基于地理加权回归模型的武汉城市圈生态用地时空演变及影响因素

doi:10.13287/j.1001-9332.202003.016

应用生态学报 ›› 2020, Vol. 31 ›› Issue (3): 987-998.doi: 10.13287/j.1001-9332.202003.016

基于地理加权回归模型的武汉城市圈生态用地时空演变及影响因素

刘彦文^1,2, 刘成武³, 何宗宜^1*, 周霞², 韩冰华², 郝汉舟²

¹武汉大学资源与环境科学学院, 武汉 430079;
²湖北科技学院资源环境科学与工程学院, 湖北咸宁 437100;
³中南民族大学公共管理学院, 武汉 430074

收稿日期:2019-10-21 出版日期:2020-03-15 发布日期:2020-03-15
通讯作者: E-mail: zongyihe@tom.com
作者简介:刘彦文, 男, 1979年生, 博士研究生。主要从事3S技术及其土地应用研究。E-mail: lhgyanzi@whu.edu.cn
基金资助:
本文由国家社会科学基金项目(14BGL156)和湖北省哲学社会科学研究项目(19Q176)资助

Spatial-temporal evolution of ecological land and influence factors in Wuhan urban agglome-ration based on geographically weighted regression model

LIU Yan-wen^1,2, LIU Cheng-wu³, HE Zong-yi^1*, ZHOU Xia², HAN Bing-hua², HAO Han-zhou²

¹School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China;
²School of Resources and Environment Science and Engineering, Hubei University of Science and Technology, Xianning 437100, Hubei, China;
³School of Public Management, South-Central University for Nationalities, Wuhan 430074, China

Received:2019-10-21 Online:2020-03-15 Published:2020-03-15
Contact: E-mail: zongyihe@tom.com
Supported by:
This work was supported by the National Social Science Foundation of China (14BGL156) and the Philosophy and Social Science Research Project of Hubei Province (19Q176)

摘要/Abstract

摘要： 生态用地对城市圈可持续发展至关重要。本研究以武汉城市圈32个研究单元生态用地为对象,采用土地利用转移矩阵、探索性回归分析和地理加权回归模型(GWR),首先利用遥感影像解译成果对2000—2005、2005—2010和2010—2015年各个单元生态用地的时空演变进行统计,然后利用公司企业、生活服务等点位及数量大数据完善传统影响因素指标体系,并进行探索性回归分析,精选最优回归模型,最后基于GWR模型对不同时期影响因素及空间分异规律进行分析。结果表明: 2000—2015年,城市圈内生态用地非生态转化呈现先升后降的倒“U”形变化规律,空间上呈现由点到面的扩张趋势;城市圈内共有8.4%的土地利用类型发生了转化,其中,耕地、林地、草地、水体和未利用地向非生态用地转型量占41.9%;空间格局由武汉中心城区逐渐向市级次中心、县级城镇周边扩展。探索性回归分析3期的通过模型数为326个,对所有模型进行GWR和普通最小二乘法(OLS)回归比较分析,3期最优模型的调整R²分别为0.83、0.91和0.76,前者较后者提高了0.02、0.03和0.02,AICc值分别减小2.88、3.42和0.83。GWR模型结果表明,武汉城市圈内生态用地转化影响因素的空间分异明显,影响模式在空间上以不同方向的逐渐过渡为主,兼有“V”形分布等其他模式。空间因素影响效果显著,空间数据潜在信息增强了城市圈内生态用地演化的解释力度。

Abstract: Ecological land is essential to sustainable development of urban agglomeration. Based on the results of remote sensing image interpretation, we analyzed the spatial-temporal evolution of ecological land in 32 research units of ecological land in Wuhan urban agglomeration in 2000-2005, 2005-2010 and 2010-2015, using the land use transition matrix, exploratory regression analysis, the ordinary least squares (OLS) model, and geographically weighted regression (GWR) model. Then, the best regression model was selected after perfecting the traditional index system of influencing factors by data of the location and quantitative information of companies, enterprises and life services, etc., and conducting exploratory regression analysis. Finally, we analyzed the influencing factors and spatial differentiation rules of different research periods with GWR model. The results showed that, from 2000 to 2015, the amount of transition from ecological land use to non-ecological land use in the urban agglomeration showed an inverted U-shaped change pattern, and the space showing the expanding trend from point to surface. Land use patterns of 8.4% area had changed in the urban agglomeration, among which the conversion of cultivated land, forest land, grassland, water body and unused land to non-ecological land accounted for 41.9% of the total area. The spatial pattern gradually expanded from the central urban area of Wuhan to the periphery of the municipal sub-center and county-level towns. The total number of passing models in the three stages of exploratory regression analysis was 326. The GWR and OLS regression were used for comparative analysis of all models. The adjusted R² in the three stages of selected models were 0.83, 0.91 and 0.76, respectively. The former improved by 0.02, 0.03 and 0.02, and the AICc decreased by 2.88, 3.42 and 0.83, respectively. The results of GWR model showed substantially spatial differentiation of influencing factors of ecological land evolution in Wuhan urban agglomeration, and that the influence patterns was dominated by gradual transition in different directions in space, with other patterns such as “V” distribution. The effects of spatial factors were significant. The potential information of spatial data enhanced the interpretation of ecological land evolution within the urban agglomeration.

刘彦文, 刘成武, 何宗宜, 周霞, 韩冰华, 郝汉舟. 基于地理加权回归模型的武汉城市圈生态用地时空演变及影响因素[J]. 应用生态学报, 2020, 31(3): 987-998.

LIU Yan-wen, LIU Cheng-wu, HE Zong-yi, ZHOU Xia, HAN Bing-hua, HAO Han-zhou. Spatial-temporal evolution of ecological land and influence factors in Wuhan urban agglome-ration based on geographically weighted regression model[J]. Chinese Journal of Applied Ecology, 2020, 31(3): 987-998.

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基于地理加权回归模型的武汉城市圈生态用地时空演变及影响因素

Spatial-temporal evolution of ecological land and influence factors in Wuhan urban agglome-ration based on geographically weighted regression model

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