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Multi-sensor data utilization of unmanned aerial vehicle for wildlife monitoring in Komodo National Park

Hendriatna Adis, Prasetyo Lilik Budi, Kusrini Mirza Dikari, Setiawan Yudi

Ecological Engineering & Environmental Technology

2025

Vol. 26, iss. 3

315--329

The use of unmanned aerial vehicles (UAVs) equipped with multispectral and thermal sensors provides a promising approach to wildlife monitoring, especially in the dynamic environment of Komodo National Park. This study explores the effectiveness of UAVs in tracking Komodo dragons and other wildlife using thermal imaging, which distinguishes animals based on body temperature contrasts with the surrounding environment. Thermal sensors detect wildlife more effectively in the afternoon, as animals like the Komodo dragon exhibit higher body temperatures compared to the cooler surroundings. Challenges, however, arise in the morning when animals body temperatures are closer to the environment, making them harder to detect. Factors such as fog, animal movement, and sensor limitations also impact detection accuracy. The study highlights the advantages of combining UAV thermal imaging with multispectral data to enhance monitoring accuracy. Despite the challenges, this method proves to be an efficient tool for wildlife management and conservation in remote, vast areas like Komodo National Park.

Monitoring Vegetation Changes and Disturbances in Gunung Merbabu National Park Using Landtrendr Algorithm and Landsat Images

Ardiaristo Astekita, Prasetyo Lilik Budi, Syaufina Lailan, Kosmaryandi Nandi

Ecological Engineering & Environmental Technology

2024

Vol. 25, iss. 7

298--307

Conservation areas protect biodiversity and ecosystems from human activities and climate change threats. Understanding disturbances that can damage conservation areas drives the need for effective mapping and monitoring. One of the primary disturbances is land cover change caused by forest fires, illegal logging, and other human activities. In this context, remote sensing algorithms such as LandTrendr offer an efficient approach to monitoring vegetation changes and disturbances in conservation areas. This study aims to monitor vegetation changes and disturbances in Gunung Merbabu National Park using the LandTrendr algorithm. Landsat image data from 1994 to 2023 was analyzed using Google Earth Engine. The results showed that the LandTrendr algorithm effectively identified vegetation changes, with forest fires being the primary disturbance. During 1994–2022, total vegetation loss and gain were detected at 933.57 ha and 2279.52 ha, respectively. The results highlight significant changes in the core zone of Gunung Merbabu National Park, mainly due to fires and logging activities. These findings provide a better understanding of the dynamics of vegetation change in Gunung Merbabu National Park and provide relevant insights for conservation area managers to implement appropriate mitigation measures. This research contributes to the literature on monitoring vegetation changes in conservation areas and provides a basis for more effective conservation efforts in Gunung Merbabu National Park and similar areas.