16 October 2009 Dynamic study of land-use in Yining City
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Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74924M (2009) https://doi.org/10.1117/12.838603
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Based on models of land-use, the paper analyzes urban sprawl from the macroscopic to the micro level, predicts the demand for construction land in the city expansion, and presents the law between total amount of urban land demand and urban space expansion. Then by combining the data with current urban land and natural resources round the city, the paper appraises the rationality of the developed-land which will have changed their use-nature, to appraisal the feasibility and utilization ratio of the undeveloped land and nature resource which will be developed in nearly future, find out the irrationality that may appear in the urban space expanding, thus restrain through planning and policy. With the rapid develop of western regions in recent years, different with the eastern coastal zone; the western city is beginning its own urbanization process. Yili Prefecture, as the window of the development of western regions, is expected to see fast development within a few years. Meanwhile, to Yili Prefecture, the topographical ground form condition is complicated, the natural resources is extremely abundant, once it is destroyed will cause irretrievable losses. Under this background, how to handle the relation between city's development and natural environment and resources well, taking the urban development path that can be constant becomes the important subject that we can't avoid. So this paper uses linear regression mode and dynamics, offer valuable reference for smooth development of the city.
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Jiangping Wang, Jiangping Wang, Lu Wei, Lu Wei, } "Dynamic study of land-use in Yining City", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74924M (16 October 2009); doi: 10.1117/12.838603; https://doi.org/10.1117/12.838603

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