The high share of impermeable surfaces in cities modifies the terrain characteristics that facilitate natural water flow and balance. The street network, an impervious surface on its own, is also the impetus for developing other impervious surfaces by facilitating access. The purpose of this work is to assess the interconnectedness between the underlying structural lines of the terrain and the street network for making informed decisions on locating green infrastructure to maintain water balance. For this purpose, the work measures the spatio-structural similarity between the co-located networks, assesses the variation of the measure with city size and relation to an indicator of water balance. Cross-sectional analysis is performed across a large sample of cities of varying sizes to extract generalized patterns of spatial structure and variations to size. The larger cities have low index values of spatio-structural similarity ranging between –0.2 and 0.2. The low index values for larger cities relate to the emergence of small-world properties in large street networks for functional efficiency and large street networks' web-like shape. Next, the paper identifies two zones based on the interconnectedness of the roads and the terrain. The spatial extent of a zone based on points where the arterial road intersects higher orders of drainage channels and ridgelines is associated with the number of above-normal wet conditions (SPEI ≥ 2.0) with the r-value of –0.30 at a p-value of 0.05. In summary, spatial statistics on spatial network data are helpful to extract trends inherent in the multi-layered network structure of cities to provide informed solutions. The policymakers and planners can use the spatial co-location patterns between street and terrain to make data-driven decisions to locate interventions for a nature-based resilient city.

城市中高比例的不透水表面改变了促进自然水流和平衡的地形特征。街道网络本身就是一个不透水的表面，也是通过促进访问来开发其他不透水表面的动力。这项工作的目的是评估地形的底层结构线与街道网络之间的相互联系，以便就定位绿色基础设施以维持水平衡做出明智的决定。为此，这项工作测量了共同定位网络之间的空间结构相似性，评估了该测量随城市规模的变化以及与水平衡指标的关系。对大量不同规模的城市样本进行横截面分析，以提取空间结构和规模变化的一般模式。较大城市的空间结构相似度指数值较低，介于 –0.2 和 0.2 之间。大城市的低指数值与大型街道网络中出现的小世界属性有关，以提高功能效率和大型街道网络的网络形状。接下来，本文根据道路和地形的互连性确定了两个区域。基于主干道与更高阶排水渠道和山脊线相交点的区域的空间范围与高于正常的潮湿条件 (SPEI ≥ 2.0) 的数量相关，r 值为 –0.30，p 值0.05。总之，空间网络数据的空间统计有助于提取城市多层网络结构中固有的趋势，以提供明智的解决方案。政策制定者和规划者可以使用街道和地形之间的空间共址模式来制定数据驱动的决策，以定位基于自然的弹性城市的干预措施。