Citation

George JS, Paul SK, Dhawale R. Environ. Plan. B Urban Anal. City Sci. 2022; 49(5): 1448-1463.

Copyright

(Copyright © 2022, SAGE Publishing)

DOI

10.1177/23998083211039853

PMID

unavailable

Abstract

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.

Language: en

Keywords

GIS; Network graphs; remote sensing; street networks; urban morphology