https://journal.ipb.ac.id/index.php/agromet/issue/feed 2024-12-16T15:48:33+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 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 https://journal.ipb.ac.id/index.php/agromet/article/view/59389 2024-12-16T15:48:33+07:00 Risyda Hanifa risydahanifa22@gmail.com Joko Wiratmo joko.wiratmo@meteo.itb.ac.id

<p>Indonesia, as a maritime continent, is vulnerable to environmental disasters such as floods and landslides due to extreme rainfall. This study aims to identify changes in the influence of ENSO and IOD on extreme rainfall across Indonesia, specifically during the September-October-November period. We used rainfall and sea surface temperature data from the CMIP6 climate model for the historical period (1985-2014), near-future (2031-2060), and far-future (2061-2090) projections under SSP2-4.5 and SSP 5-8.5 climate scenarios. The relation between rainfall dan ENSO/IOD was simply defined by linear regression approach. We analyzed the change of influence by comparing the historical and the future condition. The results indicated that the changes in the teleconnection of ENSO and IOD to extreme rainfall in future is consistently negative, except for Java (near-future) and Kalimantan and southern Sumatra (far-future). Our finding revealed that significant changes in the teleconnection varied throughout maritime continent. The maximum change was found in Northern Kalimantan, which reached values of -80 mm/°C due to ENSO and -180 mm/°C due to IOD for near future. These findings highlight the spatial variability in teleconnection changes across Indonesia, underscoring the need for region-specific climate adaptation measures in response to evolving extreme rainfall patterns.</p>

2024-12-16T15:48:33+07:00 Copyright (c) 2024 Risyda Hanifa, Joko Wiratmo