DocumentCode :
2989586
Title :
Change detection of land cover in Lushan based on TM remote sensing
Author :
Zhang, Wen ; Zhang, Qun ; Li, Manchun ; Tong, Lihua ; Chen, Yanming ; Cheng, Liang
Author_Institution :
Dept. of Geogr. Inf. Sci., Nanjing Univ., Nanjing, China
fYear :
2012
fDate :
15-17 June 2012
Firstpage :
1
Lastpage :
5
Abstract :
In this paper three images of Landsat TM data of 1983, 1999 and 2010 in winter being used to analyze the land cover changes in Lushan and surrounding areas. This paper classified the land cover types into 7 classes as cultivated land, grass land, forest land, sand, water, construction land and unused land by maximum likelihood classification, then analyses the land cover change. The results show that during 1983 to 2010, construction land increases every year, and the change is obvious; local area in the image contrast analysis showed the expansion of water area; forest land and cultivated land area decreased after increasing, while grass land area decreased year after year, but the change is much smaller from 1999 to 2010 compare with 1983 to 1999. Due to manual control, the sand of Poyang Lake, from 1983 to 2010 basically unchanged. The analysis could offer help for the regional land planning and land use.
Keywords :
geomorphology; geophysical image processing; image classification; maximum likelihood detection; terrain mapping; vegetation; vegetation mapping; AD 1983 to 1999; AD 1983 to 2010; AD 1999 to 2010; AD 2010; China; Landsat TM; Lushan; Poyang Lake; TM remote sensing; change detection; construction land; cultivated land; forest land; grass land; land cover classification; land use planning; maximum likelihood classification; regional land planning; sand; unused land; water; Cities and towns; Image color analysis; Image resolution; Lakes; Lead; Rivers; Lushan; TM image; change detection; land cover; remote sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics (GEOINFORMATICS), 2012 20th International Conference on
Conference_Location :
Hong Kong
ISSN :
2161-024X
Print_ISBN :
978-1-4673-1103-8
Type :
conf
DOI :
10.1109/Geoinformatics.2012.6270278
Filename :
6270278
Link To Document :
بازگشت