial distribution of the model 31%. Environmental variables have the highest contribution to the model is the distance from previous deforestation 37.4%. The potential of deforestation 2020 is 85,908 ha and 171,778 ha 2024. Oil palm, agriculture, rubber, HTI and mining are the driver of deforestation. Social forestry is expected to prevent potential deforestation 120,861 ha. Others expected programs to contribute to the deforestation reduction are community land intensification 30,316 ha and implementation of the HCV in plantation 20,120 ha. |
Sudhana, Sonny A; Sakti, Anjar D; Syahid, Luri N; Prasetyo, Lilik B; Irawan, Bambang; Kamal, Muhammad; Wikantika, Ketut Detecting mangrove deforestation using multi land use land cover change datasets: a comparative analysis in Southeast Asia Conference vol. 500, IOP Conf. Ser.: Earth Environ. Sci, 2020. @conference{Sudhana2020,
title = {Detecting mangrove deforestation using multi land use land cover change datasets: a comparative analysis in Southeast Asia},
author = {Sonny A Sudhana and Anjar D Sakti and Luri N Syahid and Lilik B Prasetyo and Bambang Irawan and Muhammad Kamal and Ketut Wikantika},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/500/1/012014/meta},
doi = {10.1088/1755-1315/500/1/012014},
year = {2020},
date = {2020-06-01},
volume = {500},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {Mangrove forest grows on tropical coastal areas and has an ecological role for its surrounding environment. Mangrove forest protects the coast from large waves and becomes a habitat for various marine fauna. It stores the highest densities of carbon among any other ecosystem globally. In Southeast Asia, Mangrove forest is highly biodiverse and contributes to the sustainability of the ecosystem. However, based on previous studies, mangrove forests are experiencing deforestation due to high demands of commodities and land use. In this study, we analyzed changes of land cover in Southeast Asia using several global land cover products produced between 2001 and 2012 and their correlation with mangrove deforestation based on Mangrove Forest Watch (CGMFC-21) data. LULC data products applied in this study were ESA CCI LC, MODIS LC, GlobCover. The analysis was carried out by calculating the rate of increase in mangrove deforestation and comparing it with changes in land cover that replaced the mangrove area temporally. The results of this study were land cover classes that replaced mangrove forest areas in the study period. Based on the results it could be concluded that the methods and products used influence the results. There are many sources of data products that might be used for future research, with other methods that are better so that they provide space for future research and development. Our study can be used as a consideration to implement policies that conserve mangrove forest across Southeast Asia.},
keywords = {deforestation, land cover change, mangrove},
pubstate = {published},
tppubtype = {conference}
}
Mangrove forest grows on tropical coastal areas and has an ecological role for its surrounding environment. Mangrove forest protects the coast from large waves and becomes a habitat for various marine fauna. It stores the highest densities of carbon among any other ecosystem globally. In Southeast Asia, Mangrove forest is highly biodiverse and contributes to the sustainability of the ecosystem. However, based on previous studies, mangrove forests are experiencing deforestation due to high demands of commodities and land use. In this study, we analyzed changes of land cover in Southeast Asia using several global land cover products produced between 2001 and 2012 and their correlation with mangrove deforestation based on Mangrove Forest Watch (CGMFC-21) data. LULC data products applied in this study were ESA CCI LC, MODIS LC, GlobCover. The analysis was carried out by calculating the rate of increase in mangrove deforestation and comparing it with changes in land cover that replaced the mangrove area temporally. The results of this study were land cover classes that replaced mangrove forest areas in the study period. Based on the results it could be concluded that the methods and products used influence the results. There are many sources of data products that might be used for future research, with other methods that are better so that they provide space for future research and development. Our study can be used as a consideration to implement policies that conserve mangrove forest across Southeast Asia. |
Siswono, Agus; Syaufina, Lailan; Rushayati, Siti Badriyah Correlation Study of Environmental Knowledge, Attitudes, Subjective Norms and Perceptions of Behavior Control on Students' Environmental Care Behavior Journal Article In: Science Education Journal, vol. 4, no. 1, pp. 669, 2020, ISSN: 2540-9859. @article{Siswono2020,
title = {Correlation Study of Environmental Knowledge, Attitudes, Subjective Norms and Perceptions of Behavior Control on Students' Environmental Care Behavior},
author = {Agus Siswono and Lailan Syaufina and Siti Badriyah Rushayati},
url = {https://journal.umsida.ac.id/index.php/sej/article/view/669},
doi = {10.21070/sej.v4i1.669},
issn = {2540-9859},
year = {2020},
date = {2020-05-03},
journal = {Science Education Journal},
volume = {4},
number = {1},
pages = {669},
abstract = {This study aims to examine the correlation of environmental knowledge, attitudes, subjective norms, and perceptions of behavioral control on the environmental behavior of students of SMK-SMAK Bogor, to examine differences in environmental knowledge and environmental behavior of male students and female students of SMK-SMAK Bogor. The sample in this study was 54 students. Correlation analysis was performed using Partial Least Square (PLS). The t-test analysis was used to examine differences in knowledge and the environmental behavior of male and female students. Based on the analysis, it is known that knowledge has a positive and significant effect on attitudes; attitudes have a significant effect on environmental behavior. Meanwhile, subjective norms and perceived behavioral control have no significant effect on the environmental behavior of students at SMK-SMAK Bogor. The results of the t-test analysis also showed that the knowledge and environmental behavior between male students and female students were not significantly different.},
keywords = {environmental knowledge},
pubstate = {published},
tppubtype = {article}
}
This study aims to examine the correlation of environmental knowledge, attitudes, subjective norms, and perceptions of behavioral control on the environmental behavior of students of SMK-SMAK Bogor, to examine differences in environmental knowledge and environmental behavior of male students and female students of SMK-SMAK Bogor. The sample in this study was 54 students. Correlation analysis was performed using Partial Least Square (PLS). The t-test analysis was used to examine differences in knowledge and the environmental behavior of male and female students. Based on the analysis, it is known that knowledge has a positive and significant effect on attitudes; attitudes have a significant effect on environmental behavior. Meanwhile, subjective norms and perceived behavioral control have no significant effect on the environmental behavior of students at SMK-SMAK Bogor. The results of the t-test analysis also showed that the knowledge and environmental behavior between male students and female students were not significantly different. |
Syahidah, Tazkiyatul; Rizali, Akhmad; Prasetyo, Lilik B; Buchori, Damayanti Landscape composition alters parasitoid wasps but not their host diversity in tropical agricultural landscapes Journal Article In: Biodiversitas, vol. 21, no. 4, pp. 1702-1706, 2020. @article{Syahidah2020,
title = {Landscape composition alters parasitoid wasps but not their host diversity in tropical agricultural landscapes},
author = {Tazkiyatul Syahidah and Akhmad Rizali and Lilik B Prasetyo and Damayanti Buchori},
url = {https://smujo.id/biodiv/article/view/4718},
doi = {10.13057/biodiv/d210452},
year = {2020},
date = {2020-03-29},
journal = {Biodiversitas},
volume = {21},
number = {4},
pages = {1702-1706},
