收稿日期: 2008-02-19
修回日期: 2008-05-20
网络出版日期: 2008-08-10
基金资助
国家自然科学基金创新群体项目“土壤有机碳氮主控因素的幅度效应”（编号：40621001）；国家重点基础研究发展计划项目“中国主要水蚀区土壤侵蚀过程与调控研究”（编号：2007CB407206）；国家科技基础条件平台——地球系统科学数据共享网项目“全国小比例尺土壤专题数据库建设”（编号：2006DKA32300-15）；中国科学院知识创新工程领域前沿项目“土壤属性空间变异预测的尺度效应研究”（编号：ISSASIP0715）资助.
Effects of the Linkage between Spatial Data and Attribute Data on Estimates of Soil Organic Carbon
Received date: 2008-02-19
Revised date: 2008-05-20
Online published: 2008-08-10
土壤有机碳(Soil Organic Carbon, SOC) 库在陆地生态系统中具有重要作用。在基于GIS利用土壤类型法估算SOC储量时，由于土壤图比例尺的限制，属性数据与空间数据的连接会导致对SOC储量的估算结果产生很大不确定性。利用中国滇黔桂地区（云南省、贵州省和广西壮族自治区）798个土壤剖面及1：50万土壤图在不同的制图单元水平上，分别采用算术平均值法、中值法和面积加权平均值法（以土种志中的面积为权重）估算了该地区1 m深度SOC储量，并与基于土壤学专业知识连接方法（Pedological Knowledge Based Method, PKB）的估算结果进行了比较。结果表明：面积加权平均值法比中值法和算术平均值法的估算结果更为准确，而且在土类、亚类和土属水平上应用面积加权平均值法对SOC储量的估算结果差异不大。在采用较大比例尺、较为详细的土壤图时，PKB法较理想；反之，则面积加权平均值法较好。
张勇 , 于东升 , 孙维侠 , 赵永存 , 王洪杰 , 史学正 . 属性数据与空间数据连接对土壤有机碳储量估算的影响[J]. 地球科学进展, 2008 , 23(8) : 840 -847 . DOI: 10.11867/j.issn.1001-8166.2008.08.0840
Soil organic carbon (SOC) pool plays a key role in the terrestrial eco-systems. Limited by the map scale of soil maps, the linkage between attribute and spatial data can cause large uncertainties in estimating SOC storage with the soil type method. In this study, with a total of 798 SOC density data and the 1:500 000 soil maps, the SOC storage in Yunnan-Guizhou-Guangxi Region of China (including Yunnan province, Guizhou province and Guangxi Zhuang Autonomous Region) was estimated using the soil type method with the linkage of arithmetic mean method, median method, and area-weighted mean method (based on the area recorded in the Soil Series) based on different map units and the results were compared with that of the linkage of PKB method (Pedological Professional Knowledge Based Method). The results show that the linkage of area-weighted mean method is better than arithmetic mean method and median method. The differences of the estimates with area-weighted mean method based on different map unites are the smallest. The PKB method can do better when the detailed soil maps with large map scales are utilized, or else the area-weighted mean method should be adopted.
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