夏季城市景观格局对热场空间分布的影响——以武汉为例

城市热岛效应是城市生态环境状况的综合体现，探讨城市景观格局对热场空间分布的影响机制对于优化城市空间布局、提升城市生态环境质量有着重要意义。选用2016年7月23日Landsat8遥感影像进行武汉主城区景观类型划分和地表温度反演，从斑块、斑块类型、景观水平3个级别选取所有常见景观指数表征城市景观格局特征；按3 km×3 km大小的网格将武汉市主城区进行格网划分，构建格网内各景观格局指数与地表温度的关系，并进行主成分综合回归分析，探讨城市景观格局影响夏季热场空间分布的主要特征。结果表明：（1）76%的景观指数与地表温度的线性关系在0.01的置信水平是显著的，但各景观指数之间相关性较强，信息交叉重叠严重。（2）在所有景观指数中，对地表温度影响最大的依次是水体斑块类型面积（CA_W）、建设用地斑块类型所占景观面积比例（PLAND_C）、绿地类型核心斑块占景观面积比（CPLAND_G）、绿地类型相似度均值（SIMI_MN_G）及绿地类型邻近指标均值（PROX_MN_G）。（3）当其他因素不变时，格网内建设用地每增加10%，地表温度上升1.0℃；水体面积每增加10 hm，地表温度下降0.2℃；绿地核心面积比例每增加10%，可降温1.0℃；相似度均值和邻近度均值每增加0.1，可降温0.09和0.08℃。 关键词： 景观格局；热场；格网化；多因子；热岛效应

Impact of Urban Landscape Pattern on Spatial Distribution of Thermal Field in Summer：A Case Study of Wuhan

The phenomenon of urban heat island effect (UHIE) can synthetically indicate the environmental conditions of the city. Understanding the impact mechanism of urban landscape pattern on the spatial distribution of thermal field is significantly helpful to optimize the layout of urban space and then improve environmental quality. Landsat-8 remote sensing image acquired on July 23, 2016 was used to derive land surface temperature (LST) and classify landscape types in Wuhan urbanized area. Common landscape metrics were selected at patch level, patch type level and landscape level respectively to indicate landscape characteristics. Wuhan urbanized area was divided into 77 grids sized 3 km×3 km. In each grid, the related indexes and mean LST values were counted. Principal component regression equations between selected landscape metrics and LST were modeled to detect the influence mechanism of landscape pattern on UHIE. Results showed that: (1) About 76% of the selected indexes were significantly correlated with LST at 0.01 confidence level, and they also had strong correlation with each other. (2) The most efficient landscape indexes for LST variation were patch type area of Water body (CA_W), proportion of Construction Land in Landscape area (PLAND_C), proportion of Core Area in Greenbelt of Landscape area (CPLAND_G), Mean Similarity Index of Greenbelt (SIMI_MN_G) and Mean Proximity Index of Greenbelt (PROX_MN_G). (3) When the values of other factors remain unchanged in the grid, some results will present: Increase of pland-C at 10% will cause LST value increasing 1.0℃. Increase of CA_W at 10 hm will bring about LST value decreasing 0.2℃. Increase of CPLAND_G) at 10% will give rise to LST value decreasing 1.0℃. Increase of SIMI_MN_G and PROX_MN_G at 0.1 respectively will result in, LST value decreasing 0.09℃ and 0.08℃. Key words：landscape pattern; thermal field; gridding; multi-factors; urban heat island effect