abstract = {The diversity of parasitoid wasps and their hosts in an agricultural landscape is affected by crop management and habitat conditions around crop fields. The composition of agricultural landscapes that are dominated by non-crop or natural habitats are assumed to be able to support the presence of parasitoid wasps as biological control of pests. The aim of this study was to investigate the effect of landscape composition on the diversity of parasitoid wasps and their hosts in agricultural landscapes. The research observations were conducted on six fields of long-bean cultivation located in Bogor District, West Java Province, Indonesia. Parasitoid wasps were collected by hand-collecting of their hosts (lepidopteran larvae) within 60 m distance transect to each long-bean field. In total, 17 species of parasitoid wasps and 12 species of lepidopteran larvae were found from all agricultural landscapes. A parasitoid wasp, Microplitis manilae was found in all long-bean fields (except Bantarjaya) and only parasitized the tobacco cutworm (Spodoptera litura). The tomato looper, Chrysodeixis chalcites had the highest associated parasitoids and was also parasitized by Braconidae sp5 which was also a parasitoid of S. litura. Based on the analysis results, the patch numbers of natural habitats had a positive effect on the diversity of parasitoid wasps and had no effect on the diversity of lepidopteran larvae. In conclusion, landscape compositions with patchy natural habitats have an important role to preserve beneficial insects and maintain ecosystem services in tropical agricultural landscapes.},
keywords = {parasitoid},
pubstate = {published},
tppubtype = {article}
}
The diversity of parasitoid wasps and their hosts in an agricultural landscape is affected by crop management and habitat conditions around crop fields. The composition of agricultural landscapes that are dominated by non-crop or natural habitats are assumed to be able to support the presence of parasitoid wasps as biological control of pests. The aim of this study was to investigate the effect of landscape composition on the diversity of parasitoid wasps and their hosts in agricultural landscapes. The research observations were conducted on six fields of long-bean cultivation located in Bogor District, West Java Province, Indonesia. Parasitoid wasps were collected by hand-collecting of their hosts (lepidopteran larvae) within 60 m distance transect to each long-bean field. In total, 17 species of parasitoid wasps and 12 species of lepidopteran larvae were found from all agricultural landscapes. A parasitoid wasp, Microplitis manilae was found in all long-bean fields (except Bantarjaya) and only parasitized the tobacco cutworm (Spodoptera litura). The tomato looper, Chrysodeixis chalcites had the highest associated parasitoids and was also parasitized by Braconidae sp5 which was also a parasitoid of S. litura. Based on the analysis results, the patch numbers of natural habitats had a positive effect on the diversity of parasitoid wasps and had no effect on the diversity of lepidopteran larvae. In conclusion, landscape compositions with patchy natural habitats have an important role to preserve beneficial insects and maintain ecosystem services in tropical agricultural landscapes. |
Putri, Anika; Kusrini, Mirza Dikari; Prasetyo, Lilik B Pemodelan Kesesuaian Habitat Katak Serasah (Leptobrachium hasseltii Tschudi 1838) dengan Sistem Informasi Geografis di Pulau Jawa Journal Article In: Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan, vol. 10, no. 1, pp. 12-24, 2020, ISBN: 2086-4639. @article{Putri2020,
title = {Pemodelan Kesesuaian Habitat Katak Serasah (Leptobrachium hasseltii Tschudi 1838) dengan Sistem Informasi Geografis di Pulau Jawa},
author = {Anika Putri and Mirza Dikari Kusrini and Lilik B Prasetyo},
url = {http://journal.ipb.ac.id/index.php/jpsl/article/view/21135},
doi = {10.29244/jpsl.10.1.12-24},
isbn = {2086-4639},
year = {2020},
date = {2020-03-20},
journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan},
volume = {10},
number = {1},
pages = {12-24},
abstract = {Hasselt’s litter frogs (Leptobrachium hasseltii Tschudi 1838) is a wide spread species in Java and Sumatra, but there is no specific distribution map for this species. The purpose of this study is to identify the distribution of hasselt’s litter frogs in Java and examine the suitability of it’s using maxent. We used presence data and environment variables consisting of elevation, slope, NDVI (Normalized Difference Vegetation Index), distance from the river, temperature, precipitation, and land cover to evelop the distribution model of this species. Hasselt’s litter frogs in Java depends on forested area with a wide range of elevation (lowland to mountain forests), moderate slope, temperature between 20-21 o C and rainfall over 2500 mm/year. The highest number of frogs are found in secondary forest land cover, as supported by NDVI values between 0.8 to 0.9 and relatively close to the river. Habitat model constructed are robust with AUC (Area Under Curve) value of 0.951. Environmental variables that most affectted habitat for hasselt’s litter frog are land cover, temperature, and slope.},
keywords = {katak, Leptobrachium hasseltii Tschudi 1838},
pubstate = {published},
tppubtype = {article}
}
Hasselt’s litter frogs (Leptobrachium hasseltii Tschudi 1838) is a wide spread species in Java and Sumatra, but there is no specific distribution map for this species. The purpose of this study is to identify the distribution of hasselt’s litter frogs in Java and examine the suitability of it’s using maxent. We used presence data and environment variables consisting of elevation, slope, NDVI (Normalized Difference Vegetation Index), distance from the river, temperature, precipitation, and land cover to evelop the distribution model of this species. Hasselt’s litter frogs in Java depends on forested area with a wide range of elevation (lowland to mountain forests), moderate slope, temperature between 20-21 o C and rainfall over 2500 mm/year. The highest number of frogs are found in secondary forest land cover, as supported by NDVI values between 0.8 to 0.9 and relatively close to the river. Habitat model constructed are robust with AUC (Area Under Curve) value of 0.951. Environmental variables that most affectted habitat for hasselt’s litter frog are land cover, temperature, and slope. |
Yunandar,; Effendi, Hefni; Widiatmaka,; Setiawan, Yudi Plankton biodiversity in various typologies of inundation in Paminggir peatland, South Kalimantan, Indonesia on dry season Journal Article In: Biodiversitas, vol. 21, no. 3, pp. 1012-1019, 2020, ISSN: 2085-4722. @article{Yunandar2020,
title = {Plankton biodiversity in various typologies of inundation in Paminggir peatland, South Kalimantan, Indonesia on dry season},
author = {Yunandar and Hefni Effendi and Widiatmaka and Yudi Setiawan},
url = {hdx.doi.org/10.13057/biodiv/d210322},
doi = {10.13057/biodiv/d210322},
issn = {2085-4722},
year = {2020},
date = {2020-03-01},
journal = {Biodiversitas},
volume = {21},
number = {3},
pages = {1012-1019},
abstract = {The aim of the study was to analyze the typology of inundation areas and plankton biodiversity in Paminggir peatland, South Borneo, Indonesia. Typology of inundation was determined by image processing and spatial analysis using supervised classification method from Landsat 1994, 2014, 2019. Plankton biodiversity was determined using purposive sampling in detected inundation from spatial analysis. Some environmental factors like temperature, Ph and DO were also analyzed. Confirmation of the results of spatial analysis of peatland typology made from overall accuracy and Kappa informed 88.48% and 0.8. The typology of permanent inundation decreased by 30% from 1994 to 2019 during the dry period from June to August of the total study area of 43275,584 hectares due to sedimentation, land conversion for settlement, and increase in water weeds. Inundation criteria with duration throughout the year were was categorized as permanent, whereas temporary inundation was tentative even in certain dry season. Plankton index biodiversity in permanent inundation was more varied compared to temporary inundation. Phytoplankton from the freshwater Chrysophyta group was more dominant, while zooplankton from the Nauplius group, which were the natural food for fish larvae always presented in the typology of permanent inundation.},
keywords = {inundation, peatland, plankton, spatial, typology},
pubstate = {published},
tppubtype = {article}
}
