Ping Wang, Jixian Zhang, Weidong Jia, Zongjian Lin
{"title":"土地利用/土地覆被决策树分类方法研究——以河北省树县为例","authors":"Ping Wang, Jixian Zhang, Weidong Jia, Zongjian Lin","doi":"10.1109/EORSA.2008.4620331","DOIUrl":null,"url":null,"abstract":"Adopting the decision tree technology, utilizing its process pattern that imitates human judgment and thinking and fault-tolerance features, the authors developed a decision tree classification method. Initially utilizing SPOT and TM, the work effectively enhanced LULC information and established the synthetic database; then, combining geoscience synthetic analysis with ground spectral feature information, utilizing the CART system; the authors built the decision tree model that is based on the decision rules. At last, we discussed the wild use of LULC decision tree classified and stratified extractive technology. Taking three counties in Hebei province as examples, we divided the research area to classify each unit (county area) by ecological division, utilized multiple data resources and geoscience rules to build the decision tree model and test and verify the method. The results demonstrated that the method improves the speed and precision of classification.","PeriodicalId":142612,"journal":{"name":"2008 International Workshop on Earth Observation and Remote Sensing Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A study on decision tree classification method of land use/land cover -Taking tree counties in Hebei Province as an example\",\"authors\":\"Ping Wang, Jixian Zhang, Weidong Jia, Zongjian Lin\",\"doi\":\"10.1109/EORSA.2008.4620331\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adopting the decision tree technology, utilizing its process pattern that imitates human judgment and thinking and fault-tolerance features, the authors developed a decision tree classification method. Initially utilizing SPOT and TM, the work effectively enhanced LULC information and established the synthetic database; then, combining geoscience synthetic analysis with ground spectral feature information, utilizing the CART system; the authors built the decision tree model that is based on the decision rules. At last, we discussed the wild use of LULC decision tree classified and stratified extractive technology. Taking three counties in Hebei province as examples, we divided the research area to classify each unit (county area) by ecological division, utilized multiple data resources and geoscience rules to build the decision tree model and test and verify the method. The results demonstrated that the method improves the speed and precision of classification.\",\"PeriodicalId\":142612,\"journal\":{\"name\":\"2008 International Workshop on Earth Observation and Remote Sensing Applications\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Workshop on Earth Observation and Remote Sensing Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EORSA.2008.4620331\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Workshop on Earth Observation and Remote Sensing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EORSA.2008.4620331","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A study on decision tree classification method of land use/land cover -Taking tree counties in Hebei Province as an example
Adopting the decision tree technology, utilizing its process pattern that imitates human judgment and thinking and fault-tolerance features, the authors developed a decision tree classification method. Initially utilizing SPOT and TM, the work effectively enhanced LULC information and established the synthetic database; then, combining geoscience synthetic analysis with ground spectral feature information, utilizing the CART system; the authors built the decision tree model that is based on the decision rules. At last, we discussed the wild use of LULC decision tree classified and stratified extractive technology. Taking three counties in Hebei province as examples, we divided the research area to classify each unit (county area) by ecological division, utilized multiple data resources and geoscience rules to build the decision tree model and test and verify the method. The results demonstrated that the method improves the speed and precision of classification.