1 State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, P.R.China 2 University of Chinese Academy of Sciences, Beijing 100049, P.R.China 3 Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, P.R.China 4 Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, P.R.China 5 Department of Geography, University of Wisconsin-Madison, Madison 53706, USA 6 School of Environmental and Sustainability Sciences, Kean University, Union 07083, USA
Conventional soil maps contain valuable knowledge on soil–environment relationships. Such knowledge can be extracted for use when updating conventional soil maps with improved environmental data. Existing methods take all polygons of the same map unit on a map as a whole to extract the soil–environment relationship. Such approach ignores the difference in the environmental conditions represented by individual soil polygons of the same map unit. This paper proposes a method of mining soil–environment relationships from individual soil polygons to update conventional soil maps. The proposed method consists of three major steps. Firstly, the soil–environment relationships represented by each individual polygon on a conventional soil map are extracted in the form of frequency distribution curves for the involved environmental covariates. Secondly, for each environmental covariate, these frequency distribution curves from individual polygons of the same soil map unit are synthesized to form the overall soil–environment relationship for that soil map unit across the mapped area. And lastly, the extracted soil–environment relationships are applied to updating the conventional soil map with new, improved environmental data by adopting a soil land inference model (SoLIM) framework. This study applied the proposed method to updating a conventional soil map of the Raffelson watershed in La Crosse County, Wisconsin, United States. The result from the proposed method was compared with that from the previous method of taking all polygons within the same soil map unit on a map as a whole. Evaluation results with independent soil samples showed that the proposed method exhibited better performance and produced higher accuracy.