Currently, more than half of the world’s population lives in cities, which leads to major changes in land use and land surface temperature (LST). The associated urban heat island (UHI) effects have multiple impacts on energy consumption and human health. A better understanding of how different land covers affect LST is necessary for mitigating adverse impacts, and supporting urban planning and public health management. This study explores a distance-based, a grid-based and a point-based analysis to investigate the influence of impervious surfaces, green area and waterbodies on LST, from large (distance and grid based analysis with 400 m grids) to smaller (point based analysis with 30 m grids) scale in the two mid-latitude cities of Paris and Geneva. The results at large scale confirm that the highest LST was observed in the city centers. A significantly positive correlation was observed between LST and impervious surface density. An anticorrelation between LST and green area density was observed in Paris. The spatial lag model was used to explore the spatial correlation among LST, NDBI, NDVI and MNDWI on a smaller scale. Inverse correlations between LST and NDVI and MNDWI, respectively, were observed. We conclude that waterbodies display the greatest mitigation on LST and UHI effects both on the large and smaller scale. Green areas play an important role in cooling effects on the smaller scale. An increase of evenly distributed green area and waterbodies in urban areas is suggested to lower LST and mitigate UHI effects.

中文翻译：

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市区土地覆盖与地表温度的时空关系：以日内瓦和巴黎为例

当前，全球一半以上的人口居住在城市，这导致土地使用和地表温度（LST）发生重大变化。相关的城市热岛效应（UHI）对能源消耗和人类健康具有多重影响。为了减轻不利影响，支持城市规划和公共卫生管理，有必要更好地了解不同土地面积如何影响LST。这项研究探索了基于距离，基于网格和基于点的分析，以研究不透水的表面，绿色区域和水体对LST的影响，从较大的（基于距离和基于400 m网格的网格分析）到较小的（点巴黎和日内瓦这两个中纬度城市的30 m网格比例分析）。大规模的结果证实，在市中心地区观察到最高的LST。在LST和不透水表面密度之间观察到显着正相关。在巴黎观察到LST与绿地密度之间存在反相关关系。利用空间滞后模型探索了LST，NDBI，NDVI和MNDWI之间较小的空间相关性。分别观察到LST与NDVI和MNDWI之间成反比。我们得出的结论是，无论规模大小，水体对LST和UHI的影响最大。绿色区域在较小规模的冷却效果中起着重要作用。建议增加城市地区绿地和水体的平均分布，以降低LST并减轻UHI的影响。利用空间滞后模型探索了LST，NDBI，NDVI和MNDWI之间较小的空间相关性。分别观察到LST与NDVI和MNDWI之间成反比。我们得出的结论是，无论规模大小，水体对LST和UHI的影响最大。绿色区域在较小规模的冷却效果中起着重要作用。建议增加城市地区绿地和水体的平均分布，以降低LST并减轻UHI的影响。利用空间滞后模型探索了LST，NDBI，NDVI和MNDWI之间较小的空间相关性。分别观察到LST与NDVI和MNDWI之间成反比。我们得出的结论是，无论规模大小，水体对LST和UHI的影响最大。绿色区域在较小规模的冷却效果中起着重要作用。建议增加城市地区绿地和水体的平均分布，以降低LST并减轻UHI的影响。绿色区域在较小规模的冷却效果中起着重要作用。建议增加城市地区绿地和水体的平均分布，以降低LST并减轻UHI的影响。绿色区域在较小规模的冷却效果中起着重要作用。建议增加城市地区绿地和水体的平均分布，以降低LST并减轻UHI的影响。