Paper Info
Title
Landsat-Based Land Cover Change in the Beijing-Tianjin-Tangshan Urban Agglomeration in 1990, 2000 and 2010.
Abstract
Rapid urbanization dramatically changes the local environment. A hybrid classification method is designed and applied to multi-temporal Landsat images and ancillary data to obtain land cover change datasets. A support vector machine (SVM) classifier is used to classify multi-temporal Landsat Enhanced Thematic Mapper Plus (ETM+) images that were collected in 2000 at the pixel level. These images are also segmented with the mean shift method. The impervious surface is refined based on a combination of the segmented objects and the SVM classification results. The changed areas in 1990 and 2010 are determined by comparing the Thematic Mapper (TM) and ETM+ images via the re-weighted multivariate alteration detection transformation method. The TM images that were masked as changed areas in 1990 and 2000 are input into the SVM classifier. Land cover maps for 1990 and 2010 are produced by combining the unchanged area in 2000 with the new classes of the changed areas in 1990 and 2010. Land cover change has continuously accelerated since 1990. Remarkably, arable land decreased, while the impervious surface area significantly increased.
Year
DOI
Venue
2017
10.3390/ijgi6030059
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
Field
DocType
land cover,mean shift,segment
Arable land,Impervious surface,Thematic Mapper,Ancillary data,Support vector machine,Remote sensing,Pixel,Mean-shift,Land cover,Geography,Cartography
Journal
Volume
Issue
ISSN
6
3
2220-9964
Citations 
PageRank 
References 
0
0.34
11
Authors
2
Name
Order
Citations
PageRank
Aqiang Yang111.45
Guoqing Sun216249.24