Aug 2026
Interpretable geospatial machine learning for seasonal land surface temperature prediction using multi-source earth observation data
An interpretable machine learning framework to predict seasonal MODIS clear-sky daytime LST across Rostov Oblast, Russia, using multi-source Earth observation data from 2015 to 2024 provides a spatially explicit and interpretable approach for seasonal clear-sky daytime LST prediction in understudied temperate continent...
B. B. Thien, Tatiana Minkina, S. Sushkova et al.
· Earth Science Informatics · 1 citation