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传统土壤调查和制图建立在调查者经验思维基础上,目前对高精度土壤信息的大量需求对传统技巧性土壤调查方式提出了挑战,量化的土壤———景观模型日益受到土壤科学家的重视。近十年内世界各国开展了大量研究,试图将数字地形分析,GIS技术和土壤调查技术相结合,通过对景观信息的分析预测土壤信息。本文简要阐述土壤景观模型的基本原理和定义,对线性回归、回归树、判别分析、模糊聚类、地统计学、模糊推理和规则网络等模型的研究进展进行总结。在此基础上讨论了模型的发展方向和应用前景。
Traditional soil surveys and mapping are based on the investigators’ experience. The current large demand for high-precision soil information poses a challenge to the traditional techniques of soil survey. Quantitative soil-landscape models are increasingly valued by soil scientists. In recent ten years, many countries in the world have carried out a great deal of research, attempting to combine digital terrain analysis, GIS technology and soil investigation technology to predict soil information through the analysis of landscape information. This paper briefly describes the basic principles and definitions of soil landscape model and summarizes the research progress of linear regression, regression tree, discriminant analysis, fuzzy clustering, geostatistics, fuzzy reasoning and regular network models. On this basis, the development direction and application prospect of the model are discussed.