中国农业信息2025，Vol.37Issue(2)：28-43,16.DOI:10.12105/j.issn.1672-0423.20250203
土壤盐碱化遥感制图现状及趋势研究
Current status and trends in digital mapping of soil salinization
摘要
Abstract
[Purpose]Soil salinization is one of the primary forms of soil degradation.As a major global exporter and importer of grain,it is of paramount importance to ensuring China'food security through monitoring soil health.[Method]This paper first reviewed the importance of soil salinization issues from the perspectives of its occurrence mechanisms and China's current agricultural conditions.It then conducted a bibliometric analysis of the current progress in remote sensing monitoring of soil salinization,summarized the current methods used in soil salinization research,and finally analyzed the challenges faced in soil salinization mapping while outlined future development directions.[Result](1)In the research on salinization mapping,considerable disparities existed in the definition and classification of soil salinization levels due to differences in study area scale,geographical environment,research objectives,and investigator perspectives.(2)The environmental covariates generally suffered from issues such as poor availability,low resolution,and an unclear relationship with the mechanisms driving soil salinization,resulting in low inversion accuracy.(3)Significant progress had been made in the development of machine learning models.Nevertheless,the accuracy of these models remained limited,and their transferability was weak.[Conclusion]Future remote sensing extraction of soil salinization will aim for large-scale,multi-scale,and dynamic monitoring,focusing on deepening model algorithms and strengthening collaborative research on environmental covariates to improve the transferability of models and environmental covariates.A global data and model-sharing platform should be established to build a global-scale salinization distribution monitoring system,effectively meeting the practical application needs of agricultural production management.关键词
障碍因子/数字土壤制图/机器学习/盐碱化Key words
obstacle factor/digital soil mapping/machine learning/salinization引用本文复制引用
王经天,黄青,黄埔,石宇涵..土壤盐碱化遥感制图现状及趋势研究[J].中国农业信息,2025,37(2):28-43,16.基金项目
国家重点研发计划"黑土区土壤类型与关键土壤属性制图"(2023YFD1500102) （2023YFD1500102）
