Soil property mapping by combining spatial distance information into the Soil Land Inference Model(SoLIM)

作     者：Chengzhi QIN Yiming AN Peng LIANG Axing ZHU Lin YANG Chengzhi QIN;Yiming AN;Peng LIANG;Axing ZHU;Lin YANG

作者机构：State Key Laboratory of Resources and Environmental Information SystemInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101(China) College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 100049(China) Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application and School of GeographyNanjing Normal UniversityNanjing 210097(China) Department of GeographyUniversity of Wisconsin-MadisonMadison WI 53706(USA) Key Laboratory of Virtual Geographic EnvironmentMinistry of EducationNanjing Normal UniversityNanjing 210023(China) School of Geographic and Oceanographic SciencesNanjing UniversityNanjing 210093(China) 

出 版 物：《Pedosphere》 (土壤圈（英文版）)

年 卷 期：2021年第31卷第4期

页      面：638-644页

核心收录：

学科分类：09[农学] 0903[农学-农业资源与环境] 090301[农学-土壤学] 

基　　金：funded by the National Natural Science Foundation of China (Nos.41871300,41422109,and 41431177) the National Basic Research Program of China (No.2015CB954102) the Priority Academic Program Development of Jiangsu Higher Education Institutions,China (No.164320H116) the Outstanding Innovation Team in Colleges and Universities in Jiangsu Province,China the support from the Innovation Project of State Key Laboratory of Resources and Environmental Information System of China (No.O88RA20CYA) 

主　　题：digital soil mapping location of soil sample inverse distance weighting soil organic matter Third Law of Geography 

摘      要：The Soil Land Inference Model(SoLIM) was primarily proposed by Zhu et al.(Zhu A X, Band L, Vertessy R, Dutton B. 1997. Derivation of soil properties using a soil land inference model(SoLIM). Soil Sci Soc Am J. 61: 523–533.) and was based on the Third Law of Geography. Based on the assumption that the soil property value at a location of interest will be more similar to that of a given soil sample when the environmental condition at the location of interest is more similar to that at the location from which the sample was taken, SoLIM estimates the soil property value of the location of interest using the soil property values of known samples weighted by the similarity between those samples and the location of interest in terms of an attribute domain of environmental conditions. However, the current SoLIM method ignores information about the spatial distances between the location of interest and those of the sample. In this study, we proposed a new method of soil property mapping, So LIM-IDW, which incorporates spatial distance information into the SoLIM method by means of inverse distance weighting(IDW). The proposed method is based on the assumption that the soil property value at a location of interest will be more similar to that of a known sample both when the environmental conditions are more similar and when the distance between the location of interest and the sample location is shorter. Our evaluation experiments on A-horizon soil organic matter mapping in two study areas with independent evaluation samples showed that the proposed SoLIM-IDW method can obtain lower prediction errors than the original SoLIM method, multiple linear regression, geographically weighted regression, and regression-kriging with the same modeling points. Future work mainly includes the determination of optimal power parameter values and the appropriate setting of the parameter under different application contexts.