Geoville
2025-03-12

A new AI-powered model for improving land surface temperature (LST) estimation

How hot is your city? A new AI-powered model is improving land surface temperature (LST) estimation, providing better data to track climate change, urban heat islands, and the impacts of land use. Bridging the climate data gap, our Earth Observation Innovation Unit has just published a paper on a new CNN-based model for estimating LST using multi-source satellite and meteorological data.

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Harnessing Multi-Source Data and Deep Learning for High-Resolution Land Surface Temperature Gap-Filling Supporting Climate Change Adaptation Activities

Addressing global warming and adapting to climate change is a key focus of European and national strategies. LST is an essential tool for understanding climate-change-induced phenomena, from urbanization's effects on local climates to changes in land cover. Accurate and continuous LST estimation across large regions is critical for climate change mitigation efforts.

A new AI-powered model for improving land surface temperature (LST) estimation
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