Extracting Impervious Surface and Its Change Information Using Satellite Remote Sensing Data  

流域不透水面及其变化信息提取(英文)

作　　者：马雪梅[1] 李希峰[2] 

机构地区：[1]聊城大学环境与规划学院,山东聊城252059 [2]聊城大学建工学院,山东聊城252059

出　　处：《Agricultural Science & Technology》2008年第6期113-117,共5页农业科学与技术（英文版）

摘　　要：Impervious surface is one of the important parameters of valley water circular simulation,scientific estimation for which has significant and practical value for the urban water quantity and process simulation,diffuse pollution estimating and the forecast of climate changes.The objective of this research is to get the information of impervious surface and its dynamic change.Through the computer-assisted field method,the technologies of decision tree and data mining were applied to withdraw the impervious surface information in research region by the Landsat TM data in 1988,1994 and 2002.The results suggested that the accuracy of impervious surface information extraction in the study area arrived above 94.4% in 2002 image.On this basis,the mixed method was used to extract the location and the types of the impervious surface change.The overall accuracy of monitoring reached 89%,which meets the demand of the hydrological models.Impervious surface is one of the important parameters of valley water circular simulation,scientific estimation for which has significant and practical value for the urban water quantity and process simulation,diffuse pollution estimating and the forecast of climate changes.The objective of this research is to get the information of impervious surface and its dynamic change.Through the computer-assisted field method,the technologies of decision tree and data mining were applied to withdraw the impervious surface information in research region by the Landsat TM data in 1988,1994 and 2002.The results suggested that the accuracy of impervious surface information extraction in the study area arrived above 94.4% in 2002 image.On this basis,the mixed method was used to extract the location and the types of the impervious surface change.The overall accuracy of monitoring reached 89%,which meets the demand of the hydrological models.

关 键 词：Impervious surface MONITORING REMOTE SENSING DECISION TREE classification 

分 类 号：S126[农业科学—农业基础科学]