Interpolation-Based Fusion of Sentinel-5P, SRTM, and Regulatory-Grade Ground Stations Data for Producing Spatially Continuous Maps of PM2.5 Concentrations Nationwide over Thailand

Atmospheric pollution has recently drawn significant attention due to its proven adverse effects on public health and the environment. This concern been aggravated specifically in Southeast Asia increasing vehicular use, industrial activity, agricultural burning practices. Consequently, elevated PM2.5 concentrations have become a matter of intervention for national authorities who addressed needs monitoring air by operating ground stations. However, their spatial coverage is limited installation maintenance are costly. Therefore, alternative approaches necessary at regional scales. In current paper, we investigated interpolation models fuse measurements from stations satellite data an attempt produce spatially continuous maps nationwide over Thailand. Four compared, namely inverse distance weighted (IDW), ordinary kriging (OK), random forest (RF), combined with OK (RFK) leveraging NO2, SO2, CO, HCHO, AI, O3 products Sentinel-5P satellite, regulatory-grade measurements, topographic parameters. The results suggest that RFK most robust, especially when levels moderate or extreme, achieving RMSE value 7.11 μg/m3 R2 0.77 during 10-day long period February, 10.77 0.91 entire month March. proposed approach can be adopted operationally expanded stations, low-cost sensors, as well upcoming missions such GEMS Sentinel-5.