Real time monitoring fire detection Using Remote Sensing

Each year, vegetation fires, in composite with deforestation operations, convert and modify huge sections of evergreen tropical forests, transitional forests, and savanna vegetation across the tropics. MODIS is the most basic fire product, identifying current flames as well as other thermal anomalies such as volcanoes. The MODIS product has daily composite fire products. The daily composite fire products that we use is MOD14a. MOD14a is a daily level 3 fire product spans one of the 460 MODIS tile, 326 of which contain land pixels. We used a comprehensive analysis in this study to validate the MODIS satellite active fire detection products (MOD14) and compute the data in time series. The data were taken during January 2021 – August 2021 utilizing in Google Earth Engine. This method is user-friendly methods for data processing, aggregation, downloading, and ingestion data processing parallel processing for fast downloads. The parallel processing is useful to fulfill the gap of the data of the hotspot region which are not cover by the other satellite imagery. From results show the distribution of hotspot locations in Riau, identifying the most vulnerable regions to fire as Pelalawan and Bukit Kapur, as well as the smoke and hazes that are prone to fires and validated with monitoring system Sipongi application.