受传统制图技术和基础数据质量所限，历史土壤数据的空间详细度和属性精确度不能满足社会发展的需求。本研究将选择亚热带丘陵地区安徽省宣城市宣州区为研究区域，利用历史土壤图数据（二次土壤普查）以及研究区的环境景观因子(地形、母质、植被等)数据，应用多元自适应回归样条算法，提取与凝练土壤环境知识，构建主要土壤性质/土壤类型与环境景观因子之间的定量土壤-景观数学模型，实现历史土壤数据的更新制图。. 项目的目的在于挖掘历史土壤数据所潜在的土壤分布规律，将历史土壤数据更新为可重复、定量化、易移植使用的土壤-景观制图模型。该研究将推动数字土壤制图的发展，极大地提高土壤制图的效率和精度，降低土壤调查与制图的成本。

Conventional soil maps, as the major data source for information on the spatial variation of soil, are limited in terms of both the level of spatial detail and the accuracy of soil attributes. There is a need, therefore, to update conventional soil data to provide detailed and accurate soil information for agricultural and environmental policy making, watershed management, and nature and soil conservation..In this research, Multivariate adaptive regression splines (MARS) are used to extract the expert knowledges and quantify the relationships between soil attributions and environmental variables using conventional soil data in Xuanzhou Prefecture, Anhui Province. The aim of this research is to update the soil maps without additional fieldwork through digital soil mapping using conventional soil data. This method can be used in situations where the study area contains no or few soil profile descriptions at points, which would greatly improve the efficiency of digital soil mapping.