“Satellite remote sensing technology is widely used in the field of atmospheric water vapor detection, but its accuracy needs to be improved. Experts have utilized machine learning techniques to construct a MODIS water vapor product neural network correction model that takes into account spatial neighborhood features, significantly reducing correction errors and providing more accurate data support for atmospheric water vapor change research.”