自然资源遥感2026，Vol.38Issue(2)：1-11,11.DOI:10.6046/zrzyyg.2025130
基于田间尺度下土壤盐渍化遥感监测研究进展
Research advances in remote sensing monitoring of field-scale soil salinization
摘要
Abstract
Soil salinization can inhibit crop growth,diminish soil fertility,and cause ecological degradation,thereby leading to severe economic losses.The remote sensing technology provides real-time data with high spatiotemporal resolution for identifying,grading,and dynamically monitoring field-scale soil salinization.Focusing on current hot research topics of field-scale soil salinization,including multi-source and multi-scale integration,time series analysis,and machine learning/deep learning inversion and interpretability,this study reviewed the application of the remote sensing monitoring technology in field-scale soil salinization research,followed by a comprehensive analysis of the current status of agricultural soil salinization in fields.Based on domestic and international research advances,this study summarized the mechanisms and modeling for salinization monitoring,the methods for dynamic field monitoring,the application of field-scale soil salinization research methodologies,as well as the advantages and limitations of various types of sensors.However,challenges persist in the field-scale soil salinization research,including the prominent presence of mixed pixels,strong salinity heterogeneity induced by microtopography and irrigation,as well as the disruption by agricultural activities on water-salt migration.Therefore,from the perspective of artificial intelligence,this study suggests optimizing the scale transform and regional adaptation,developing physical models,and integrating multi-source data to enhance model robustness across different land use types and ecological zones.Overall,this study provides insights for future field-scale salinization monitoring and treatment.关键词
盐渍化/田间监测/遥感/人工智能Key words
salinization/field monitoring/remote sensing/artificial intelligence分类
信息技术与安全科学引用本文复制引用
邵长葆,何宝忠,马杰伟,王溥玄,钱梦媛..基于田间尺度下土壤盐渍化遥感监测研究进展[J].自然资源遥感,2026,38(2):1-11,11.基金项目
国家自然科学基金项目"干旱区绿洲土壤盐渍化对于冰川融水时空变化的响应"(编号:42361063)资助. （编号:42361063）
