Paper
14 November 2007 Land use change and its driving forces in alluvial-plain oasis
Luxiang Xiao, Zengxiang Zhang, Xi Chen, Geping Luo
Author Affiliations +
Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67901U (2007) https://doi.org/10.1117/12.749358
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
Land use change and its driving factors are hot topics of global change research, and also important topics of sustainable development. This paper selected a small area in alluvial plain oasis in Xinjiang Autonomous region of China as the study area. Using Landsat TM data of 1987, 1998 and 2004, the dynamic process of the spatial-temporal characteristics of land use changes were analyzed to improve understanding and to find the driving forces of land use changes so that sustainable land utilization could be practiced. During the 17 years salt-alkali tolerant cropland, cereal cropland, vegetable-fruit land, and shrubbery, had decreased remarkably by 78.59%, 85.95%, 92.13%, 68.43%, respectively. Cotton-liquorice land, grape-hop land, planted forest, residential area in town, residential area in village, and saline-alkaline field had increased dramatically. The increased percentage received the value of 2432.11%, 10103.18%, 889.91%, 222.45%, 96.00%, 44.18%, respectively. By the logistic regression, the main driving factors were derived for each land use type. The advance of technology (fertilizer input, irrigation quota, and animal labor et al.) and market (unit are yield net) were the main driving factors. Policy, in a higher level, influenced the land use dynamics for all the land use changes.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luxiang Xiao, Zengxiang Zhang, Xi Chen, and Geping Luo "Land use change and its driving forces in alluvial-plain oasis", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67901U (14 November 2007); https://doi.org/10.1117/12.749358
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KEYWORDS
Agriculture

Data conversion

Data modeling

Earth observing sensors

Landsat

Climatology

Roads

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