Evaluation of regional land use performance based on entropy TOPSIS model and diagnosis of its obstacle factors

Xunping Lei, Robin Qiu, Yong Liu

Research output: Contribution to journalArticlepeer-review

50 Scopus citations


Quantitatively evaluating land use performance and diagnosing its obstacle factor are an effective way to improve regional land use performance level. Through the comprehensive consideration on 4 subsystems: economic, social, ecological and management performance, an evaluation index system of regional land use performance was established. In the part of empirical research, firstly, the performance evaluation of Anhui Province land use in recent 15 years (2000-2014) was carried out through applying the entropy weight TOPSIS model, and the performances were classified into 4 grades based on close degree, which included low, medium, good and superior grade; secondly, the obstacle factor of Anhui land use performance was diagnosed through applying the obstacle degree model; at last, according to the performance evaluation result, subsystem and comprehensive performance change trend of Anhui Province land use in future 5 years (2015-2019) were predicted and analyzed by using GM (1, 1) model. The research results showed that: 1) The comprehensive performance of Anhui Province land use experienced such development process from low performance, medium, good to superior, and combined with the average annual growth rate of land use performance, the development process could be divided into 4 stages, i.e. low performance but high speed growth (2000-2004), medium performance but fast growth (2005-2009), good performance but slow growth (2010-2011) and superior performance and faster growth (2012-2014); 2) Four subsystem performance levels were basically improved year by year, but their change trends were different, economic and management performance presented linear increase trend, but social and ecological performance presented fluctuating upward trend; and in future 5 years, the annual growth rate of economic subsystem performance would be the fastest, social and management performance would be second, and ecological performance be the lowest; 3) The obstacle degree of economic performance was the maximum, followed by social, ecological and management performance. In 2000-2008, 3 indicators including industrial growth value in built-up area were the top three all the time, and people living standard and employment number per square kilometer occupied No. 4 or No. 5; in 2009-2012, the first 3 obstacle factors greatly changed, and fiscal revenue per square kilometer and people living standard became the major obstacle factors of land use performance; in 2013-2014, the top 5 obstacle factors had a great change, and social performance became the major subsystem of restricting land use performance. Improving people living standard, strengthening public infrastructure construction and exploring economical, intensive and efficient land use mode would be an important way to enhance land use performance of Anhui Province; according to the prediction results of GM (1, 1) model, social performance, ecological performance and management performance would have a huge promotion development space in the future. Anhui Province government should enhance land use economic performance and focus on the benignant and harmonious development among economic, society and environment aspects at the same time, and pay more attention to enhancing social performance, management performance, and especially ecological performance of land use. The research ideas and methods of the paper provide realistic basis for promoting regional land use performance.

Original languageEnglish (US)
Pages (from-to)243-253
Number of pages11
JournalNongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Issue number13
StatePublished - Jul 1 2016

All Science Journal Classification (ASJC) codes

  • General Agricultural and Biological Sciences
  • Mechanical Engineering


Dive into the research topics of 'Evaluation of regional land use performance based on entropy TOPSIS model and diagnosis of its obstacle factors'. Together they form a unique fingerprint.

Cite this