The aim of the study was to analyze the typology of inundation areas and plankton biodiversity in Paminggir peatland, South Borneo, Indonesia. Typology of inundation was determined by image processing and spatial analysis using supervised classification method from Landsat 1994, 2014, 2019. Plankton biodiversity was determined using purposive sampling in detected inundation from spatial analysis. Some environmental factors like temperature, Ph and DO were also analyzed. Confirmation of the results of spatial analysis of peatland typology made from overall accuracy and Kappa informed 88.48% and 0.8. The typology of permanent inundation decreased by 30% from 1994 to 2019 during the dry period from June to August of the total study area of 43275,584 hectares due to sedimentation, land conversion for settlement, and increase in water weeds. Inundation criteria with duration throughout the year were was categorized as permanent, whereas temporary inundation was tentative even in certain dry season. Plankton index biodiversity in permanent inundation was more varied compared to temporary inundation. Phytoplankton from the freshwater Chrysophyta group was more dominant, while zooplankton from the Nauplius group, which were the natural food for fish larvae always presented in the typology of permanent inundation. |
2019
|
A, Suheri; Kusmana, Cecep; Purwanto, M Y J; Setiawan, Yudi The peak runoff model based on Existing Land Use and Masterplan in Sentul City area, Bogor Conference vol. 399, no. 1, IOP Conf. Ser.: Earth Environ. Sci, 2019. @conference{A2019b,
title = {The peak runoff model based on Existing Land Use and Masterplan in Sentul City area, Bogor},
author = {Suheri A and Cecep Kusmana and M Y J Purwanto and Yudi Setiawan},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/399/1/012039},
doi = {10.1088/1755-1315/399/1/012039},
year = {2019},
date = {2019-12-31},
volume = {399},
number = {1},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {This research aimed to create a peak runoff mode based on existing land use (LU) and masterplan in Sentul City area. To determine the peak runoff by rational method, the study uses the formulation as follows: Q = 0.2778.C.I.A, in which Q is the peak runoff, C is the runoff coefficient of area, I is the average rain rate intensity, and A is the area of study. For recognizing the existing LU, the researcher used image analysis SPOT-6 (2017) by supervised classification. It estimated the gamma distribution parameter through the maximum likelihood method by using software QGIS 2.8, SAGA GIS, dan Arc-GIS 10.4.1. According to the analysis, the study result showed the existing LU peak runoff coefficient value and masterplan are 0.40 and 0.61, respectively, in which the difference is 0.21. The peak runoff increase is 25.32 m3/sec or 6,622,560 m3/year as the impact of land-use change.},
keywords = {runoff},
pubstate = {published},
tppubtype = {conference}
}
This research aimed to create a peak runoff mode based on existing land use (LU) and masterplan in Sentul City area. To determine the peak runoff by rational method, the study uses the formulation as follows: Q = 0.2778.C.I.A, in which Q is the peak runoff, C is the runoff coefficient of area, I is the average rain rate intensity, and A is the area of study. For recognizing the existing LU, the researcher used image analysis SPOT-6 (2017) by supervised classification. It estimated the gamma distribution parameter through the maximum likelihood method by using software QGIS 2.8, SAGA GIS, dan Arc-GIS 10.4.1. According to the analysis, the study result showed the existing LU peak runoff coefficient value and masterplan are 0.40 and 0.61, respectively, in which the difference is 0.21. The peak runoff increase is 25.32 m3/sec or 6,622,560 m3/year as the impact of land-use change. |
D, Nugraha; Alikodra, Hadi S; Kusmana, Cecep; Setiawan, Yudi Ecotourism land suitability based on the different weighting method in the buffer zone of Mount Ceremai National Park, Kuningan Regency, West Java Province Conference vol. 399, no. 1, IOP Conf. Ser.: Earth Environ. Sci, 2019. @conference{D2019,
title = {Ecotourism land suitability based on the different weighting method in the buffer zone of Mount Ceremai National Park, Kuningan Regency, West Java Province},
author = {Nugraha D and Hadi S Alikodra and Cecep Kusmana and Yudi Setiawan},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/399/1/012044},
doi = {10.1088/1755-1315/399/1/012044},
year = {2019},
date = {2019-12-31},
volume = {399},
number = {1},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {Location suitability selection for ecotourism development is determined by various variables. Differences in the characteristics and complexity of the region cause each variable to have a different influence. In the process of multi-criteria decision analysis, the influence of each variable can be identified through several weighting methods, such as ranking, rating, and pairwise comparisons. This paper aims to show the result of land suitability examining for ecotourism development using the different weighting methods and selecting the best method according to the complexity of the case. This research was conducted by using ten ecotourism suitability variables in the buffer zone of Mount Ceremai National Park in Kuningan District, West Java Province. Based on the results of the analysis, the differences of the ecotourism suitability map that had produced by the Ranking and Rating methods were not significantly different. However, the pairwise method produced different suitability maps than that of rating and ranking. Pairwise tends to classify a larger area as a suitable class. Therefore, the selection of weighting methods can be adjusted to the need and availability of existing resources.},
keywords = {AHP, ecotourism, land suitability},
pubstate = {published},
tppubtype = {conference}
}
Location suitability selection for ecotourism development is determined by various variables. Differences in the characteristics and complexity of the region cause each variable to have a different influence. In the process of multi-criteria decision analysis, the influence of each variable can be identified through several weighting methods, such as ranking, rating, and pairwise comparisons. This paper aims to show the result of land suitability examining for ecotourism development using the different weighting methods and selecting the best method according to the complexity of the case. This research was conducted by using ten ecotourism suitability variables in the buffer zone of Mount Ceremai National Park in Kuningan District, West Java Province. Based on the results of the analysis, the differences of the ecotourism suitability map that had produced by the Ranking and Rating methods were not significantly different. However, the pairwise method produced different suitability maps than that of rating and ranking. Pairwise tends to classify a larger area as a suitable class. Therefore, the selection of weighting methods can be adjusted to the need and availability of existing resources. |
Condro, Aryo Adhi; Prasetyo, Lilik B; Rushayati, Siti Badriyah Short-term projection of Bornean orangutan spatial distribution based on climate and land cover change scenario Conference vol. 11372, SPIE, 2019. @conference{Condro2019,
title = {Short-term projection of Bornean orangutan spatial distribution based on climate and land cover change scenario},
author = {Aryo Adhi Condro and Lilik B Prasetyo and Siti Badriyah Rushayati},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/113721B/Short-term-projection-of-Bornean-orangutan-spatial-distribution-based-on/10.1117/12.2541633.short},
doi = {10.1117/12.2541633},
year = {2019},
date = {2019-12-28},
volume = {11372},
publisher = {SPIE},
abstract = {Primates, the closest living biological relatives with human, play the important roles in the livelihoods, human-health, and ecosystem services. In the Anthropocene, populations of 75% of primate species are decreasing globally – due to cultivation activities, logging harvesting, hunting, and climate change. In this study, we focus on Bornean orangutan (Pongo pygmaeus) as the global conservation icons. Hence, understanding Bornean orangutan’s distribution dynamics is crucial regarding to conservation and climate mitigation strategies. The objectives of this study are: (1) to predict current and future spatial distribution of orangutan in Borneo using pessimistic climate model and land cover projection as well; (2) to identify spatial dynamics of Bornean orangutan distribution due to climate and land cover change in 2030. Species distribution modelling of baseline and future scenario was performed using logistic regression model. Land cover categories and climate parameters (i.e. annual temperature and precipitation) were used for model predictors. Presence points of observed primate species were retrieved from Ministry of Environment and Forestry Indonesia (MoEF). We used WorldClim v2.0 annual temperature and precipitation data for the baseline and CMIP5 MIROC-ESM model RCP8.5 2030 for the future climate scenario. We performed cellular automata algorithm to retrieve 2030 projected land-use for the future. Distance to road and distance to selected important land covers were used for transition potential modelling of land cover projection. Generally, the prediction shows that suitable habitat of Bornean orangutan will decrease in 2030. However, we found the gain of suitable area of Bornean orangutan. Findings of this study should support the identification of priority conservation area of Bornean orangutan for the future and wildlife corridor management planning.},
