Title :
Spatial-temporal analysis of land use and coverage change in Nanjing based on GIS/RS
Author :
Cao, Kai ; Lv, Heng ; Wu, Bo ; Xu, Yong
Author_Institution :
Dept. of Geogr. & Resource Manage., Chinese Univ. of Hong Kong, Shatin, China
fDate :
June 29 2011-July 1 2011
Abstract :
Land Use and Coverage Change (LUCC) is an important aspect of global change. It is also very meaningful to regional development and land use management towards sustainable development. In this research, Nanjing, as one representative city in Yangtze River Delta, one of the regions which have the densest population and the quickest economic growth, was chosen to be the research area. Remote Sensing technology is very popular for monitoring land use change and detecting land use change areas. In this research, three Landsat TM/ETM+ images in 1988, 1994 and 2000 are chosed as the data, and classified by supervised classification method based on maximum likelihood method so as to monitor the land use change in Nanjing. And the spatial-temporal analysis models including land use structure, transition matrix, gravity centers, have been used to analyze the dynamic change of land use and land cover. The result shows that the land use and land cover had changed a lot during 1988-2000, especially for the building land and plough land. All these achievement are very meaningful and helpful to the land policy making towards sustainability.
Keywords :
environmental science computing; geophysical image processing; image classification; maximum likelihood estimation; sustainable development; terrain mapping; AD 1988; AD 1994; AD 2000; China; GIS; LUCC; Landsat ETM+ images; Landsat TM images; Nanjing; Yangtze River delta; coverage change spatiotemporal analysis; global change; gravity centers; land use change detection; land use change monitoring; land use management; land use spatiotemporal analysis; land use structure; maximum likelihood method; regional development; remote sensing; supervised classification method; sustainable development; transition matrix; Buildings; Gravity; MLC; Nanjing; Supervised Classification; TM/ETM+; Transition Matrix;
Conference_Titel :
Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on
Conference_Location :
Fuzhou
Print_ISBN :
978-1-4244-8352-5
DOI :
10.1109/ICSDM.2011.5969080