街区蓝绿空间对热环境影响的空间异质性研究  

Research on the Spatial Heterogeneity of the Impact of Blue-Green Space Within Urban Block on Urban Thermal Environment

作　　者：石炜豪 曾穗平 艾合麦提·那麦提 SHI Weihao;ZENG Suiping;Aihemaiti NAMAITI(College of Architecture,Tianjin University;College of Architecture,Tianjin Chengjian University)

机构地区：[1]天津大学建筑学院 [2]天津城建大学建筑学院

出　　处：《风景园林》2024年第10期98-105,共8页Landscape Architecture

基　　金：国家自然科学基金面上项目“基于大气安全阈值约束与控污物理环境调适的京津冀产-城低污布局理论研究”(编号52078320);国家自然科学基金面上项目“基于智慧与韧性适灾机理的沿海河口城市雨潮组合风险防控规划理论”(编号52378065)。

摘　　要：【目的】蓝绿空间对热环境优化的积极效应已获得广泛关注,但现有研究对蓝绿空间指标影响热环境作用的空间异质性探究不深入,挖掘多维度蓝绿空间对热环境的影响有利于气候适应性城市建设。【方法】将蓝绿空间破碎化、热环境恶化的天津市中心城区作为研究区域,以地表温度作为热环境表征指标,借助Fragstats 4.2与Guidos Toolbox 2.9软件计算蓝绿空间规模、形态、布局3个方面的表征指标,引入多尺度地理加权回归(multiscale geographically weighted regression, MGWR)模型开展统计分析。【结果】1)天津市中心城区蓝绿空间分布呈现“四廊多点”的特征,而地表温度分布则呈现明显的“中心高外围低”的特征;2)各蓝绿空间指标对热环境的作用尺度存在一定分异,平均形状指数、边缘布局占比的作用尺度较小,存在较大的空间异质性;绿色空间占比与核心布局占比的作用尺度较大,影响程度在空间上变化平缓;3)各蓝绿空间指标中,绿色空间占比、核心布局占比、斑块内聚度指数(COHESION)对热环境具有显著负向作用,分支布局占比和边缘布局占比对热环境有显著正向作用。【结论】全面挖掘了街区蓝绿空间中影响热环境的指标,探索了它们对热环境的多尺度空间异质性影响并提出蓝绿空间调控建议,为高密度城区的气候适应及城市街区精细化管理提供理论支撑。[Objective]Blue-green space is considered as an important ecological facility to optimize the thermal environment,whose positive effects on thermal environment optimization have gained widespread attention.Previous research has paid less attention to the construction of comprehensive indicators such as the scale,shape and layout of blue-green space,the spatial heterogeneity of the impact of blue-green space on the thermal environment,and the research unit of block,which makes it difficult to implement grounded optimization strategy for blue-green space as a response to thermal mitigation regulation.Thoroughly exploring the multi-dimensional impact of blue-green space on the thermal environment is beneficial for climate-adaptive urban development.[Methods]This research takes the central urban area of Tianjin as the research area.The intense development and high-density construction in Tianjin have led to the fragmentation of blue-green space and the continuous deterioration of the thermal environment,making central Tianjin an area in urgent need of ecological transformation.Based on Landsat 8 remote sensing imagery and ENVI for land surface temperature(LST)inversion,the average of multiple datasets is utilized as the indicator to characterize the thermal environment.High-precision identification of blue-green space at a 2 m resolution is achieved through Google Earth images and eCognition 8.9 software.On this basis,combined with OpenStreetMap road data,over 300 blocks are delineated as the basic research units.Integrating landscape ecology and morphological analysis(morphological spatial pattern analysis,MSPA)based on ArcGIS Pro 3.0,Fragstats 4.2,and Guidos Toolbox 2.9 software,multi-dimensional evaluation indices of blue-green space at the block scale are calculated from the perspectives of“scale−shape−layout”.Finally,a multiscale geographically weighted regression(MGWR)model is introduced to conduct the statistical analysis.[Results]1)The results show that the blue-green space in the central urban area o

关 键 词：城市更新 绿地规划 街区蓝绿空间 热环境优化 地表温度 多尺度地理加权回归模型 

分 类 号：TU985.12[建筑科学—城市规划与设计]