作者:Yang, XT (Yang, Xiao Tong)[ 1,2,3 ] ; Liu, HP (Liu, Huiping)[ 1,2,3 ] ; Gao, XF (Gao, Xiaofeng)[ 1,2,3 ]

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION

卷: 38  页: 129-137

DOI: 10.1016/j.jag.2014.12.015

出版年: JUN 2015

摘要

Land cover change information is crucial to analyse the process and the change patterns of environments and ecological systems. Recent studies have incorporated object-based image analysis for its ability to generate meaningful geographical objects into studies of change detection. In this research, we developed a systematic methodology to realise multi-type land cover changed object detection with medium spatial resolution remote sensing images in Beijing, China. Optimum index factor (OIF) was applied to determine the best change indicators and the chi-square transformation was carried out to determine the change threshold of the 4 classes of changed object. The clustering change vectors in the feature space were proposed to discriminate the change types. According to the accuracy assessment, the overall accuracy of changed/unchanged object detection was approximately 93.9% with an overall kappa of 0.824, and the change type discrimination also achieved an overall accuracy of 81.67%, indicating the effectiveness of the proposed method. (C) 2014 Elsevier B.V. All rights reserved.

通讯作者地址: Liu, HP (通讯作者)

Beijing Normal Univ, 19 XinJieKouWai St, Beijing 100875, Peoples R China.

地址:

[ 1 ] State Key Lab Remote Sensing Sci, Beijing, Peoples R China

[ 2 ] Beijing Key Lab Environm Remote Sensing & Digital, Beijing, Peoples R China

[ 3 ] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China