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王海军,刘艺明,张彬,徐姗,贾克敬,洪松.基于Logistic-GTWR模型的武汉城市圈城镇用地扩展驱动力分析[J].农业工程学报,2018,34(19):248-257.DOI:10.11975/j.issn.1002-6819.2018.19.032
基于Logistic-GTWR模型的武汉城市圈城镇用地扩展驱动力分析
投稿时间:2018-04-02  修订日期:2018-08-08
中文关键词:  土地利用  模型  城市扩展  驱动力  逻辑斯蒂  时空地理加权回归  武汉城市圈
基金项目:国家自然科学基金面上项目(41571384);国土资源部土地资源调查评价项目(DCPJ161207-01);国家基础科学人才培养基金项目(J1103409);国家自然科学基金重点项目(71433008)
作者单位
王海军 1. 武汉大学资源与环境科学学院武汉 4300792. 武汉大学地理信息系统教育部重点实验室武汉 430079 
刘艺明 1. 武汉大学资源与环境科学学院武汉 430079 
张彬 1. 武汉大学资源与环境科学学院武汉 430079 
徐姗 3. 中国科学院地理科学与资源研究所北京 100101 
贾克敬 4. 中国土地勘测规划院北京 100035 
洪松 1. 武汉大学资源与环境科学学院武汉 430079 
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中文摘要:该文以武汉城市圈为例,利用1995年、2000年、2005年、2010年、2015年5期土地利用数据、社会经济因子、邻域因子和自然因子,构建耦合空间异质性和时间非平稳性的Logistic-GTWR(逻辑斯蒂-时空地理加权回归)模型,挖掘武汉城市圈城镇用地扩展驱动力及其时空分异格局。结果表明:1)耦合空间异质性和时间非平稳性的Logistic-GTWR模型比全局Logistic回归模型和Logistic-GWR(逻辑斯蒂-地理加权回归)模型具有更好的拟合效果,验证了Logistic-GTWR模型在城镇用地扩展驱动力分析研究中的适用性。2)武汉城市圈城镇用地扩展的不同影响因子系数时空分异格局各不相同,人口因子高值分布区围绕武汉市先收缩后扩散并逐渐稳定,最终形成绕武汉城市圈中部沿线周边环状分布格局;地均GDP因子高值分布区先向西部转移,后逐渐趋于均衡,最终形成绕武汉、麻城和崇阳县周边集聚分布的空间格局。武汉市极化作用占据主导地位,且影响范围不断扩大。3)人口和经济是20年间武汉城市圈城镇扩展的核心驱动因子,且影响力呈逐年上升趋势;国道、高速和省道影响力整体呈略微升高态势。4)武汉城市圈中部及东部城市多为人口、经济核心驱动型城市,高程影响在武汉市发展中逐渐凸显;西部城市主要受高程限制,并以交通及经济驱动为主,东西差异显著; 但西部城市1995年以来人口和经济的作用强度逐步增加。人口因子作用强度在咸宁和黄冈呈逐渐上升趋势,经济因子作用强度在武汉、孝感、仙桃、天门、潜江和黄冈逐年上升。
Wang Haijun,Liu Yiming,Zhang Bin,Xu Shan,Jia Kejing,Hong Song.Analysis of driving forces of urban land expansion in Wuhan metropolitan area based on Logistic-GTWR model[J].Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2018,34(19):248-257.DOI:10.11975/j.issn.1002-6819.2018.19.032
Analysis of driving forces of urban land expansion in Wuhan metropolitan area based on Logistic-GTWR model
Author NameAffiliation
Wang Haijun 1. School of Resource and Environmental Science,Wuhan University,Wuhan 430079, China
2. Key Laboratory of Geographic Information Systems, Ministry of Education, Wuhan University, Wuhan 430079, China
 
Liu Yiming 1. School of Resource and Environmental Science,Wuhan University,Wuhan 430079, China
 
Zhang Bin 1. School of Resource and Environmental Science,Wuhan University,Wuhan 430079, China
 
Xu Shan 3. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
 
Jia Kejing 4. China Land Surveying and Planning Institute, Beijing 100029, China 
Hong Song 1. School of Resource and Environmental Science,Wuhan University,Wuhan 430079, China
 
Key words:land use  models  urban expansion  driving forces  logistic  geographically and temporally weighted regression  Wuhan metropolitan area
Abstract: Under the background that the country pushes forward the new-type urbanization, spatial planning and urban agglomeration planning, it is of great significance to scientifically cognize the driving forces mechanism of urban land expansion for the urban agglomeration, which is important for the sustainable development of urban agglomeration land use and planning. Taking the Wuhan metropolitan area as an example, the paper uses the land use data, socio-economic factors, neighborhood factors and natural factors in 1995, 2000, 2005, 2010 and 2015 to construct the Logistic-GTWR (Logistic - geographically and temporally weighted regression) model, which couples the spatial heterogeneity and temporal non-stationarity. The model is used to explore the driving forces and its spatio-temporal differentiation pattern of urban land expansion in Wuhan metropolitan area. The results highlight that: 1) The Logistic-GTWR model with coupling spatial heterogeneity and temporal non-stationarity has a better performance than the global logistic regression model and the Logistic-GWR (Logistic-Geographically Weighted Regression) model which only considers the spatial heterogeneity, verifying the applicability of Logistic-GTWR model in driving force analysis of urban land expansion. 2) There are significant disparities on the spatio-temporal patterns for various driving forces of urban expansion in Wuhan metropolitan area. For example, the distribution area of high values for population factor shrank, spread and then stabilized around Wuhan, finally forming a circular distribution pattern around the central part of Wuhan metropolitan area as time went by. The distribution area of high value for per capita GDP (gross domestic product) firstly transferred to the west, then gradually balanced, and finally concentrated around Wuhan, Macheng and Chongyang. The effect of polarization plays a dominant role in the process of urbanization in Wuhan, and its influence range is constantly expanding. The effect of rent seeking is apparent. 3) Population and economy are the core driving forces of urban expansion in Wuhan metropolitan area in 20 years and the influence of the 2 factors has been increasing year by year. The influence of the national highways, highways and provincial roads has been slightly increased. 4) The central and eastern cities are mostly such cities where population and economic factors are the core driving forces. The influence of elevation is gradually prominent in the development of Wuhan on account of a rapid development and decreasing land source. The cities in the west are mainly restricted by elevation and driven by traffic, where the differences between the east and the west are obvious. However, the intensities of the population and economy in western cities have gradually increased since 1995. The effects of population and economy on western cities have been an uptrend since 1995. Similarly, the intensity of population has been gradually increasing in Xianning and Huanggang. In Wuhan, Xiaogan, Xiantao, Tianmen and Qianjiang, economic factor has an increasing trend over year. This research provides a model that couples the spatial heterogeneity and temporal non-stationarity, depicting more detailed spatio-temporal differentiation characteristics of driving factors, which is beneficial to the meticulous?management of land resource.
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