Pedosphere 31(4): 638--644, 2021
ISSN 1002-0160/CN 32-1315/P
©2021 Soil Science Society of China
Published by Elsevier B.V. and Science Press
| Soil property mapping by combining spatial distance information into the Soil Land Inference Model (SoLIM) |
Chengzhi QIN1,2,3, Yiming AN1,2, Peng LIANG1,2, Axing ZHU1,3,4,5 , Lin YANG6 |
1State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101 (China)
2College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049 (China)
3Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application and School of Geography, Nanjing Normal University, Nanjing 210097 (China)
4Department of Geography, University of Wisconsin-Madison, Madison WI 53706 (USA)
5Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023 (China)
6School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093 (China) |
| ABSTRACT |
| 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, SoLIM-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. |
| Key Words: digital soil mapping,location of soil sample,inverse distance weighting,soil organic matter,Third Law of Geography |
| Citation: Qin C Z, An Y M, Liang P, Zhu A X, Yang L. 2021. Soil property mapping by combining spatial distance information into the Soil Land Inference Model (SoLIM). Pedosphere. 31(4): 638-644. |
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