https://journal.ipb.ac.id/index.php/agromet/issue/feed Agromet 2024-10-03T16:43:38+07:00 Muh Taufik mtaufik@apps.ipb.ac.id Open Journal Systems <p><strong>Agromet</strong> is published twice a year by the Indonesian Association of Agricultural Meteorology (PERHIMPI) in collaboration with Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, IPB University. Agromet publishes original research articles or reviews that have not been published elsewhere. The scope of publication related to weather and climate issues (agriculture, forestry, water resources, environment, ecology, and health as affected by weather and climate variability and change).&nbsp;</p> https://journal.ipb.ac.id/index.php/agromet/article/view/57588 Identification of Peatland Burned Area based on Multiple Spectral Indices and Adaptive Thresholding in Central Kalimantan 2024-10-03T16:43:38+07:00 Hilda Ayu Pratikasiwi hildaayu.siwi@gmail.com Muh. Taufik mtaufik@ipb.ac.id I Putu Santikayasa ipsantika@apps.ipb.ac.id Dede Dirgahayu Domiri dededirgahayu11@gmail.com <p>Nowadays, spectral index has become popular as a tool to identify fire-burned areas. However, the use of a single index may not be universally applicable to region with diverse landscape and vegetation as peatlands. Here, we propose to develop a procedure that integrates multiple spectral indices with an adaptive thresholding method to enhance the performance of burned area detection. We combined the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR) using MODIS imagery from 2002 to 2022 to calculate &nbsp;(Confirmed Burned Pixel) by filtering dNDVI and dNBR. The mean and standard deviation of &nbsp;serve as inputs for image thresholding. We tested our approach in Sebangau peatland, Central Kalimantan, where fires occur annually. The results showed that the model performed well with overall accuracy &gt; of 91%, indicating that the model is effective and reliable for identifying burned areas. The findings also revealed that the frequency of fire is below 2 times/year, with the southeastern is the most fire prone regions. Further, our findings provide an alternative approach for identifying burned areas in locations with diverse vegetation cover and different geographical regions.&nbsp;&nbsp;</p> 2024-10-03T16:41:32+07:00 Copyright (c) 2024 Hilda Ayu Pratikasiwi, Muh. Taufik, I Putu Santikayasa, Dede Dirgahayu Domiri