Developing Models to Predict Areas at Risk of Burned Areas in Forests from an Effect of the ENSO Phenomenon Using Space Technology Data in Sam Ngao District, Tak Province
Keywords:
wildfires, ENSO Phenomenon , tropical forest ecosystem , predictive model , space technologyAbstract
Background and Objectives : This study has two objectives: 1) to analyze the relationship between the forest ecosystem and the burned areas in tropical forests from an effect of the ENSO phenomena; and 2) to study the physical factors and develop models to predict areas at risk of burned areas in forests from an effect of the ENSO Phenomenon in Sam Ngao District, Tak Province.
Methodology : Data used in this study were; 1) Sentinel-2 data between January-March in the ENSO years;
El Niño (2019), Neutral (2020) and La Niña (2022) years, these data were used to analyze Burned Area Index for Sentinel 2 (BAIS2), Normalized Difference Vegetation Index (NDVI), and Moisture Stress Index (MSI);
2) Landsat 8 (TIRS) data were used to extract Land Surface Temperature (LST); and 3) Topographic images from NASA's Shuttle Radar Topography Mission (SRTM) were used to analyze Digital Elevation Model (DEM), slope and aspect. Monthly NDVI and BAIS2 were used to examine the relationship between forest ecosystem and burned areas in tropical forests using pearson correlation. The creation of the predictive model was performed from Multiple Linear Regression (MLR). The dependent variable is burned area and the independent variables are NDVI, LST, MSI, DEM, slope, and aspect.
Main Results : The results found that there is a relationship between forest ecosystem integrity and burned areas in ENSO years. For the predictive model areas at risk of burned areas in forests, El Niño, Neutral and La Niña years could predict wildfires with high (R2 = 0.905), high (R2 = 0.700), and moderate (R2 = 0.519) precisions, respectively. The factors influencing wildfires are NDVI, LST and MSI.
Conclusions : The study found that forest ecosystem integrity in tropical forests and areas prone to wildfires is closely related to climate change from the ENSO phenomenon, including measures to prohibit forest and agricultural burning as declared by the provinces.
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