Evaluation and Adjustment of Coordinated Development between Land Use and Eco-Environment in Wuxi City
ABSTRACT
The purpose of this paper is to assess the coordinated development degree of land use and eco-environment in Wuxi City and choose the appropriate adjustment mode. Methods employed include documentation analysis, the coordinated development degree model analysis and BP neural network model analysis. The result shows that the coordinated development degree of land use and eco-environment in Wuxi City presents overall ever-increasing trends and that the overall consideration mode can reduce the contradiction between land use and eco-environment, which is a suitable mode for Wuxi City. It is concluded that the coordinated development degree model and BP neural network model have high reliability and practicability in evaluating and adjusting the coordinated development degree of land use and eco-environment in Wuxi City.
The purpose of this paper is to assess the coordinated development degree of land use and eco-environment in Wuxi City and choose the appropriate adjustment mode. Methods employed include documentation analysis, the coordinated development degree model analysis and BP neural network model analysis. The result shows that the coordinated development degree of land use and eco-environment in Wuxi City presents overall ever-increasing trends and that the overall consideration mode can reduce the contradiction between land use and eco-environment, which is a suitable mode for Wuxi City. It is concluded that the coordinated development degree model and BP neural network model have high reliability and practicability in evaluating and adjusting the coordinated development degree of land use and eco-environment in Wuxi City.
Cite this paper
nullH. Sun, H. Pan, J. Zhao, Q. Qu and F. Han, "Evaluation and Adjustment of Coordinated Development between Land Use and Eco-Environment in Wuxi City," iBusiness, Vol. 2 No. 4, 2010, pp. 415-420. doi: 10.4236/ib.2010.24055.
nullH. Sun, H. Pan, J. Zhao, Q. Qu and F. Han, "Evaluation and Adjustment of Coordinated Development between Land Use and Eco-Environment in Wuxi City," iBusiness, Vol. 2 No. 4, 2010, pp. 415-420. doi: 10.4236/ib.2010.24055.
References
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[1] B. L. Turner, “Two Types of Global Environment Changes: Definition and Spatial-Scale Issues in Their Human Dimen-sions,” Global Environmental Change, Vol. 1, No. 1, 1990, pp. 14-22. [2] C. Q. Song and S. Y. Leng, “Some Important Sci-entific Problems of Integrative Study of Chinese Geography in 5 to 10 Years,” Acta Geographica Sinica, Vol. 60, No. 4, 2005, pp. 546-552. [3] E. Kalnay and M. Cai, “Impact of Urbaniza-tion and Land -Use Change on Climate,” Nature, Vol. 423, No. 6939, 2003, pp. 528-531. [4] F. Steiner and L. McSherry, “Cohen Land Suitability Analysis for the Upper Gila River Watershed,” Landscape and Urban Planning, Vol. 50, No. 4, 2000, pp. 199-214. [5] L. Sliva and D. D. W. Buffer, “Zone versus Whole Catchment Approaches to Studying Land Use Impact on River Water Quality,” Water Research, Vol. 35, No. 14, 2001, pp. 3462-3472. [6] P. Reidsma, T. Tekelenburg, M. van den Berg and R. Alkemade, “Impacts of Land-Use Change on Biodiversity: An Assessment of Agricultural Biodiversity in the European Union,” Agriculture, Ecosystems and Environ-ment, Vol. 114, No. 1, 2006, pp. 86-10. [7] Z. B. Liao, “Quantitaitve Judgement and Classification System for Coor-dinated Development of Environment and Economy,” Tropical Geography, Vol. 19, No. 2, 1999, pp. 171-177. [8] F. R. Zhang, “Evaluation System and Method of Sustainable Use of Land,” China Agriculture Press, Beijing, 2003. [9] S. C. Li, etc., “An Analysis on Coordinated Development of the Eco-logical and Economic System around BoHai Area of Hebei Province,” Geographical Research, Vol. 17, No. 4, 1998, pp. 351-358. [10] Z. L. Jiang, “Introduction to Artificial Neural Networks,” Higher Education Press, Beijing, 2001. [11] H. L. Li, J. H. Gao, etc., “Land Sustainable Use Evaluation Based BP Neural Network in Henan Province,” Territory & Natural Re-sources Study, Vol. 4, No. 1, 2009, pp. 27-29. [12] Q. Y. Tang and M. G. Feng, “DPS Data Processing System,” Science Press, Beijing, 2006.