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浙江大学学报（理学版）
浙江大学学报（理学版）  2019, Vol. 46 Issue (5): 610-618    DOI: 10.3785/j.issn.1008-9497.2019.05.014
地球科学     
基于属性权重优化算法的土地利用绩效评价及差异分解分析
贾玉杰1,2, 杜震洪2, 张丰2, 刘仁义2
1.浙江大学 浙江省资源与环境信息系统重点实验室，浙江 杭州310028
2.浙江大学 地理信息科学研究所，浙江 杭州310027
Land use performance evaluation based on attribute weight optimization algorithm and analysis of land use performance differentiation.
JIA Yujie1,2, DU Zhenhong2, ZHANG Feng2, LIU Renyi2
1.Zhejiang Provincial Key Lab of GIS, Zhejiang University, Hangzhou 310028, China
2.Department of Geographic Information Science, Zhejiang University, Hangzhou 310027, China
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摘要： 为了解土地利用绩效现状，探究区域间绩效的差异特征，以31个省域2011—2015年的数据为研究对象，从土地利用结构、经济社会效益和生态可持续性3个角度构建绩效评价指标体系，用综合主客观赋权的属性权重优化算法确定指标权重，运用改进的TOPSIS模型测度绩效值，并用泰尔指数组间分解法定量分析区域内和区域间差异对总绩效差异的贡献度。结果表明：按三大地带分组时，东部差异对总体差异贡献最大，西部次之，中部最小；按六大常规分类分组时，华北、华东地区对总体差异贡献较大，东北、西北地区贡献较小；按九大土地利用分类分组时，京津冀鲁区、苏浙沪区对总体差异贡献较大，青藏区、东北区、晋豫区、湘鄂皖赣区贡献较小。总体上，绩效越高的省域对差异贡献越大，绩效越低的省域对差异贡献越小，且各区域间的差异格局长期存在。
关键词： 土地利用绩效;  属性权重优化算法;  绩效差异分解    
Abstract: In order to understand the status of land use performance and explore the different characteristics of interregional performance. This study took the data covered 31 provinces from 2011 to 2015 for analysis. Firstly, 18 indicators from three aspects of land use structure, economic and social benefits and ecological sustainability were selected to establish performance evaluation index system. Secondly, the attribute weight optimization algorithm which integrates subjective and objective weights was adopted to determine the index weight, and the improved TOPSIS model was used to measure the performance value. Moreover, the interregional and innerregional differences on the total performance difference were analyzed by Theil index decomposition between groups quantitatively. The results show that: The eastern difference made the largest contribution to the overall difference, followed by the western and central minimums; The north and east China contributed more to the overall differences, while the northeastern and northwestern regions contributed little; The Beijing-Tianjin-Hebei-Shandong region and Jiangsu-Zhejiang-Shanghai region contributed a lot to the overall difference, while Qinghai-Tibet region, Shanxi-Hebei region, Hunan-Hubei-Anhui-Jiangxi region and northeast region contributed less. On the whole, the higher performance, the higher contribution to the difference. The lower performance, the lower contribution to the difference. The pattern of differences among the groups had existed for a long time.
Key words: land use performance    attribute weight optimization algorithm    performance differences decomposition
收稿日期: 2018-01-20 出版日期: 2019-09-25
CLC:  P208  
基金资助: 国家自然科学基金资助项目(41671391，41471313，41101356，41101371，41171321)；国家科技基础性工作专项(2012FY 112300)；浙江省科技攻关项目(2014C33072，2013C33051)；国家海洋公益性行业科研专项经费资助项目(201505003-6).
通讯作者: ORCID: http://orcid.org/0000-0001-9449-0415     E-mail: duzhenhong@zju.edu.cn.
作者简介: 贾玉杰(1991—)，ORCID: http://orcid.org/0000-0001-5509-5631，女，硕士研究生，主要从事时空数据分析及挖掘研究.
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引用本文:

贾玉杰, 杜震洪, 张丰, 刘仁义. 基于属性权重优化算法的土地利用绩效评价及差异分解分析[J]. 浙江大学学报（理学版）, 2019, 46(5): 610-618.

JIA Yujie, DU Zhenhong, ZHANG Feng, LIU Renyi. Land use performance evaluation based on attribute weight optimization algorithm and analysis of land use performance differentiation.. Journal of Zhejiang University (Science Edition), 2019, 46(5): 610-618.

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https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2019.05.014    或    https://www.zjujournals.com/sci/CN/Y2019/V46/I5/610

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