scholarly journals Measuring Orangutan nest structure using Unmanned Aerial Vehicle (UAV) and ImageJ

2018 ◽  
Author(s):  
Salniza Akmar Kamaruszaman ◽  
Nik Fadzly ◽  
Aini Hasanah Abd Mutalib ◽  
Aidy M. Muslim ◽  
Sri Suci Utami Atmoko ◽  
...  

AbstractThe nest is one of the crucial elements in orangutan daily activities. Previously, most of the nest structure studies were done manually by estimating measurement directly from visual observation. However, using the latest unmanned aerial vehicle (UAV) technology, we can reduce the workforce, time and energy while simultaneously ensuring the safety of the researcher conducting nest structure analysis. We recorded 49 pictures of orangutan nests at Sepilok Orangutan Rehabilitation Centre (SORC) using UAV (DJI Phantom 3 Quadcopter). The nest structure (length, depth, and width) was digitally measured by using ImageJ. Most of the nests were built at a strong, stable, and comfortable position at the top of the tree. Most orangutans chose Eusideroxylon zwageri to build nest compared to other tree species because of the strong and durable wood characteristic which would create a sturdy, strong and comfortable nest. We propose the use of drone with digital image analysis could provide a more accurate, less time consuming and safe method for studying orangutan nest structure.

2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  

2018 ◽  
pp. 7-13
Author(s):  
Anton M. Mishchenko ◽  
Sergei S. Rachkovsky ◽  
Vladimir A. Smolin ◽  
Igor V . Yakimenko

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.


Author(s):  
Amir Birjandi ◽  
◽  
Valentin Guerry ◽  
Eric Bibeau ◽  
Hamidreza Bolandhemmat ◽  
...  

2019 ◽  
Vol E102.B (10) ◽  
pp. 2014-2020
Author(s):  
Yancheng CHEN ◽  
Ning LI ◽  
Xijian ZHONG ◽  
Yan GUO

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