DocumentCode :
2585950
Title :
Spatial distribution and driving mechanism of land degradation in Xinjiang based on RS and spatial regression model
Author :
Jiang, Wang Chang ; Qian, Wang ; Xiaobin, Jin
Author_Institution :
Land Arrangements Center, Land Resource Bur., Beijing, China
Volume :
2
fYear :
2010
fDate :
28-31 Aug. 2010
Firstpage :
246
Lastpage :
249
Abstract :
Land degradation is an important environmental problem, it will become a threat to food security and the sustainable development of socio-economic systems, ultimately affecting the development of humans with global warming. Xinjiang is a key region in China, in which land degradation is very serious. Combed RS with GIS technology, based on the latest remote sensing data, analyzed the spatial distribution pattern of land degradation in the provincial region of 85 counties in Xingjiang, applied spatial regression model to analyze the relationships between land degradation and influencing factors, formulated the main influencing factors. Land degradation in Xinjiang is from north to south and west to east, with a gradually increasing trend. Severe land degradation is found mainly in the Xinjiang region in the eastern. the main factors of land degradation are vegetation coverage, annual average rainfall, and land reclamation rate with regression coefficients of 381.967, -512.008 and -865.043, respectively.
Keywords :
food safety; geographic information systems; global warming; regression analysis; remote sensing; sustainable development; vegetation mapping; China; GIS technology; Xinjiang region; annual average rainfall; food security; global warming; influencing factors; land degradation; land reclamation rate; provincial region; regression coefficients; remote sensing data; socioeconomic systems; spatial distribution pattern; spatial regression model; sustainable development; vegetation coverage; Biological system modeling; Degradation; Indexes; Mathematical model; Remote sensing; Soil; Water resources; RS; land degradation; spatial pattern; spatial regression model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-8514-7
Type :
conf
DOI :
10.1109/IITA-GRS.2010.5602988
Filename :
5602988
Link To Document :
بازگشت