DocumentCode
3209718
Title
Land Use Change Modeling and Predicting of Xinzhuang Town Based on CLUE-S Model
Author
Rui, Zhou ; Yuanman, Hu ; Yuehui, Li ; Hongshi, He
Author_Institution
Inst. of Appl. Ecology, Chinese Acad. of Sci., Shenyang, China
Volume
2
fYear
2010
fDate
11-12 May 2010
Firstpage
581
Lastpage
584
Abstract
Land use change models are the important tools in researching regional landscape dynamics and its driving mechanisms. Researchers have aimed at exploring land use/cover change (LUCC) and predicting future land use pattern in order to improve our understanding of the causes and effects. With the application of CLUE-S (Conversion of Land Use and Its Effects at Small Regional Extent) model and under the support of high-resolution remotely sensed data(1980, 1991, 2001 and 2009 high-resolution remote sensing images: spatial resolution is not more than 1m), this study analyzed landscape change from 1980 to 2009, simulated the land use of 2009 from 1980, 1991 and 2001, respectively, and predicted the land use changes of Xinzhuang town in the south of Jianhsu province for current trend scenario from 2010 to 2027. Results showed that paddy field decreased dramatically from 1980 to 2009, while construction land and fish pond increased largely. With the modeling time´s decreasing, the modeling accuracy was increasing (67%: from 1980, 75%: from 1991, 80%: from 2001), and we identified 18 years were the appropriate temporal scale based on the kappa coefficient wasn´t less than 75%. The predicted results of CLUE-S shows that the paddy field would keep on decreasing in future, most of which were invaded and occupied by construction land and fish pond, the construction land and fish pond would increase dramatically in 2027, the changes of other types weren´t obvious.
Keywords
geographic information systems; land use planning; regional planning; statistical analysis; terrain mapping; CLUE-S model; Jianhsu; Kappa coefficient; Xinzhuang town; construction land; driving mechanism; fish pond; land use conversion; paddy field; regional landscape dynamic; remotely sensed data; Automation; Biological system modeling; Cities and towns; Economic forecasting; Ecosystems; Environmental factors; Humans; Marine animals; Predictive models; Sustainable development; CLUE-S; Kappa; LUCC; Modeling; Predicting;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-7279-6
Electronic_ISBN
978-1-4244-7280-2
Type
conf
DOI
10.1109/ICICTA.2010.525
Filename
5523565
Link To Document