基于遥感影像数据的土壤制图研究进展

Research progress on soil mapping based on remote sensing image data

关键词:  遥感  土壤环境变量  第三次土壤普查  不确定性  数字土壤制图

Key words:  remote sensing  soil environmental variables  third national soil survey  uncertainty  digital soil mapping

摘要:

【目的】 数字土壤制图成本低、精度高，是刻画土壤环境变量的新技术和新工具，遥感技术在数字土壤制图业务化应用中发挥了重要作用，但是还存在诸多问题和不确定性。文章总结相关研究进展，以期为基于遥感影像数据的土壤数字制图提供有益参考。【方法】 梳理遥感技术在土壤类型与属性制图研究中的进展情况并进行总结展望，以期更好地发挥高空间、时间、光谱分辨率遥感数据在土壤数字制图方面的作用，为研发新模型、提高土壤制图模型精度提供信息支撑，为第三次全国土壤普查数字土壤制图提供有益参考。【结果】 遥感数据的特征与土壤发生学理论契合并推动了土壤制图的发展，但是，基于遥感的土壤制图技术在快速土壤环境变量因子提取、自适应制图指标筛选、满足多层级制图需求的土壤推测制图模型构建等方面还需要进一步深入探讨。【结论】 为了实现土壤类型与属性制图的业务化、流程化和自动化，未来的研究应该着眼于从“环境变量分析—评价指标体系筛选—预测模型构建”一体化解决方案入手，探讨如何融合多种遥感载荷、综合运用新型模型，以提高数字土壤制图的精度，为农业生产和土地资源管理提供更为精准的信息支撑。

Abstract:

［Purpose］ Digital soil mapping，with low cost and high accuracy，is a new technology and a new tool for portraying soil environmental variables. Remote sensing technology plays an important role in the operational application of digital soil mapping，but there are still many problems and uncertainties. This paper summarizes the progress of related research with the aim of providing useful references for digital soil mapping based on remotely sensed image data.［Method］ This paper reviewed the progress of remote sensing technology in the study of soil type and property mapping and provided a summary and outlook，with a view to better exploiting the role of high spatial，temporal，and spectral resolution remote sensing data in digital soil mapping，providing information support for the development of new models，and improving the accuracy of soil mapping models for the upcoming third national soil survey.［Results］ The study indicated that the characteristics of remote sensing data align with soil science theories and drive the development of soil mapping. However，further exploration was needed in areas such as rapid extraction of environmental variable factors，adaptive indicator selection and the construction of predictive models that meet the needs of multi-level mapping.［Conclusion］ In order to achieve the operational，procedural and automated mapping of soil types and properties，future research should focus on an integrated solution from"environmental variable analysis - evaluation indicator system selection - predictive model construction"，exploring how to integrate various remote sensing payloads and comprehensively apply new models to improve the accuracy of digital soil mapping to provide more accurate support for agricultural production and land resource management.