keywords = {orangutan},
pubstate = {published},
tppubtype = {conference}
}
Primates, the closest living biological relatives with human, play the important roles in the livelihoods, human-health, and ecosystem services. In the Anthropocene, populations of 75% of primate species are decreasing globally – due to cultivation activities, logging harvesting, hunting, and climate change. In this study, we focus on Bornean orangutan (Pongo pygmaeus) as the global conservation icons. Hence, understanding Bornean orangutan’s distribution dynamics is crucial regarding to conservation and climate mitigation strategies. The objectives of this study are: (1) to predict current and future spatial distribution of orangutan in Borneo using pessimistic climate model and land cover projection as well; (2) to identify spatial dynamics of Bornean orangutan distribution due to climate and land cover change in 2030. Species distribution modelling of baseline and future scenario was performed using logistic regression model. Land cover categories and climate parameters (i.e. annual temperature and precipitation) were used for model predictors. Presence points of observed primate species were retrieved from Ministry of Environment and Forestry Indonesia (MoEF). We used WorldClim v2.0 annual temperature and precipitation data for the baseline and CMIP5 MIROC-ESM model RCP8.5 2030 for the future climate scenario. We performed cellular automata algorithm to retrieve 2030 projected land-use for the future. Distance to road and distance to selected important land covers were used for transition potential modelling of land cover projection. Generally, the prediction shows that suitable habitat of Bornean orangutan will decrease in 2030. However, we found the gain of suitable area of Bornean orangutan. Findings of this study should support the identification of priority conservation area of Bornean orangutan for the future and wildlife corridor management planning. |
Wijayanie, Akira; Setiawan, Yudi; Hikmat, Agus; Pairah,; Septiana, Wardi; Erlan, Mochamad; Hilmy, Yoesri Characterization of vegetation structure in Gunung Halimun Salak National Park corridor with drone technology and Geographic Information System (GIS) Conference vol. 11372, SPIE, 2019. @conference{Wijayanie2019,
title = {Characterization of vegetation structure in Gunung Halimun Salak National Park corridor with drone technology and Geographic Information System (GIS)},
author = {Akira Wijayanie and Yudi Setiawan and Agus Hikmat and Pairah and Wardi Septiana and Mochamad Erlan and Yoesri Hilmy},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2539337/Characterization-of-vegetation-structure-in-Gunung-Halimun-Salak-National-Park/10.1117/12.2539337.short},
doi = {10.1117/12.2539337},
year = {2019},
date = {2019-12-28},
volume = {11372},
publisher = {SPIE},
abstract = {Gunung Halimun Salak National Park (GHSNP) corridor is an area that connects Salak and Halimun Mountain, and has a role in animal movement, breeding and living. This study aims to characterize the vegetation structure in a restoration area in the corridor of Gunung Halimun Salak National Park. The vegetation characteristics was analyzed through structural vegetation datasets such as Canopy Height Model (CHM) and some vegetation indices namely; Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), Soil Adjusted Vegetation Index (SAVI), and Normalized Difference Water Index (NDWI). Significance of the approach was evaluated by the Mann Whitney test. The results indicated that the restoration area of HSNPC consist of seedlings, saplings, poles and trees. GHSNP’s corridor canopy layer consists of five canopy layers, namely strata A (> 30 m), B (20 – 30 m), C (4 – 20 m), D (1 – 4 m), and E (0 – 1 m). The most important species are Schima wallichii, Agathis dammara, Bellucia axinanthera and Macaranga triloba. The effective vegetation index to see the differences vegetation structure are NDVI and RVI vegetation index.},
keywords = {characterization, drone, vegetation structure},
pubstate = {published},
tppubtype = {conference}
}
Gunung Halimun Salak National Park (GHSNP) corridor is an area that connects Salak and Halimun Mountain, and has a role in animal movement, breeding and living. This study aims to characterize the vegetation structure in a restoration area in the corridor of Gunung Halimun Salak National Park. The vegetation characteristics was analyzed through structural vegetation datasets such as Canopy Height Model (CHM) and some vegetation indices namely; Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), Soil Adjusted Vegetation Index (SAVI), and Normalized Difference Water Index (NDWI). Significance of the approach was evaluated by the Mann Whitney test. The results indicated that the restoration area of HSNPC consist of seedlings, saplings, poles and trees. GHSNP’s corridor canopy layer consists of five canopy layers, namely strata A (> 30 m), B (20 – 30 m), C (4 – 20 m), D (1 – 4 m), and E (0 – 1 m). The most important species are Schima wallichii, Agathis dammara, Bellucia axinanthera and Macaranga triloba. The effective vegetation index to see the differences vegetation structure are NDVI and RVI vegetation index. |
Setiawan, Yudi; Murdaningsih,; Taufik, Muh; Sumantri, Hendi; Widiastuti, Marliana Tri Spatial modeling of oil palm development in Sumatra and Kalimantan: An integrative spatial approach using CLUE-S model Journal Article In: vol. 11372, 2019. @article{Setiawan2019,
title = {Spatial modeling of oil palm development in Sumatra and Kalimantan: An integrative spatial approach using CLUE-S model},
author = {Yudi Setiawan and Murdaningsih and Muh Taufik and Hendi Sumantri and Marliana Tri Widiastuti},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2538820/Spatial-modeling-of-oil-palm-development-in-Sumatra-and-Kalimantan/10.1117/12.2538820.short},
doi = {10.1117/12.2538820},
year = {2019},
date = {2019-12-28},
volume = {11372},
abstract = {Palm oil industry delivers a large part of Indonesia’s economy due to the fact that is the major exporter in the list of producers worldwide. However, environmental protection and sustainability of the oil palm plantation is a global issue since its development was identified as a driving factor of deforestation as well as forest degradation in Indonesia. Therefore, the projection of oil palm development is required in order to support the national program of low-carbon development planning. The objective of this study is to develop projections of oil palm expansion for 2045 that comprise of a business-as-usual scenario due to considering the complex interactions between historic and present land use, socioeconomic conditions and biophysical constraints. An integrative spatial approach of the CLUE (Conversion of Land Use and its Effects) model was applied to explore land use changes for a scenario of further oil palm development in both Sumatra and Kalimantan, Indonesia. According to the BAU scenario, the total estimated area planted with oil palm plantation in 2045, both Sumatra and Kalimantan, had reached 13.8 Mha and 10.6 Mha, respectively. If we compare with the estimation result of the BAU with legal compliance, no-expansion allowed in forest area, oil palm plantation in both islands are: 11.2 Mha in Sumatra and 7.3 Mha in Kalimantan. Meanwhile, based on the zero-deforestation scenario, the expansion of oil palm is still possible in both islands, Sumatra and Kalimantan, for about 1,632,019 ha and 869,844 ha, respectively. The different trend of their changes per year for each island shown the different characteristics of each island triggered by biophysical environments, the historical development of land, as well as social-economic conditions.},
