A novel approach for urbanization level evaluation based on information entropy principle: A case of Beijing
A novel approach for urbanization level evaluation based on information entropy principle: A case of Beijing
复制标题
基于信息熵原理的城镇化水平评价新方法——以北京市为例
DOI:
10.1016/j.physa.2015.02.039
复制
发表时间:
2015-07
期刊:
影响因子:
--
通讯作者:
Lihe Chai
中科院分区:
文献类型:
--
作者:
Jingjing Zhao;Lihe Chai
Urbanization level evaluation (ULE) is an important scientific basis for guiding urban managers to make decisions. By introducing information entropy to describe the interactions between all indicators, a holistic structural parameter ξ, its dynamic equation and self-organizing feature map simulation technique are derived to describe the structural evolution of the indicator network. In this way, a novel ULE model is universally proposed. Then, we use the model to assess the evolutionary urbanization level of Beijing during 2005–2012. We calculate structural parameter ξ values of the indicator network with 35 microscopic indicators as nodes. The results show Beijing’s urbanization level has ever kept increasing. Large increase of ξ values in 2008 and 2012 represented significant improvements of urbanization level in these two years, while a rapid adjustment of urbanization development occurred in 2010. Five meso-scopic subsystems as urban construction, economic development, social development, ecological environment and urban–rural development affected Beijing’s urbanization level in different ways. The radar chart of the model shows the contributions of economic development and urban–rural development to Beijing’s urbanization changed most, while poor coordination of urban–rural development largely existed. By showing Beijing’s ULE based on two analytical ways, we further discuss the objectivity and flexibility in choosing indicator network. Finally, beyond the application case, we discuss the universality and superiority of the new model.
登录
查看更多内容
影响因子:
2.5
作者:
Wang, Yang;Liu, Jin-Long;Li, Shuang-Cheng;Zhu, Yu-Kun
通讯作者:
Zhu, Yu-Kun
影响因子:
4.7
作者:
Wu Qian
通讯作者:
Wu Qian
影响因子:
1.7
作者:
Xiao-lin Shao;L. Chai
通讯作者:
Xiao-lin Shao;L. Chai
DOI:
--
发表时间:
2008
期刊:
--
影响因子:
--
作者:
Cai Yun-long
通讯作者:
Cai Yun-long
影响因子:
3.4
作者:
Shangguang Yang;M. Wang;Chunlan Wang
通讯作者:
Shangguang Yang;M. Wang;Chunlan Wang