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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) BIOTROPIA - The Southeast Asian Journal of Tropical Biology
Simon, Okta
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Engineering Immunology & microbiology Veterinary

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Object detection of the bornean orangutan nests using drone and YOLOv5 Teguh, Rony; Dwijaya Maleh, I Made; Sagit Sahay, Abertun; Porkab Pratama, Muhamad; Simon, Okta
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1640-1649

Abstract

Object detection methods when applied to ecology and conservation can help to identify and monitor endangered species and their habitats. Using drones for this purpose has become increasingly popular due to their ability to cover large areas quickly and efficiently. In this study, we aim to implement object detection using YOLOv5 to detect orangutan nests in forests. To conduct our experiment, we collect drone imagery under different conditions. We propose to use the original YOLOv5 to implement our model. The detection and monitoring of orangutan nests can help conservationists to identify critical habitats, monitor population, and design effective conservation strategies. Additionally, the use of drones can reduce the need for on-the-ground surveys, which can be time-consuming, expensive, and logistically challenging. In our study proposes a model for detecting orangutan nests in forests using a drone and the YOLOv5. Our model predicted 1,970 training images and 414 labeled orangutan nests, with a precision of 0.973, recall 0.949, accuracy mean average precision (mAP)_0.5 is 0.969, and mAP_0.5:0.95 is 0.630. The model finished 217 epochs in 58 hours and had a high object detection accuracy. The model has a 99.9% accuracy in detecting the number of orangutan nests.
ORANGUTAN (Pongo pygmaeus ssp. wurmbii) RANGING PATTERN IN PUNGGUALAS, SEBANGAU NATIONAL PARK, CENTRAL KALIMANTAN INDONESIA: Ranging pattern of P.p. wurmbii in Punggualas, Sebangau National Park Panda, Adventus; Meididit, Ari; Simon, Okta; Artama, Wayan Tunas; Priyowidodo, Dwi; Djohan, Tjut Sugandawaty
BIOTROPIA Vol. 30 No. 3 (2023): BIOTROPIA Vol. 30 No. 3 December 2023
Publisher : SEAMEO BIOTROP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11598/btb.2023.30.3.1901

Abstract

Punggualas lies in the western part of Sebangau National Park (SNP). It is a logged-over forest, yet it is one of the major strongholds for the P. p. wurmbii population in the SNP. The range size, as well as the ranging pattern for Punggualas, has never been conducted. The study aimed to estimate orangutan ranging size and pattern as well as their distribution over the Punggualas forest. Ranging data within the area of interest (AOI) was collected from Feb 2015 – Dec 2019 (P1), and Mar 2020 – May 2022 (P2). Minimum convex polygon (MCP), range size of orangutan individual was calculated using adehabitatHR package in RStudio 4.1.1 for Windows. We visualized the distribution in ArcGIS 10.5 with Kernel Density (KD) tool.   The range size of Mother-Infant is the greatest (259,6 Ha) among all individuals being studied within the study periods. Moreover, the size estimation was found greater in Mother-Infant sex class compared to other orangutan studies areas, such as Peat Natural Laboratory, and CIMTROP-UPR which reported a flanged male HR Size reaching 250 Ha per annum. We have found that the ranging pattern significantly changes over the study period. However, during P1, the distribution area was located within the northern of AOI, while in the P2 have changed to the south-eastern part of the AOI.  We concluded that the ranging pattern indeed follows the fruit availability as well as fine-scale habitat quality.
Co-Authors Adventus Panda Dwi Priyowidodo Dwijaya Maleh, I Made Meididit, Ari Porkab Pratama, Muhamad Rony Teguh Sagit Sahay, Abertun Tjut Sugandawaty Djohan Wayan Tunas Artama