keywords = {CLUE-S model, oil palm},
pubstate = {published},
tppubtype = {article}
}
Palm oil industry delivers a large part of Indonesia’s economy due to the fact that is the major exporter in the list of producers worldwide. However, environmental protection and sustainability of the oil palm plantation is a global issue since its development was identified as a driving factor of deforestation as well as forest degradation in Indonesia. Therefore, the projection of oil palm development is required in order to support the national program of low-carbon development planning. The objective of this study is to develop projections of oil palm expansion for 2045 that comprise of a business-as-usual scenario due to considering the complex interactions between historic and present land use, socioeconomic conditions and biophysical constraints. An integrative spatial approach of the CLUE (Conversion of Land Use and its Effects) model was applied to explore land use changes for a scenario of further oil palm development in both Sumatra and Kalimantan, Indonesia. According to the BAU scenario, the total estimated area planted with oil palm plantation in 2045, both Sumatra and Kalimantan, had reached 13.8 Mha and 10.6 Mha, respectively. If we compare with the estimation result of the BAU with legal compliance, no-expansion allowed in forest area, oil palm plantation in both islands are: 11.2 Mha in Sumatra and 7.3 Mha in Kalimantan. Meanwhile, based on the zero-deforestation scenario, the expansion of oil palm is still possible in both islands, Sumatra and Kalimantan, for about 1,632,019 ha and 869,844 ha, respectively. The different trend of their changes per year for each island shown the different characteristics of each island triggered by biophysical environments, the historical development of land, as well as social-economic conditions. |
Jailani,; Liyantono,; Setiawan, Yudi; Muradi, Hengky; Musliman, Sri Algorithm of pattern recognition for real-time rice crops monitoring using Sentinel images Conference vol. 11372, SPIE, 2019. @conference{Jailani2019,
title = {Algorithm of pattern recognition for real-time rice crops monitoring using Sentinel images},
author = {Jailani and Liyantono and Yudi Setiawan and Hengky Muradi and Sri Musliman},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2541801/Algorithm-of-pattern-recognition-for-real-time-rice-crops-monitoring/10.1117/12.2541801.short?SSO=1},
doi = {10.1117/12.2541801},
year = {2019},
date = {2019-12-28},
volume = {11372},
publisher = {SPIE},
abstract = {Rice crops is a crucial commodity for Indonesian people. Most Indonesian people consume rice as a staple food. With the rate of population growth that continues to increase, the demand for rice also increases. Rice crops Monitoring needed in ensuring national food availability. This paper presents a new method for predicting the growth phase of rice crops with a rice field area approach and identifying patterns of vegetation index from Sentinel 2A satellite image data series from May to September 2017. The study was conducted in Sukamekar Village, Karawang District, West Java, Indonesia from June to August 2017. Polynomial regression models used to identify the relationship between the growth phase of rice crops and vegetation index. The vegetation index used is NDVI. In determining the vegetation index in the rice field two methods are obtained, first calculating the average value of the vegetation index on the pixels in each rice fields area. Second, by removing the pixels that contact with the border of each rice field area, then calculate the average value of the vegetation index on the pixel of the rice field area. From both of methods, an algorithm was developed to get the rule base to determine the phase of rice growth based on the value of the vegetation index in each field area. The model developed was implemented in the same location in January 2019 using Sentinel-2A Image. Based on field validation in February 2019, the accuracy of the first method was 70% while the second method was 75%.},
keywords = {crop monitoring, pattern recognition, Sentinel},
pubstate = {published},
tppubtype = {conference}
}
Rice crops is a crucial commodity for Indonesian people. Most Indonesian people consume rice as a staple food. With the rate of population growth that continues to increase, the demand for rice also increases. Rice crops Monitoring needed in ensuring national food availability. This paper presents a new method for predicting the growth phase of rice crops with a rice field area approach and identifying patterns of vegetation index from Sentinel 2A satellite image data series from May to September 2017. The study was conducted in Sukamekar Village, Karawang District, West Java, Indonesia from June to August 2017. Polynomial regression models used to identify the relationship between the growth phase of rice crops and vegetation index. The vegetation index used is NDVI. In determining the vegetation index in the rice field two methods are obtained, first calculating the average value of the vegetation index on the pixels in each rice fields area. Second, by removing the pixels that contact with the border of each rice field area, then calculate the average value of the vegetation index on the pixel of the rice field area. From both of methods, an algorithm was developed to get the rule base to determine the phase of rice growth based on the value of the vegetation index in each field area. The model developed was implemented in the same location in January 2019 using Sentinel-2A Image. Based on field validation in February 2019, the accuracy of the first method was 70% while the second method was 75%. |
Rudianto, Yoga; Prasetyo, Lilik B; Setiawan, Yudi; Hudjimartsu, Sahid A Canopy cover estimation of agroforestry based on airborne LiDAR and Landsat 8 OLI Conference vol. 11372, SPIE, 2019. @conference{Rudianto2019,
title = {Canopy cover estimation of agroforestry based on airborne LiDAR and Landsat 8 OLI},
author = {Yoga Rudianto and Lilik B Prasetyo and Yudi Setiawan and Sahid A Hudjimartsu},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2541549/Canopy-cover-estimation-of-agroforestry-based-on-airborne-LiDAR-and/10.1117/12.2541549.short},
doi = {10.1117/12.2541549},
year = {2019},
date = {2019-12-28},
volume = {11372},
publisher = {SPIE},
abstract = {Agroforestry/mixed gardens is a land management system that combines agricultural, livestock production with tree to obtain various products in a sustainable manner so as to increase social, economic and environmental benefits This system can be a form of mitigation and adaptation to global climate change, especially in areas with high population densities, but with less agricultural labor, such as in urban fringe area. Based on the formal definition of forests from the Indonesian Ministry of Environment and Forestry of Indonesia based on canopy cover, agroforestry might be considered as forest, whereas the canopy cover >30%. The research aim to estimate canopy cover base on integration of Lidar and Landsat 8 OLI of agroforestry in the Cidanau watershed. The most suitable equation model is an exponential equation (FRCI = 22.928e (-80.439 * 'RED')), however, some underestimation in high canopy cover ( >70%) and underestimation in low canopy cover (< 60%) should be anticipated. The result showed that agroforestry in some location have canopy cover greater than 30% and therefore it can be considered as a forest.},
keywords = {agroforestry, canopy cover, Landsat, LiDAR},
pubstate = {published},
tppubtype = {conference}
}
Agroforestry/mixed gardens is a land management system that combines agricultural, livestock production with tree to obtain various products in a sustainable manner so as to increase social, economic and environmental benefits This system can be a form of mitigation and adaptation to global climate change, especially in areas with high population densities, but with less agricultural labor, such as in urban fringe area. Based on the formal definition of forests from the Indonesian Ministry of Environment and Forestry of Indonesia based on canopy cover, agroforestry might be considered as forest, whereas the canopy cover >30%. The research aim to estimate canopy cover base on integration of Lidar and Landsat 8 OLI of agroforestry in the Cidanau watershed. The most suitable equation model is an exponential equation (FRCI = 22.928e (-80.439 * 'RED')), however, some underestimation in high canopy cover ( >70%) and underestimation in low canopy cover (< 60%) should be anticipated. The result showed that agroforestry in some location have canopy cover greater than 30% and therefore it can be considered as a forest. |
