Abstract
One of the efforts to control the forest and land fire disasters which affect on the biomass burning haze is fire hotspots monitoring. Biomass burning haze in Southeast Asia (SEA) has become a recurring annual issue. This study aims to determine the spatial and temporal distribution of fire hotspots along SEA, so that it can serve as guidance for efforts to control them. The hotspot data used is derived from NASA’s Fire Information for Resource Management System (FIRMS) MODIS sensors which is collected from 2001-2020. Spatial analysis of the re-gridded data shows the highest burning activities over SEA occurred in Feb-Apr, with >2000 fire events in the Indo-China area and >1000 fire events in Sumatra and Borneo. Empirical Orthogonal Function (EOF) was performed on monthly total hotspot data for 228 months for determining dominant patterns spatially and temporally. Based on the EOF analysis results, the three major modes have achieved a total variance of 71 %. The first mode (EOF1) explains 65 % of the total variance. The second (EOF2) and third (EOF3) modes account for 3.60 % and 2.97 % of the total variance respectively. The first and the third principal component identified high loadings over the Indo-China and Sumatra-Borneo regions respectively. Whereas the second principal component separates the fire areas into China and Indo-China region. Inter-annual pattern is dominant in the EOF1, while the inter-seasonal pattern is dominant in EOF2 and EOF3. ENSO, IOD, and MJO are factors that influence the pattern of the determined principal components. The result of this study provides general understanding on how the fire events varied over the past two decades in SEA.
MODIS-derived fire spatial and temporal distribution during haze season in Southeast Asia using empirical orthogonal function
