卫星遥感在作物缺水诊断与预测中的应用进展OA

Accurate diagnosis and prediction of crop water deficit are essential for enhancing water resource utilization efficiency and advancing precision agriculture,serving as critical prerequisites for the intelligent management of irrigation water resources.The traditional methods for acquiring crop water information in irrigation districts are primarily at the point scale,which are time-consuming,labor-intensive,and have certain spatial limitations.Satellite remote sensing technology,with its wide coverage and continuous monitoring capabilities,provides extensive and long-term land surface information,making it an effective solution for assessing crop water deficit over large regions.This paper begins by summarizing the common methods used to acquire soil and crop water information in modern agriculture,analyzing their strengths and weaknesses.Then,based on the different responses of crops to water stress,the research progress of satellite remote sensing in crop water deficit diagnosis is described from the aspects of spectral reflection characteristics,microwave remote sensing technology,infrared thermometry,and multi-modal remote sensing data coupling.Finally,this study reviews the progress in applying crop growth models,machine learning algorithms,and hybrid-driven models for predicting crop water deficit and drought early warnings,while also addressing the challenges in crop water deficit diagnosis research.The aim is to clarify the application prospects and development directions of satellite remote sensing technology in crop water deficit diagnosis and drought prediction,offering new insights and references for future research in crop water deficit diagnosis using satellite remote sensing methods.