SAR数据在土壤盐渍化监测中的应用研究进展  

Research Progress in the Application of SAR Data in Soil Salinity Monitoring

作　　者：刘康怡 赵振宇 李俐 LIU Kangyi;ZHAO Zhenyu;LI Li(College of Land Science and Technology,China Agricultural University,Beijing 100083,China;Key Laboratory of Remote Sensing for Agri-Hazards,Ministry of Agriculture and Rural Affairs,Beijing 100083,China)

机构地区：[1]中国农业大学土地科学与技术学院,北京100083 [2]农业农村部农业灾害遥感重点实验室,北京100083

出　　处：《地球信息科学学报》2024年第8期1893-1910,共18页Journal of Geo-information Science

基　　金：国家自然科学基金项目(42171324)。

摘　　要：土壤盐渍化不仅会造成土地荒漠化等生态问题,而且可能减低耕地数量和质量,对粮食安全构成威胁。快速、准确地获取土壤盐渍化信息对及时有效的土壤治理具有重要意义。近些年来,微波遥感的发展为大面积快速实现土壤盐渍化监测提供了新的思路,基于合成孔径雷达(Synthetic Aperture Radar,SAR)数据的土壤盐渍化监测成为当前遥感土壤盐渍化研究领域的热点之一。本文从盐渍化土壤微波散射机理、盐渍化土壤特征参数的构建与提取、盐渍化土壤分类、土壤含盐量反演4个方面总结国内外土壤盐渍化SAR遥感监测的主要进展与标志性成果:(1)盐渍化土壤微波散射机理的研究明确了土壤含盐量与雷达后向散射系数的相关关系;(2)盐渍化土壤特征参数的构建与提取呈现多元化、综合化变化趋势;(3)盐渍化土壤分类方法从机器学习向深度学习方法转移;(4)土壤含盐量反演从回归分析向结合散射机理的反演方法转化。同时,本文提出现有研究存在的问题和挑战:土壤含盐量与后向散射系数关系受到多种因素的影响,实现高精度的土壤盐渍化SAR遥感技术监测,还需更深入的机理解析、特征构建和多源数据的融合利用。Soil salinization is a significant issue that not only leads to ecological problems like land desertification but also poses a threat to food security by reducing the quantity and quality of arable land.Therefore,it is crucial to rapidly and accurately obtain information about soil salinization for timely and effective soil management.In recent years,the development of microwave remote sensing has provided new methods for large-scale and rapid monitoring of soil salinization,with Synthetic Aperture Radar(SAR) databased soil salinization monitoring becoming a hotspot in remote sensing research.Recent advancements in SAR remote sensing for soil salinization monitoring can be summarized in four main aspects:(1) Microwave scattering mechanism of saline soil:Research has clarified the correlation between soil salinity and radar backscattering coefficients,providing a basis for estimating soil salinity using SAR data.Understanding the microwave scattering mechanism of saline soil is essential for accurately interpreting SAR data and extracting meaningful information about soil salinization.(2) Construction and extraction of characteristic parameters of saline soil:The construction and extraction of characteristic parameters of saline soil have shown a trend towards diversification and integration.Various parameters,such as backscattering coefficients,polarization ratios,and texture features,are used to characterize the properties of saline soil.By utilizing a combination of these parameters,researchers can obtain a more comprehensive understanding of soil salinization.(3) Classification of saline soil:The classification methods for saline soil have shifted from traditional machine learning to deep learning methods.Deep learning algorithms,such as convolutional neural networks,have shown promising results in accurately classifying saline soil areas.These advanced techniques enable the identification and mapping of different levels of soil salinity,aiding in effective soil management strategies.(4) Inversion of soil sali

关 键 词：合成孔径雷达 土壤盐渍化 后向散射系数 土壤介电常数 监测 研究进展 土壤含盐量 反演 

分 类 号：S156.4[农业科学—土壤学] S127[农业科学—农业基础科学]