[1]ZHAO Fei-fei,LIU Dong,LIU Meng.Driving Force Analysis of Land Use Structure in Jiansanjiang Branch Bureau Based on Information Entropy and Gray Correlative Degree[J].Research of Soil and Water Conservation,2012,19(03):250-253,258.
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
19
Number of periods:
2012 03
Page number:
250-253,258
Column:
Public date:
2012-06-20
- Title:
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Driving Force Analysis of Land Use Structure in Jiansanjiang Branch Bureau Based on Information Entropy and Gray Correlative Degree
- Author(s):
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ZHAO Fei-fei1, LIU Dong1,2, LIU Meng1
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1. College of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin 150030, China;
2. Postdoctoral Scientific Research Mobile Station of Agriculture and Forestry Economic Management, Northeast Agricultural University, Harbin 150030, China
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- Keywords:
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information entropy; gray correlative degree analysis; land use structure; driving force
- CLC:
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F301.2
- DOI:
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- Abstract:
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Under the support of GIS, based on the data of land use change survey from 1999 to 2009 in Jiansanjiang Branch Bureau and the associated economic and social statistics, Shannon entropy function was employed to analyze the entropy features of land use structure and evolution laws of land use types, and the gray correlative degree analysis method was used to study the driving forces of information entropy changes. The results showed that the information entropy was in a state of sustaining growth during 1999 to 2004, and the equilibrium degree of land use structure was in a state of sustaining growth as well. But information entropy was in a state of sustaining descend during 2005 to 2009, the equilibrium degree of land-use structure was in a state of sustaining decline, and advantage degree was rising. The area of low information entropy value of land use structure expanded in 2009. The resultsd indicated that land use structure was single; the orderliness of land use type was high. The results of gray correlative degree analysis method indicated that the factor of population mobility was the most obvious driving forces of the information entropy change.