NDLI: Dynamic monitoring of land use/cover changes based on CBERS imagery

Content Provider	IEEE Xplore Digital Library
Author	Wang Li Chen Fu
Copyright Year	2011
Description	Author affiliation: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou City, Jiangsu Province, P.R. China (Wang Li; Chen Fu)
Abstract	The work present in this paper focuses on using CBERS imagery data to acquire some information such as land use/cover change (LUCC) by means of remote sensing and GIS and to find out an appropriate classification method to CBERS imagery by applying and comparing some classification methods. CBERS CCD imageries of Xuzhou city in 2001, 2005 and 2008 were classified by using decision tree classifier, support vector machine, maximum likelihood classifier and neural network classifier. After comparing the applicability and accuracy of four classification methods, the data classified by decision tree classifier was chosen to extract the land use information. In order to monitor the land-use, land-use dynamic degree and land-use preference index were introduced. The dynamic changes of land use and land cover from 2001 to 2008 were analyzed by utilizing GIS. Recent experiments in Xuzhou city suggested that the area was expanded rapidly and its construction area was being extended continuously. This research we have done suggests that the CBERS data has good application prospective in land use monitoring.
Starting Page	1
Ending Page	5
File Size	178532
Page Count	5
File Format	PDF
ISBN	9781612848495
ISSN	21610258
e-ISBN	9781612848488
DOI	10.1109/GeoInformatics.2011.5981155
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Charge coupled devices GIS Satellites Land use/cover changes CBERS imagery Buildings Cities and towns Decision tree classifier Decision trees Monitoring Remote sensing
Content Type	Text
Resource Type	Article
Subject	Geography, Planning and Development Computer Networks and Communications Information Systems Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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