Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling
Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling
复制标题
DOI：
10.1016/j.uclim.2019.100459
复制
发表时间：
2019-06-01
期刊：
影响因子：
6.4
通讯作者：
Niyogi, Dev
中科院分区：
文献类型：
--
作者：
Ching, Jason;Aliaga, Dan;Niyogi, Dev
WUDAPT（世界城市数据库和访问门户工具）项目的目标是为世界各地的城市获取关于城市形态和功能的一致信息，以支持城市天气、气候、水文和空气质量建模。这些数据作为城市冠层参数（UCPs）提供，用于天气、气候和空气质量模式，以模拟城市表面对上覆大气的影响。信息以不同的细节级别（LOD）存储。LOD越高，提供的空间精度越高。在最低LOD下，提供了具有标称UCP范围的局部气候区（LCZ）（100米或更高）。为了描述在不同的城市尺度上具有很大特异性的城市中存在的空间异质性，我们引入了数字合成城市（DSC）工具，以在任何期望的尺度上生成符合WUDAPT目标的UCP。整个城市景观的3D建筑物和道路元素基于现成的数据进行模拟。与真实世界的城市数据进行比较非常令人鼓舞。它是定制的（C-DSC），根据建筑类型、建筑特征、建筑材料以及绿色和透水表面的分布的独特类型、变化和空间分布，融入每个城市独特的建筑形态。C-DSC使用众包方法，并在世界各地的城市测试台内进行抽样。UCP数据可以从选定网格尺寸的合成图像计算并存储，使得编码串为各个网格单元提供UCP值。
The WUDAPT (World Urban Database and Access Portal Tools project goal is to capture consistent information on urban form and function for cities worldwide that can support urban weather, climate, hydrology and air quality modeling. These data are provided as urban canopy parameters (UCPs) as used by weather, climate and air quality models to simulate the effects of urban surfaces on the overlying atmosphere. Information is stored with different levels of detail (LOD). With higher LOD greater spatial precision is provided. At the lowest LOD, Local Climate Zones (LCZ) with nominal UCP ranges is provided (order 100m or more). To describe the spatial heterogeneity present in cities with great specificity at different urban scales we introduce the Digital Synthetic City (DSC) tool to generate UCPs at any desired scale meeting the fit-for-purpose goal of WUDAPT. 3D building and road elements of entire city landscapes are simulated based on readily available data. Comparisons with real-world urban data are very encouraging. It is customized (C-DSC) to incorporate each city's unique building morphologies based on unique types, variations and spatial distribution of building typologies, architecture features, construction materials and distribution of green and pervious surfaces. The C-DSC uses crowdsourcing methods and sampling within city Testbeds from around the world. UCP data can be computed from synthetic images at selected grid sizes and stored such that the coded string provides UCP values for individual grid cells.