Spatial non-stationarity in the relationships between land cover and surface temperature in an urban heat island and its impacts on thermally sensitive populations
Spatial non-stationarity in the relationships between land cover and surface temperature in an urban heat island and its impacts on thermally sensitive populations
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DOI：
10.1016/j.landurbplan.2012.05.016
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发表时间：
2012-08
影响因子：
9.1
通讯作者：
Yuan-Fong Su;G. Foody;K. Cheng
中科院分区：
文献类型：
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作者：
Yuan-Fong Su;G. Foody;K. Cheng
过去的研究重点关注土地覆盖和城市温度之间的关系，通常假设平稳性并使用传统的（全球）回归分析。本研究以桃园地区为例，利用地理加权回归法，探讨土地覆被类型（建筑物、水、水田及其他植被）与地表温度间的空间稳定性。通过采用GWR方法，观察到这些关系的显着空间非平稳性，这些关系的强度显着高于传统的回归分析。这些差异有很大的影响。如果使用回归模型来估计桃园的城市热岛强度，则全球和GWR模型分别为2.63°C和3.17°C。这一结果表明，全球模型低估了城市热岛，因此，这增加了低估城市人口健康不良和不适风险的可能性。从GWR分析得出的映射参数为规划温度缓解和适应策略提供了有用的信息，特别是对于对温度特别敏感的非常年轻和老年人。
Past studies focused on the relationships between land cover and urban temperature have commonly assumed stationarity and used conventional (global) regression analysis. In this study, geographically weighted regression (GWR) was used to test the spatial stationarity of the relationships between a set of land cover types (built-up, water, paddy field, and other vegetation) and the surface temperature in TaoYuan, Taiwan. By adopting the GWR approach, significant spatial non-stationarity of these relationships was observed and the strength of these relationships was markedly higher than from a conventional regression analysis. The differences have large impacts. If the regression models were used to derive an estimate of the urban heat island intensity for TaoYuan this would equate to 2.63°C and 3.17°C for the global and GWR models, respectively. This result showed that the urban heat island was underestimated by global model and this, therefore, increased potential to underestimate the risk of ill-health and discomfort for urban populations. The mapped parameters derived from GWR analyses provided useful information for planning temperature mitigation and adaptation strategies especially for the very young and elderly that are particularly sensitive to temperature.