Knowledge-Based Classification in Automated Soil Mapping

作     者：ZHOU BIN and WANG RENCHAOInstitute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310029 (China) ZHOU BIN and WANG RENCHAOInstitute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310029 (China)

作者机构：Institute of Agricultural Remote Sensing and Information Technology Application Zhejiang UniversityHangzhou 310029 China 

出 版 物：《Pedosphere》 (土壤圈（英文版）)

年 卷 期：2003年第13卷第3期

页      面：209-218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：Project supported by the National Natural Science Foundation of China(Nos.40101014 and 40001008) 

主　　题：classification classification tree knowledge-based rule extracting soilmapping 

摘      要：A machine-learning approach was developed for automated building of knowledgebases for soil resources mapping by using a classification tree to generate knowledge from trainingdata. With this method, building a knowledge base for automated soil mapping was easier than usingthe conventional knowledge acquisition approach. The knowledge base built by classification tree wasused by the knowledge classifier to perform the soil type classification of Longyou County,Zhejiang Province, China using Landsat TM bi-temporal images and CIS data. To evaluate theperformance of the resultant knowledge bases, the classification results were compared to existingsoil map based on a field survey. The accuracy assessment and analysis of the resultant soil mapssuggested that the knowledge bases built by the machine-learning method was of good quality formapping distribution model of soil classes over the study area.