Munawir, Abdillah; June, Tania; Kusmana, Cecep; Setiawan, Yudi Dynamics factors that affect the land use change in the Lore Lindu National Park, Indonesia Conference vol. 11372, SPIE, 2019. @conference{Munawir2019,
title = {Dynamics factors that affect the land use change in the Lore Lindu National Park, Indonesia},
author = {Abdillah Munawir and Tania June and Cecep Kusmana and Yudi Setiawan},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2542812/Dynamics-factors-that-affect-the-land-use-change-in-the/10.1117/12.2542812.short},
doi = {10.1117/12.2542812},
year = {2019},
date = {2019-12-28},
volume = {11372},
publisher = {SPIE},
abstract = {Changes in land use and land cover play a critical role, especially in the Lore Lindu National Park (TNLL) area, impacting on ecosystem functions. This study was aimed at analyzing the dynamics of land change and the factors influencing the land change in this National Park. The methods used were the GIS technique and a binary logistic regression model. The land changes locating between Sigi Regency and Donggala Regency, Central Sulawesi Province, Indonesia, which consisted of thirteen sub-districts in the TNLL region acquiring from Landsat satellite data acquisition of 1997, 2002, 2013, and 2018. The dynamics of land changes during the period of 1997-2002 has decreased the forest area by 2,643 ha, and the next period, 2002-2013, the decline of forest area has reached 4,265 ha, and the overall the dynamics of land change experiences a significant increase from 1997 to 2018 which declines the forest areas approximately 10,175 ha and followed by a decline of the meadow area in 1,726 ha changing function into the built-up land of 526 ha, mixed gardens of 1,189 ha, fields/moorings of 3,019 ha, rice fields of 1,548 ha and shrubs of 5,619 ha. The factors influencing the land change in this TNLL region based on the results of binary logistic regression analysis are the population density (X5), distance from the settlement (X3), distance from the road (X2), distance from the capital (X4), and topographic conditions (X1). Of these five variables, the population density has the highest negative regression coefficient, which is equal to -0.068. The regression equation is Y = -0.094X1-0.157X2-0.176X3-0.083X4- 0.068X5 and being significant in a level of 0.001 percent that indicates these five factors have influenced greatly high the land change in the TNLL. This situation can be inferred that the free distribution and population growth in the National Park influence increasing the conversion of forest areas.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.},
keywords = {land use change},
pubstate = {published},
tppubtype = {conference}
}
Changes in land use and land cover play a critical role, especially in the Lore Lindu National Park (TNLL) area, impacting on ecosystem functions. This study was aimed at analyzing the dynamics of land change and the factors influencing the land change in this National Park. The methods used were the GIS technique and a binary logistic regression model. The land changes locating between Sigi Regency and Donggala Regency, Central Sulawesi Province, Indonesia, which consisted of thirteen sub-districts in the TNLL region acquiring from Landsat satellite data acquisition of 1997, 2002, 2013, and 2018. The dynamics of land changes during the period of 1997-2002 has decreased the forest area by 2,643 ha, and the next period, 2002-2013, the decline of forest area has reached 4,265 ha, and the overall the dynamics of land change experiences a significant increase from 1997 to 2018 which declines the forest areas approximately 10,175 ha and followed by a decline of the meadow area in 1,726 ha changing function into the built-up land of 526 ha, mixed gardens of 1,189 ha, fields/moorings of 3,019 ha, rice fields of 1,548 ha and shrubs of 5,619 ha. The factors influencing the land change in this TNLL region based on the results of binary logistic regression analysis are the population density (X5), distance from the settlement (X3), distance from the road (X2), distance from the capital (X4), and topographic conditions (X1). Of these five variables, the population density has the highest negative regression coefficient, which is equal to -0.068. The regression equation is Y = -0.094X1-0.157X2-0.176X3-0.083X4- 0.068X5 and being significant in a level of 0.001 percent that indicates these five factors have influenced greatly high the land change in the TNLL. This situation can be inferred that the free distribution and population growth in the National Park influence increasing the conversion of forest areas.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only. |
Nuraeni, Siti; Rushayati, Siti Badriyah; Setiawan, Yudi Estimation of biomass and carbon deposits in the Mount Tampomas Sumedang protected forest area in West Java Conference vol. 11372, SPIE, 2019. @conference{Nuraeni2019,
title = {Estimation of biomass and carbon deposits in the Mount Tampomas Sumedang protected forest area in West Java},
author = {Siti Nuraeni and Siti Badriyah Rushayati and Yudi Setiawan},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2539098/Estimation-of-biomass-and-carbon-deposits-in-the-Mount-Tampomas/10.1117/12.2539098.short},
doi = {10.1117/12.2539098},
year = {2019},
date = {2019-12-28},
volume = {11372},
publisher = {SPIE},
abstract = {Increased carbon dioxide in the atmosphere causes the surface temperature of the earth to warm up and has a major impact on climate change globally. Plants in the forest as the biggest absorber of carbon dioxide used in the process of photosynthesis, then the results are stored in the form of biomass in plant organ tissues. The purpose of the study was to estimate biomass and carbon storage in the Mount Tampomas Protected Forest Area in Sumedang, West Java. Mount Tampomas protected forest area is divided into areas dominated by pine plant species (Pinus merkusii) and mixed jungles. In the two regions the NDVI class was classified into 5 classes as the basis for calculating the stand density, biomass and carbon storage. The relationship between NDVI classes and stand densities can be demonstrated by linear and quadratic regression models. The quadratic regression model has r of 0.79 while the linear regression model of 0.78. Quadratic regression model is the best model to connect the NDVI class and stand density, where the NDVI class and stand density are very strongly related. The total biomass and carbon deposits sequentially in protected forest areas dominated by pine are 132,613.79 tons and 62,328.48 tons C, while the total biomass and carbon deposits sequentially in mixed forest protected areas are 64,682.95 tons and 30,400.99 tons C, so that the total biomass and carbon storage sequentially in the Mount Tampomas Protected Forest Area are 197,296.74 tons and 92,729.47 tons C.},
keywords = {biomass, carbon deposit},
pubstate = {published},
tppubtype = {conference}
}
Increased carbon dioxide in the atmosphere causes the surface temperature of the earth to warm up and has a major impact on climate change globally. Plants in the forest as the biggest absorber of carbon dioxide used in the process of photosynthesis, then the results are stored in the form of biomass in plant organ tissues. The purpose of the study was to estimate biomass and carbon storage in the Mount Tampomas Protected Forest Area in Sumedang, West Java. Mount Tampomas protected forest area is divided into areas dominated by pine plant species (Pinus merkusii) and mixed jungles. In the two regions the NDVI class was classified into 5 classes as the basis for calculating the stand density, biomass and carbon storage. The relationship between NDVI classes and stand densities can be demonstrated by linear and quadratic regression models. The quadratic regression model has r of 0.79 while the linear regression model of 0.78. Quadratic regression model is the best model to connect the NDVI class and stand density, where the NDVI class and stand density are very strongly related. The total biomass and carbon deposits sequentially in protected forest areas dominated by pine are 132,613.79 tons and 62,328.48 tons C, while the total biomass and carbon deposits sequentially in mixed forest protected areas are 64,682.95 tons and 30,400.99 tons C, so that the total biomass and carbon storage sequentially in the Mount Tampomas Protected Forest Area are 197,296.74 tons and 92,729.47 tons C. |
