Remote Sensing Drought Monitoring and Assessment in Southwestern China based on Machine Learning

Due to the complexity of drought and the diversity of influencing factors， the accurate monitoring of drought still faces many problems， especially the increasing frequency and aggravation of drought in Southwestern China， and the formation and disaster causing process have certain particularity.However， the traditional drought monitoring methods cannot meet the requirements of regional drought monitoring， so more scientific monitoring methods and means are needed.Since machine learning can comprehensively consider a variety of disaster causing factors to establish a comprehensive drought monitoring model， it undoubtedly provides a new technical means for drought monitoring.Therefore， this paper used multi-source remote sensing data from 2010 -2019 and meteorological station data from 1980-2019 to first construct a random forest monitoring model to reconstruct and supplement the surface temperature in Southwestern China， and then constructed XGBoost monitoring model to monitor， evaluate and validate the droug