Investigating the influence of three-dimensional building configuration on urban pluvial flooding using random forest algorithm
Investigating the influence of three-dimensional building configuration on urban pluvial flooding using random forest algorithm
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利用随机森林算法研究三维建筑结构对城市雨洪的影响
DOI：
10.1016/j.envres.2020.110438
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发表时间：
2021
影响因子：
8.3
通讯作者：
Peiting He
中科院分区：
文献类型：
--
作者：
Jinyao Lin;Xiaoyu He;Siyan Lu;Danyuan Liu;Peiting He
城市雨水泛滥已成为对环境条件和人类生活的严重威胁。确定其主要驱动因素对于减轻洪水风险至关重要。虽然以往的研究表明，雨洪是由自然因素（如地形）和人为因素（如土地覆盖条件）共同引起的，但对三维建筑形态对雨洪的潜在影响的研究却很少。为了阐明这一主题，我们首先使用Pearson相关分析分析了一个高度城市化城市中洪水热点密度与不同潜在驱动因素之间的线性关系。接下来，我们设计了两个随机的基于森林的模型来量化各种建筑指标的重要性。第一个模型只考虑常见的驱动因素，而第二个模型还包括不同类型的构建指标。结果表明，建筑物密度、建筑物拥塞程度和建筑物覆盖率对雨洪的发生有较大影响。例如，增强模型的根相对平方误差（28.36%）低于基线模型的根相对平方误差（32.58%）。本文的研究结果有望从三维城市规划的角度为缓解洪积洪水风险提供实践指导。此外，该方法框架可以进一步应用于许多其他地区的洪水分析。
Urban pluvial flooding has emerged as a serious threat to environmental conditions and human lives. Identifying its key drivers is crucial for the mitigation of flood risks. Although previous studies have demonstrated that pluvial flooding is caused by both natural (e.g., topography) and anthropogenic factors (e.g., land cover condition), much less effort has been devoted to investigating the potential influence of three-dimensional building configuration on pluvial flooding. To shed some light on this topic, we first analyzed the linear relationship between the density of flooding hotspots and different potential drivers in a highly-urbanized city using Pearson correlation analysis. Next, we designed two random forest-based models to quantify the importance of various building metrics. The first model considers only common drivers, while the second one also includes different types of building metrics. Results indicate that the density of buildings, building congestion degree, and building coverage ratio have exerted considerable influence on the occurrence of pluvial flooding. For example, the root relative squared error of our enhanced model (28.36%) is lower than that of the baseline model (32.58%). Our findings are expected to provide practical guidance for the mitigation of pluvial flood risks from the perspective of three-dimensional urban planning. Moreover, this methodological framework can be further applied to the analysis of flooding in many other regions.