Putri, Hafidzah; Hermawan, Rachmad; Setiawan, Yudi Tree carbon stock estimation model based on canopy density in green open space area Depok City Conference vol. 11372, SPIE, 2019. @conference{Putri2019,
title = {Tree carbon stock estimation model based on canopy density in green open space area Depok City},
author = {Hafidzah Putri and Rachmad Hermawan and Yudi Setiawan},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2540430/Tree-carbon-stock-estimation-model-based-on-canopy-density-in/10.1117/12.2540430.short},
doi = {10.1117/12.2540430},
year = {2019},
date = {2019-12-28},
volume = {11372},
publisher = {SPIE},
abstract = {Depok is a city with rapid undergoing economic and infrastructure development in Indonesia. Such increasing growth in infrastructure affected positively to increase the population, and then, it threat an existence of remaining green open areas. Vegetation on green open areas has a role as the carbon storage in forms of trees. This research aim is to find the correlation between tree carbon stock and Leaf Area Index (LAI) in green open space. The method were used vegetation analysis and field measurement to collect diameter data for estimate carbon stock and hemispherical photography to measure the LAI. The result shown that the highest tree carbon stock were located in University of Indonesia City Forest (87.02 ton C/ha) with the highest vegetation index was Falcataria moluccana. The amount of tree carbon stock in Pancoran Mas Forest Park was 13.96 ton C/ha and in Lembah Gurame Park was 6.25 ton C/ha. LAI estimated in University of Indonesia City Forest was between 3.30 – 6.55, Pancoran Mas Forest Park 2.96 – 3.77 and Lembah Gurame Park 1.46 – 2.92. The correlation between the two variables were weak, rxy=0.32 and has polynomial equation C = -2.0874LAI2 + 10.188LAI - 9.5021 with R2= 0.477.},
keywords = {canopy density, carbon stock},
pubstate = {published},
tppubtype = {conference}
}
Depok is a city with rapid undergoing economic and infrastructure development in Indonesia. Such increasing growth in infrastructure affected positively to increase the population, and then, it threat an existence of remaining green open areas. Vegetation on green open areas has a role as the carbon storage in forms of trees. This research aim is to find the correlation between tree carbon stock and Leaf Area Index (LAI) in green open space. The method were used vegetation analysis and field measurement to collect diameter data for estimate carbon stock and hemispherical photography to measure the LAI. The result shown that the highest tree carbon stock were located in University of Indonesia City Forest (87.02 ton C/ha) with the highest vegetation index was Falcataria moluccana. The amount of tree carbon stock in Pancoran Mas Forest Park was 13.96 ton C/ha and in Lembah Gurame Park was 6.25 ton C/ha. LAI estimated in University of Indonesia City Forest was between 3.30 – 6.55, Pancoran Mas Forest Park 2.96 – 3.77 and Lembah Gurame Park 1.46 – 2.92. The correlation between the two variables were weak, rxy=0.32 and has polynomial equation C = -2.0874LAI2 + 10.188LAI - 9.5021 with R2= 0.477. |
Hossea, Hannura; Pravitasari, Andrea Emma; Setiawan, Yudi; Rustiadi, Ernan Landscape metric in the analysis of urban form in Cekungan Bandung urban region Journal Article In: vol. 11372, 2019. @article{Hossea2019,
title = {Landscape metric in the analysis of urban form in Cekungan Bandung urban region},
author = {Hannura Hossea and Andrea Emma Pravitasari and Yudi Setiawan and Ernan Rustiadi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/2541668/Landscape-metric-in-the-analysis-of-urban-form-in-Cekungan/10.1117/12.2541668.short},
doi = {10.1117/12.2541668},
year = {2019},
date = {2019-12-28},
volume = {11372},
abstract = {Cekungan Bandung Urban Region is a national strategic area from the point of economic interest. Rapid economic growth in the region has led to increased population growth and Built-up land use. Increased use of built up land in urban areas can cause urban sprawl which can have serious impacts that will damage the structure and function of urban area ecosystems, thus hampering the development of regional sustainability. Landscape Metrics can be used to analyze the urban form of the Cekungan Bandung Area in time series from 1983-2015 so that it can identify the changing trends. The results of the analysis show that during this period urban growth in the Cekungan Bandung Area showed a positive trend with a compact, connected, un-fragmented and near-square urban form. Being a concern of Patch Density (PD) and CONTIG values because it shows an increasing number of patches so that patches are more fragmented and the distance between the built up patches shows the trend is increasingly scattered on the edges of the Cekungan Bandung Area which can cause urban sprawl.},
keywords = {landscape metric, urban},
pubstate = {published},
tppubtype = {article}
}
Cekungan Bandung Urban Region is a national strategic area from the point of economic interest. Rapid economic growth in the region has led to increased population growth and Built-up land use. Increased use of built up land in urban areas can cause urban sprawl which can have serious impacts that will damage the structure and function of urban area ecosystems, thus hampering the development of regional sustainability. Landscape Metrics can be used to analyze the urban form of the Cekungan Bandung Area in time series from 1983-2015 so that it can identify the changing trends. The results of the analysis show that during this period urban growth in the Cekungan Bandung Area showed a positive trend with a compact, connected, un-fragmented and near-square urban form. Being a concern of Patch Density (PD) and CONTIG values because it shows an increasing number of patches so that patches are more fragmented and the distance between the built up patches shows the trend is increasingly scattered on the edges of the Cekungan Bandung Area which can cause urban sprawl. |
Siahaan, Lasriama; Hilwan, Iwan; Setiawan, Yudi Spatial Distribution of Andaliman Potential Habitat (Zanthoxylum acanthopodium DC.) in Samosir Island, North Sumatera Journal Article In: Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan, vol. 9, no. 4, pp. 861-871, 2019, ISSN: 2086-4639. @article{Siahaan2019,
title = {Spatial Distribution of Andaliman Potential Habitat (Zanthoxylum acanthopodium DC.) in Samosir Island, North Sumatera},
author = {Lasriama Siahaan and Iwan Hilwan and Yudi Setiawan},
url = {https://journal.ipb.ac.id/index.php/jpsl/article/view/22970},
doi = {10.29244/jpsl.9.4.861-871},
issn = {2086-4639},
year = {2019},
date = {2019-11-02},
journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan},
volume = {9},
number = {4},
pages = {861-871},
abstract = {Andaliman breeding and regeneration (Zanthoxylum acanthopodium DC.) in its natural habitat tends to be slow and difficult. The purpose of this research was to determine the distribution pattern, spatial character, and potential suitable habitat for andaliman growth with a suitability model approach in Samosir island, North Sumatera. Andaliman distribution pattern based on the calculation of the Standard Morisita Index (Ip) shows various patterns. There are three categories of distribution pattern, depends on the Standard Morisita Index The distribution patterns on each plot based on the calculation are: random (Location 1 – open area (Ip = 0.00)), uniform (Location 2 – plantation forest (Ip = -0.77); Location 3 – open field (Ip = -0.09)), and clump (Location 4 – plantation forest (Ip = 0.36)). Analysis of habitat suitability for andaliman used spatial modelling with the Principal Component Analysis (PCA) approach. This method utilized ecological variables, i.e.: Bare Soil Index (BSI), slope, Digital Elevation Model (DEM), rainfall, Normalized Difference Moisture Index (NDMI), and Normalized Difference Vegetation Index (NDVI). The result is 69.8% of Samosir Island is suitable for andaliman, while 26.4% of it is considered as highly suitable habitat.},
keywords = {distribution patterns, samosir island, suitability spatial modeling, Zanthoxylum acanthopodium},
pubstate = {published},
tppubtype = {article}
}
