武汉市都市发展区地表温度季节性空间分布与驱动力分析  

Seasonal-Spatial Distribution and Driving Forces of Land Surface Temperature in the Urban Development Area of Wuhan

作　　者：葛静茹 王海军[1,2] 贺三维[3] 黄鑫鑫[1] 洪松[1] GE Jing-ru;WANG Hai-jun;HE San-wei;HUANG Xin-xin;HONG Song(School of Resources and Environmental Sciences,Wuhan University,Wuhan 430079,China;Key Laboratory of Geographic Information Systems,Ministry of Education,Wuhan University,Wuhan 430079,China;School of Public Administration,Zhongnan University of Economic and Law,Wuhan 430073,China)

机构地区：[1]武汉大学资源与环境科学学院,湖北武汉430079 [2]武汉大学地理信息系统教育部重点实验室,湖北武汉430079 [3]中南财经政法大学公共管理学院,湖北武汉430073

出　　处：《长江流域资源与环境》2021年第2期351-360,共10页Resources and Environment in the Yangtze Basin

基　　金：国家自然科学基金(41571384)。

摘　　要：基于2015年武汉市都市发展区30 m空间分辨率的Landsat 8遥感影像反演近地表温度(LST),运用地统计学、地理加权回归(GWR)等方法,分析都市发展区、生态绿楔以及主城区四季LST时空分布规律和各驱动因子的作用机制,以期为更全面、科学地规划城市发展空间布局和缓解热岛效应提供借鉴。结果表明:(1)与单一的普通最小二乘回归(OLS)相比,线性逐步回归(LSR)可以寻找最优的多驱动因子组合模型,与LSR拟合的结果相比,GWR模型R2值提高了0.04~0.09,且AIC值均明显减小;(2)LST存在空间聚集关系,"高-高"聚集主要发生在主城区、新型城镇发展区、主要交通干线沿线等更容易造成高温聚集的人工表面,其中夏季"高-高"聚集网格数最多且占比最大,而"低-低"聚集四季均主要发生在各大湖泊水系;(3)绿楔生态用地降温幅度各异,春季降温幅度不明显,夏季降温幅度最显著,各绿楔生态用地降温均超过2℃,且在一定范围内,LST随着与绿楔距离增大而升高,达到一定距离时,会随着与绿楔距离增加而趋于平缓或呈下降趋势;(4)与前人研究相比,景观格局对LST变化的解释程度整体较低,其原因可能是快速城市化导致人工表面积增加,相应的人工绿地也将增加,使得城市景观格局更加零散,导致LST受多种相互作用因素的影响;(5)影响四季LST的驱动因子空间差异较大,夏季土地覆盖和景观格局与冬季土地覆盖、景观格局和人为活动的回归系数均为正值,说明高温或低温条件下这些驱动因子对全域升温作用明显。Based on Landsat 8 remote sensing images with a 30 m spatial resolution acquired in 2015 the Urban Development Area of Wuhan, this paper retrieved Land Surface Temperature(LST)using atmospheric correction method. This study sought to analyze the spatial-temporal distribution of LST in urban development area, ecological green wedge and main urban area, so as to provide reference for the planning of urban spatial distribution and the mitigation effect of Urban Heat Island(UHI)more comprehensively and scientifically. The results show that:(1)Compared with ordinary least squares regression(OLS), linear stepwise regression(LSR)can find the multiple driving factors combination model. Compared with the results of LSR fitting, the R^2 value of GWR model is improved by 0.04~0.09.(2)The "high-high" cluster occurred mainly in the main urban area, the new town development area and the main traffic line covered with artificial surface, which was more prone to high temperature cluster. Furthermore, the "high-high" cluster had the largest number and proportion in summer, while the "low-low" cluster occurred mainly in the major lake water systems in four seasons.(3)The ecological land of the ecological green wedge had different cooling range. The cooling range was not obvious in spring, but was most obvious in summer. The temperature drop of each green wedge was more than 2℃. In a certain buffer range, LST increased with the distance from green wedge.When the buffer range reached a certain distance, LST tended to be gentle or downward with the increase of the distance from the green wedge.(4)Compared with previous studies, the explanation of LST change in landscape pattern is generally lower, which may be due to the increase of artificial surface area caused by rapid urbanization and the increase of artificial green space. So it makes the urban landscape pattern more fragmented and LST affected by a variety of interaction factors.(5)The driving factors of LST in four seasons were quite different in space. The regression coeffi

关 键 词：地表温度 季节性 空间分布 驱动力 生态绿楔 

分 类 号：X87[环境科学与工程—环境工程]