基于熵权-TOPSIS模型的高新区土地利用绩效评价

发布时间：2018-04-16 21:42

本文选题：土地利用绩效 + 熵权　；参考：《科技通报》2017年04期

【摘要】：基于广东省第一次地理国情监测数据,为探讨高新区土地利用的综合效果和发展能力,以广东省清远市高新技术产业开发区为例,采用改进的熵权-TOPSIS模型和灰色关联分析法,评价高新区2009-2013年土地利用综合绩效动态变化及重要影响因素排序。结果表明:(1)2009-2013年,高新区土地利用综合绩效呈现先减少后稳定增长的趋势;(2)高新区土地利用的社会经济效益显著,而土地空间潜力挖掘不足,有较大发展空间;(3)道路铺张带动经济发展,而工业基础设施建设整体水平下降;(4)绿化意识增强,但生态效益不容乐观;(5)劳动力和经济投入偏低,发展潜力巨大。高新区土地利用综合绩效与基础设施建设、土地空间潜力挖掘、生态环境的综合关联度相对较高,未来高新区发展应重点关注基础设施完善、土地集约利用和生态环境保护。
[Abstract]:Based on the data of the first geographical situation monitoring in Guangdong Province, in order to discuss the comprehensive effect and development ability of land use in high-tech zones, the improved entropy weight TOPSIS model and the grey relational analysis method are adopted in the high-tech industrial development zone of Qingyuan City, Guangdong Province.To evaluate the dynamic changes of comprehensive land use performance and the ranking of important influencing factors in 2009-2013.The results show that the comprehensive performance of land use in the high and new developed zones shows a trend of first decreasing and then increasing steadily from 2009-2013) the social and economic benefits of land use in the zones are remarkable, but the potential of land space is insufficient.There is a great space for development: road spreading drives economic development, while the overall level of industrial infrastructure falls. 4) the consciousness of greening is enhanced, but the ecological benefit is not optimistic. 5) the labor force and economic investment are low, and the development potential is huge.The comprehensive performance of land use and infrastructure construction, the potential mining of land space and the comprehensive correlation degree of ecological environment in high-tech zones are relatively high. In the future, the development of high-tech zones should focus on the improvement of infrastructure, intensive use of land and ecological environment protection.
【作者单位】：华南农业大学公共管理学院;
【基金】：国家自然科学基金项目(41401626) 广东省哲学社会科学“十二五”规划学科共建项目(GD14XGL22)
【分类号】：F301.2

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