Land Surface Temperature

Land surface temperature (LST) is a crucial parameter for understanding Earth's climate system and its impacts, with research focusing on improving its accuracy and spatial resolution. Current efforts involve advanced machine learning techniques, such as deep learning networks (e.g., incorporating multi-modal data fusion and physics-constrained models) and gradient boosting methods, to overcome limitations of traditional remote sensing data and create gapless, high-resolution LST maps. These improvements are vital for enhancing climate change modeling, urban planning, wildfire management, and economic impact assessments, providing more accurate and timely information for decision-making.