【目的】对历史土壤调查结果进行信息抽提与整合近年来得到国际科学界高度重视。高精度土壤时空信息可用于土壤与环境质量评价、耕地保育、抗旱防涝减灾、水土流失防治、面源污染防治、土壤与农产品污染防治等众多领域，是现代科学研究和管理不可或缺的新型基础工具。中国近代进行过多次土壤调查，积累了大量土壤调查资料，已具备构建土壤时空数据库基础条件，但多年来各地调查资料分散存留，丢失损毁严重，未能发挥应有作用。本研究目标是对中国不同时期土壤调查完成的大比例尺土壤图件、具有坐标的土壤剖面点与土壤采样点信息进行收集、提取与整合，构建中国数字土壤图数据库CDSM（China digital soil maps），以满足科学研究和管理对高精度土壤时空信息的需求。【方法】通过分析中国土壤调查资料状况与国际土壤调查主题变化趋势，完成了CDSM数据模型设计，确定了对全国各地土壤调查资料进行信息抽提与整合建库的工作边界。还建立并采用了海量空间数据分析方法和智能化海量空间信息分析软件包IMAT（Intelligent mapping tools），通过总计180多个分段流程的数据处理与分析，完成了对各地异源、异质、异构、异形土壤资料的信息抽提和CDSM构建。【结果】CDSM库收入的土壤资源与土壤质量信息在时间上覆盖了30多年，空间覆盖中国全境，要素类型有描述土壤要素地带性分布特征的面图层和描述土壤采样点信息的点图层两种。面图层精度主要为1﹕5万大比例尺。点图层为全国第二次土壤普查（二普）完成的10万个剖面和二普后完成的具有地理坐标的土壤剖面采样点和耕层采样点数据。CDSM规模宏大，能以100 m×100 m 空间分辨率提供具有时间序列和地理坐标的土壤信息，信息内容既含土壤类型、母质、土体构型、分层质地、机械组成等慢变化土壤信息，也含土壤有机质、氮、磷、钾、酸碱度、中微量元素含量等快变化土壤质量信息，不仅可用于了解土壤质量现势状况，也可用于预测土壤质量变化。【结论】CDSM 库数据模型既能有效收录中国各地30多年来进行的各类土壤调查科学记载，实现按时空序列或按主题类型的调用和分析，也便于延展和扩充，可将各地在新一轮土壤调查中完成的土壤采样点信息汇入S90PT点图层中。在CDSM构建过程中，其阶段性数据产品已为多家科研单位、多个部门应用，今后随着CDSM库增补、在时间尺度上的延伸和主题类型上的增加，CDSM库土壤时空信息将会在各领域有更广泛的应用。%Objective]High priority has been paid on development of soil geo data base based on soil legacy data by international scientific community in recent years. Temporal and spatial soil information with high resolution, as a new and indispensable tool for researchers and managers, can be applied to soil and environmental quality assessment, arable land conversation, flood and draught mitigation, erosion control, non-point source pollution control, soil and agricultural product pollution control and many other areas. In last decades, several nation-wide soil surveys have been conducted in China. Large number of soil data has been obtained. However, the valuable soil survey data, still in hand drafting map or paper printing format, has been unavailable to researchers and public shares, as the data have been stored at different locations and have not been processed, digitalized and integrated. The purpose of the study is to develop China Digital Soil Maps (CDSM) through extracting soil information from legacy data collected from the whole country.[Method]Data model of CDSM was constructed by analyzing the characteristics of soil legacy data from different time periods and with consideration of future trends to topics of soil survey. The data model confined the kinds and scopes of information to be extracted and compiled for CDSM. A data treatment working flow was developed, that composed of about 180 separated processes for extracting, analyzing and integrating heterogeneous and massive soil information of different regions and periods. CDSM has been completed by using the methodology for processing massive soil geo data and a computer software program IMAT (Intelligent Mapping Tools) developed in the study.[Result]CDSM was mainly composed of two kinds of soil geo information. One kind was vector maps of the whole country at 1﹕50 000 scale with polygon objects to describe soil types, soil organic matter, total nitrogen, available phosphorus, available potassium and pH-value. The second kind was point data of about 100 000 soil profiles and 80 000 plough layer samplings with description of sampling point coordinates, sampling year, and soil physical and chemical properties obtained from soil survey works since 1980s. The information contains both the slow-changing soil features such as soil types, parent material, soil mechanical composition, texture and other morphological features and the fast-changing properties such as concentrations of soil carbon and nutrient concentrations.[Conclusion]The study shows that the CDSM data model is fit both to accept different kind of legacy data from soil surveys across the country over 30 years and to further extend and expand in future. With the S90PT point layer, information of soil sampling points from the new round soil survey works can be added into CDSM. According to time series, space sequence or thematic order, required soil information of the whole country with a map resolution of 100 m×100 m can be inquired and provided by CDSM. The information has been applied by a number of agricultural, environmental and land resource organizations, divisions and research institutes for knowing current soil quality status and understanding changes in soil and environment quality. Along with the extension in time, space and themes in the future, CDSM spatial and temporal soil information will have broader application in various fields.
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