蓝绿空间景观格局对城市热岛的影响

城市热岛是城市环境中的典型问题。景观指数影响范围的空间异质性很少被理解。为了解决这个问题，拟采用多尺度地理加权回归模型(MGWR)来分析景观指数，归一化差值植被指数(NDVI)与地表温度(LST)之间的相互关系。结果显示，和普通最小二乘法回归和地理加权回归相比较，MGWR揭示了不同景观指数的空间影响尺度，具有更接近真实值的拟合效果。增加绿地和水体景观百分比及NDVI能够很好地缓解LST，其他景观指数则与LST的关系在不同的位置呈现正或负相关，需在特定位置进行优化才能有效地缓解LST。总的来说，形状简单且聚集分布的较大绿地斑块和形状复杂且较小的绿地斑块，以及在大多数情况下形状复杂、连通性强的水体景观更利于缓解LST。

Influence of Blue-green Spatial Landscape Pattern on Urban Heat Island

Urban heat island is a typical problem in urban environment. The spatial heterogeneity of influence ranges of landscape metrics is poorly understood. To solve the problem, this study used the multiscale geographically weighted regression model (MGWR) to analyze the relationship between landscape metrics, normalized difference vegetation index (NDVI) and land surface temperature (LST). The results showed that compared with the ordinary least squares regression and geographically weighted regression, MGWR revealed the spatial influence scale of different landscape metrics, and had a fitting effect closer to the true value. Increasing the percentage of green space and water landscape as well as NDVI could alleviate LST well, while the relationship between other landscape metrics and LST was positive or negative in different locations, and optimization in specific locations is needed to effectively alleviate LST. In general, larger green space patches with simple shapes and clustered distribution, as well as complex shapes and smaller green space patches and, in most cases, complex shaped and connected landscape of water bodies are more conducive to LST mitigation.