Climate change acceleration and intensifying global carbon reduction efforts have created an urgent need to understand how climate transition risks affect carbon emission efficiency in energy enterprises. Our study breaks new ground by developing climate risk indicators through machine learning and...

As global climate change intensifies, with frequent extreme weather events, the stability of vegetation is severely threatened. This study (2002–2023) uses NDVI, temperature, and precipitation data, along with methods like pixel binary, trend analysis, and multiple regression residual analysis, to...