Estimation of burned severity areas using landsat8 data from 2016 to 2022 in Chiang Mai province

This study aims to evaluate the area and severity of wildfire damage in Chiang Mai Province using LANDSAT8 satellite data from 2016, 2018, 2020, and 2022, and to analyze the relationship between spatial factors, namely the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST), with fire occurrence and severity. The study utilized hotspot data analysis in conjunction with the Differenced Normalized Burn Ratio (dNBR) index to assess the area and classify fire severity levels, while also analyzing pre-fire and post-fire NDVI and LST values to identify correlations. The results indicated that 2020 experienced the most severe fire situation, recording 1,716 hotspots and a total damaged area (Low Severity and higher) of 1989.66 km² within the hotspot buffer radius, with the total damaged area ranking 2020 (1989.66 km²), followed by 2018 (489.10 km²), 2022 (331.84 km²), and 2016 (106.88 km²). The factor analysis revealed that areas with low pre-fire NDVI and high pre-fire LST correlated significantly with fire occurrence; notably, the high average LST (33.2°C) in 2020, combined with degraded vegetation (low NDVI), reflected conditions highly conducive to severe fire incidents, and furthermore, fire severity demonstrated a significant positive correlation with LST and a significant negative correlation with NDVI. This knowledge is applicable to developing a proactive monitoring and prediction system for high fire-risk areas using NDVI and LST as key indicators, thereby supporting targeted resource allocation for fire prevention, real-time situational monitoring, and long-term sustainable forest resource management.