2020
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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. |
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. |
2019
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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. |
