基于城市大数据的热场格局形成机制及主导因素的多尺度研究

A multi-scale study on the formation mechanism and main controlling factors of urban thermal field based on urban big data

城市景观的组成与结构及人类活动强度是城市热场格局形成的重要影响因素,但不同要素在城市热场形成机制中的相对重要性尚不清楚.本研究以江苏省宜兴市为例,综合运用遥感解译、外业测绘和编程技术获取城市地表温度、生态基础设施(植被、水体盖度)、建筑容积和百度用户兴趣点(POI)数据,运用Pearson相关分析、回归分析和相对权重分析的方法定量研究了500、1000和2000 m:尺度上生态基础设施、建筑容积和POI密度与地表温度的关联关系及相对重要性.结果表明生态基础设施具有显著的降温效应,建筑容积和POI密度与地表温度呈显著正相关关系.在城市热场的影响因子中,生态基础设施的相对权重在各尺度均最高(24.3%～43.8%),其次为建筑容积(20.7%～22.6%)和POI密度(13.7%～21.7%).本研究有助于定量理解城市热场形成的多种驱动因子的相对贡献,并可为制定缓解热岛效应的措施提供重要参考.

The composition and structure of urban landscape and human activity intensity are key factors shaping urban thermal fields, whereas the relative importance of influencing factors for urban thermal distribution remains unclear. We carried out a case study in Yixing City. Land surface temperature（LST）, ecological infrastructure（including vegetation and water cover）, building volume and point of interest data were extracted from the RS interpretation, field mapping and programming technique. Using Pearson correlation analysis, univariete regression analysis, multiple regression analysis and relative weight analysis, we quantitatively analyzed the relationships between urban land surface temperature to ecological infrastructure, building volume, POI density at multiple scales（500, 1000, 2000 m） as well as their relative importance. The results showed that ecological infrastructure had a significant cooling effect, and the building volume and POI density were positively correlated with LST. Among the influence factors of urban heat field, ecological infrastructure had the highest relative weight（21.3%-43.8%）, followed by building volume（20.7%-22.6%）and POI density（13.7%-21.7%）. Our results would help to understand the relative importance of factors driving urban thermal field and offer important reference for taking mitigation measures to alleviate urban heat island effect.