Title :
The detection of vegetation change in Wuhan City based on object-oriented method
Author :
Han, Chen ; Maolin, Chen ; Jincheng, Shi ; Run, Huang ; Jun, Yan
Author_Institution :
Sch. of Remote Sensing & Inf. Eng., Wuhan Univ., Wuhan, China
Abstract :
Vegetation is one of the most important parts of the city´s ecological system, which has a great significance to improve the quality of city´s environment and citizens´ life quality. In this study the TM images of 1993, 1998, 2002 and 2005 are used as data resources, eCognition software and the method of object-oriented classification are used to extract vegetation information. And on this basis, the features and causes of temporal and spatial changes of vegetation in Wuhan are analyzed.
Keywords :
agriculture; ecology; environmental science computing; object-oriented methods; pattern classification; vegetation; Wuhan City; citizen life quality; eCognition software; ecological system; environment quality; object-oriented classification; object-oriented method; vegetation change detection; vegetation information; Accuracy; Buildings; Cities and towns; Data mining; Image segmentation; Indexes; Vegetation mapping; Change detection; Multiscale segmentation; Object-oriented classification; Wuhan city; Wuhan: TM image;
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
DOI :
10.1109/AIMSEC.2011.6010872
