Object-based change monitoring in mining areas-taking Pingshuo as an example

摘要：

　　In this paper, RapidEye Remote Sensing Image (Map 2012) and SPOT7 Remote Sensing Image (Map 2015) in Pingshuo Mining Area are selected as the data.Combined with object-based classification and change vector analysis method, we studied the feasibility of high resolution remote sensing image for mining land classification and the accuracy of monitoring.The results show that the classification of reclaimed mining land has higher precision, the overall accuracy and kappa coefficient of the classification of Map2012 were 0.89 and 0.87, and the change region map were 0.87 and 0.84.Its obvious that object-based classification and change vector analysis which has a great significance to improve the monitoring accuracy can be used to monitor mining land, especially reclaiming mining land.

关键词： land use/cover monitoring object-based classification change vector analysis open-pit coal mine land reclamation

作者: M.L.Zhang W.Zhou T.Yuan Y.H.Xie Y.F.Li

作者单位: School of Land Science and Technology, China University of Geosciences, Beijing, China Center for Urban and Environmental Change, Department of Earth and Environmental Systems,Indiana Sta School of Environment, Beijing Normal University, Beijing, China

会议类型: 国际会议

会议名称: The 2nd International Symposium on Land Reclamation and Ecological Restoration (第二届国际土地复垦与生态修复学术研讨会)

会议地点: 西安

会议语种:英文

页码: 127-130

在线出版日期: 2017-10-20（万方平台首次上网日期，不代表论文的发表时间）