Andaliman breeding and regeneration (Zanthoxylum acanthopodium DC.) in its natural habitat tends to be slow and difficult. The purpose of this research was to determine the distribution pattern, spatial character, and potential suitable habitat for andaliman growth with a suitability model approach in Samosir island, North Sumatera. Andaliman distribution pattern based on the calculation of the Standard Morisita Index (Ip) shows various patterns. There are three categories of distribution pattern, depends on the Standard Morisita Index The distribution patterns on each plot based on the calculation are: random (Location 1 – open area (Ip = 0.00)), uniform (Location 2 – plantation forest (Ip = -0.77); Location 3 – open field (Ip = -0.09)), and clump (Location 4 – plantation forest (Ip = 0.36)). Analysis of habitat suitability for andaliman used spatial modelling with the Principal Component Analysis (PCA) approach. This method utilized ecological variables, i.e.: Bare Soil Index (BSI), slope, Digital Elevation Model (DEM), rainfall, Normalized Difference Moisture Index (NDMI), and Normalized Difference Vegetation Index (NDVI). The result is 69.8% of Samosir Island is suitable for andaliman, while 26.4% of it is considered as highly suitable habitat. |
Prasetyo, Lilik B; Nursal, Wim I; Setiawan, Yudi; Rudianto, Yoga; Wikantika, Ketut; Irawan, Bambang Canopy cover of mangrove estimation based on airborne LIDAR & Landsat 8 OLI Conference vol. 335, IOP Conf. Ser.: Earth Environ. Sci, 2019. @conference{Prasetyo2019,
title = {Canopy cover of mangrove estimation based on airborne LIDAR & Landsat 8 OLI},
author = {Lilik B Prasetyo and Wim I Nursal and Yudi Setiawan and Yoga Rudianto and Ketut Wikantika and Bambang Irawan},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/335/1/012029},
doi = {10.1088/1755-1315/335/1/012029},
year = {2019},
date = {2019-10-28},
volume = {335},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {Mangroves are very important ecosystems, because of their economic value and environmental services, including as a habitat for various wildlife species, storing carbon, and protecting land from sea abrasion. Indonesia is known to have large mangrove area and diversity. It is estimated that the area of mangroves in Indonesia in 2015 reached about 3 million hectares, with 15 families, 18 genera, 41 true mangrove species and 116 species of mangrove associations. Unfortunately, the area to continue to decline due to degradation and conversion to other land uses, especially ponds and built up areas. Usually, mangrove degradation assessment is carried out by field survey and relying on Normalized Difference Vegetation Index (NDVI) clustering derived from satellite image data. Field surveys require a large amount of time and cost, meanwhile NDVI clustering is either inaccurate or too rough. Therefore, exploration of another methods are needed. Our result showed that pixel value of Band 5, Band 6, NDVI and PC1 can be used to estimate canopy cover. Regression using quadratic equation is better than linear equations. However, we noticed limitations of optical Landsat 8 OLI data for canopy cover mapping, namely pixel saturation on high canopy cover and high pixel value of bush/shrubs/regrowth that was not always representing high canopy cover.},
keywords = {canopy cover, Landsat, LiDAR, mangrove},
pubstate = {published},
tppubtype = {conference}
}
Mangroves are very important ecosystems, because of their economic value and environmental services, including as a habitat for various wildlife species, storing carbon, and protecting land from sea abrasion. Indonesia is known to have large mangrove area and diversity. It is estimated that the area of mangroves in Indonesia in 2015 reached about 3 million hectares, with 15 families, 18 genera, 41 true mangrove species and 116 species of mangrove associations. Unfortunately, the area to continue to decline due to degradation and conversion to other land uses, especially ponds and built up areas. Usually, mangrove degradation assessment is carried out by field survey and relying on Normalized Difference Vegetation Index (NDVI) clustering derived from satellite image data. Field surveys require a large amount of time and cost, meanwhile NDVI clustering is either inaccurate or too rough. Therefore, exploration of another methods are needed. Our result showed that pixel value of Band 5, Band 6, NDVI and PC1 can be used to estimate canopy cover. Regression using quadratic equation is better than linear equations. However, we noticed limitations of optical Landsat 8 OLI data for canopy cover mapping, namely pixel saturation on high canopy cover and high pixel value of bush/shrubs/regrowth that was not always representing high canopy cover. |
Rachdian, Azar; Hariyadi,; Setiawan, Yudi; Santoso, Kresno Dwi Carbon stock change dynamics of oil palm plantation in Sembilang Dangku Landscape, South Sumatra Conference vol. 336, IOP Conf. Ser.: Earth Environ. Sci, 2019. @conference{Rachdian2019,
title = {Carbon stock change dynamics of oil palm plantation in Sembilang Dangku Landscape, South Sumatra},
author = {Azar Rachdian and Hariyadi and Yudi Setiawan and Kresno Dwi Santoso},
url = {https://iopscience.iop.org/article/10.1088/1755-1315/336/1/012016},
doi = {10.1088/1755-1315/336/1/012016},
year = {2019},
date = {2019-10-15},
volume = {336},
publisher = {IOP Conf. Ser.: Earth Environ. Sci},
abstract = {One of the land cover type in the Sembilang Dangku Landscape is oil palm plantation, which is developed by changing the type of previous land covers. Land cover change causes changes in carbon stock. If the carbon stock increase in an area, it means the area acts as a carbon sinker, whereas if the carbon stock decrease, inconsequently the area is a carbon emitter. The purpose of this study was to analyze the dynamics of carbon stock changes in 1997-2007 and 2007-2017. The research was carried out on six private oil palm plantations. Carbon stocks were estimated based on the type of land cover interpreted from Landsat 5 imagery with the unsupervised method by using Las Palmas QGIS 2.18.0 Software. Determination of land cover in 1997 was based on the year when oil palm plantation began. Carbon stock of oil palm plantation was estimated based on the Normalized Difference Vegetation Index (NDVI) with the equation: Y = 638.13 X - 242.65 (Y = carbon stock, X = NDVI). The value of carbon sequestration or carbon emission were based on carbon stock changes. The types of land cover in 1997 and 2007 were in the form of shrub swamp, oil palm plantation, undisturbed peat swamp forest, disturbed peat swamp forest; while in 2017 land cover was dominated by oil palm plantation. The results showed respectively that carbon stocks in 1997, 2007 and 2017 were 3,333,549.6 tonC, 1,541,825.5 tonC, and 1,626, 951.8 tonC. In 1997-2007, carbon stock encountered a decrease, resulting in carbon emission of 18.68 tonCO2-eq/ha/year. However, in 2007-2017, carbon stock encountered an increase, leading in carbon sequestration of 0.89 tonCO2-eq/ha/year.},
keywords = {carbon stock, oil palm},
pubstate = {published},
tppubtype = {conference}
}
One of the land cover type in the Sembilang Dangku Landscape is oil palm plantation, which is developed by changing the type of previous land covers. Land cover change causes changes in carbon stock. If the carbon stock increase in an area, it means the area acts as a carbon sinker, whereas if the carbon stock decrease, inconsequently the area is a carbon emitter. The purpose of this study was to analyze the dynamics of carbon stock changes in 1997-2007 and 2007-2017. The research was carried out on six private oil palm plantations. Carbon stocks were estimated based on the type of land cover interpreted from Landsat 5 imagery with the unsupervised method by using Las Palmas QGIS 2.18.0 Software. Determination of land cover in 1997 was based on the year when oil palm plantation began. Carbon stock of oil palm plantation was estimated based on the Normalized Difference Vegetation Index (NDVI) with the equation: Y = 638.13 X - 242.65 (Y = carbon stock, X = NDVI). The value of carbon sequestration or carbon emission were based on carbon stock changes. The types of land cover in 1997 and 2007 were in the form of shrub swamp, oil palm plantation, undisturbed peat swamp forest, disturbed peat swamp forest; while in 2017 land cover was dominated by oil palm plantation. The results showed respectively that carbon stocks in 1997, 2007 and 2017 were 3,333,549.6 tonC, 1,541,825.5 tonC, and 1,626, 951.8 tonC. In 1997-2007, carbon stock encountered a decrease, resulting in carbon emission of 18.68 tonCO2-eq/ha/year. However, in 2007-2017, carbon stock encountered an increase, leading in carbon sequestration of 0.89 tonCO2-eq/ha/year. |
