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The decline in air quality is a significant global issue, with agricultural practices and biomass burning being a few of the factors contributing to harmful pollutants. In 2015, Malaysia faced severe air quality deterioration due to forest fires and agricultural burning, worsened by El Niño–Southern Oscillation (ENSO) conditions. Vegetation fires, particularly forest fires, emit pollutants and cause temperature fluctuations, significantly impacting air quality. Although satellites like NOAA’s GOES16 and NASA’s MODIS are used for fire detection, data coverage and capture frequencies create uncertainties. This study examines local vegetation burning data from the Fire and Rescue Department of Malaysia (BOMBA), MODIS hotspots from the Fire Information for Resource Management System (FIRMS), and MODIS Burned Area Monthly L3 Global 500m (MCD64A1). The analysis focuses on the spatial distribution and trends of vegetation burning in Peninsular Malaysia’s forests and agricultural lands in 2015. It also compares fire detection data from BOMBA and MODIS to identify discrepancies between the local and remote sensing datasets. The research aims to enhance understanding of vegetation fire activities in Peninsular Malaysia, offering insights for more effective fire management and mitigation strategies.