Dr. Yudi Setiawan, S.P, M.Sc

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@article{Arai2019,

title = {Method for Uncertainty Evaluation of Vicarious Calibration of Spaceborne Visible to Near Infrared Radiometers},

author = {Kohei Arai and Wahyudi Hasbi and A Hadi Syafrudin and Patria Rachman Hakim and Sartika Salaswati and Lilik B Prasetyo and Yudi Setiawan},

url = {https://thesai.org/Publications/ViewPaper?Volume=10&Issue=1&Code=ijacsa&SerialNo=51},

doi = {10.14569/IJACSA.2019.0100151},

year  = {2019},

date = {2019-01-01},

journal = {International Journal of Advanced Computer Science and Applications},

volume = {10},

number = {1},

pages = {387-393},

abstract = {A method for uncertainty evaluation of vicarious calibration for solar reflection channels (visible to near infrared) of spaceborne radiometers is proposed. Reflectance based at sensor radiance estimation method for solar reflection channels of radiometers onboard remote sensing satellites is also proposed. One of examples for vicarious calibration of LISA: Line Imager Space Application onboard LISAT: LAPAN-IPB Satellite is described. Through the preliminary analysis, it is found that the proposed uncertainty evaluation method is appropriate. Also, it is found that percent difference between DN: Digital Number derived radiance and estimated TOA: Top of the Atmosphere radiance (at sensor radiance) ranges from 3.5 to 9.6 %. It is also found that the percent difference at shorter wavelength (Blue) is greater than that of longer wavelength (Near Infrared: NIR). In comparison to those facts to those of Terra/ASTER/VNIR, it is natural and reasonable.},

keywords = {Field experiment, image quality evaluation, vicarious calibration},

pubstate = {published},

tppubtype = {article}

}

@article{setiawan2018identifying,

title = {Identifying Areas Affected By Fires In Sumatra Based On Time Series Of Remotely Sensed Fire Hotspots And Spatial Modeling},

author = {Yudi Setiawan and Lilik B Prasetyo and Hidayat Pawitan and Prita A Permatasari and Desi Suyamto and Arif K Wijayanto},

url = {http://journal.ipb.ac.id/index.php/jpsl/article/view/24760},

doi = {10.29244/jpsl.8.3.420-427},

issn = {2460-5824},

year  = {2018},

date = {2018-01-01},

journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)},

volume = {8},

number = {3},

pages = {420--427},

abstract = {Wildfires threaten the environment not only at local scales, but also at wider scales. Rapid monitoring system to detect active wildfires has been provided by satellite remote sensing technology, particularly through the advancement on thermal infrared sensors. However, satellite-based fire hotspots data, even at relatively high temporal resolution of less than one-day revisit period, such as time series of fire hotspots collected from TERRA and AQUA MODIS, do not tell exactly if they are fire ignitions or fire escapes, since other factors like wind, slope, and fuel biomass significantly drive the fire spread. Meanwhile, a number of biophysical fire simulation models have been developed, as tools to understand the roles of biophysical factors on the spread of wildfires. Those models explicitly incorporate effects of slope, wind direction, wind speed, and vegetative fuel on the spreading rate of surface fire from the ignition points across a fuel bed, based on either field or laboratory experiments. Nevertheless, none of those models have been implemented using real time fire data at relatively large extent areas. This study is aimed at incorporating spatially explicit time series data of weather (i.e. wind direction and wind speed), remotely sensed fuel biomass and remotely sensed fire hotspots, as well as incorporating more persistent biophysical factors (i.e. terrain), into an agent-based fire spread model, in order to identify fire ignitions within time series of remotely sensed fire hotspots.},

keywords = {fire, hotspot},

pubstate = {published},

tppubtype = {article}

}

@article{setiawan2018pemanfaatan,

title = {Pemanfaatan Fusi Data Satelit Lapan-a3/IPB dan Landsat 8 Untuk Monitoring Lahan Sawah},

author = {Yudi Setiawan and Lilik B Prasetyo and Hidayat Pawitan and Liyantono Liyantono and Syartinilia Syartinilia and Arif K Wijayanto and Prita A Permatasari and Hadi A Syafrudin and Patria R Hakim},

url = {https://journal.ipb.ac.id/index.php/jpsl/article/view/19754},

doi = {10.29244/jpsl.8.1.67-76},

issn = {2460-5824},

year  = {2018},

date = {2018-01-01},

journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)},

volume = {8},

number = {1},

pages = {67--76},

abstract = {Increasing of economic development is generally followed by the change of landuse from agriculture to other function. If it occurs in large frequency and amount, it will threaten national food security. Therefore, it is necessary to monitor the agricultural land, especially paddy fields regarding to changes in landuse and global climate. Utilization and development of satellite technology is necessary to provide more accurate and independent database for agricultural land monitoring, especially paddy fields. This study aims to develop a utilization model for LAPAN-IPB satellite (LISAT) and other several satellites data that have been used for paddy field monitoring. This research is conducted through 2 stages: 1) Characterization LISAT satellite data to know spectral variation of paddy field, and 2) Development method of LISAT data fusion with other satellites for paddy field mapping. Based on the research results, the characteristics Red and NIR band in LISAT data imagery have a good correlation with Red and NIR band in LANDSAT 8 OLI data imagery, especially to detect paddy field in the vegetative phase, compared to other bands. Observation and measurement of spectral values using spectroradiometer need to be conducted periodically (starting from first planting season) to know the dynamics of the change related to the growth phase of paddy in paddy field. Pre-processing of image data needs to be conducted to obtain better LISAT data characterization results. Furthermore, it is necessary to develop appropriate algorithms or methods for geometric correction as well as atmospheric correction of LISAT data.},

keywords = {Landsat, LAPAN},

pubstate = {published},

tppubtype = {article}

}