Urban street network and data science-based spatial connectivity evaluation of African Cities: Implications for sustainable urban development

Wenzhong Shi, Man Sing Wong, Rui Zhu, Bewketu Mamaru Mengiste (Corresponding Author)

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

The aim of the study was to evaluate spatial connectivity and socioeconomic status of African cities using street network datasets and geospatial methods. The drivable street network was collected from OpenStreetMap, and spatial connectivity has developed at the cityscape level and central business districts (CBD). At the cityscape level, almost all studied cities have minimum spatial connectivity as illustrated by metrics like betweenness centrality, average node average and intersection density metrics where maximum values were 0.11, 6.28 and 359 nodes/km2 respectively. The spatial connectivity of CBD was higher compared cityscape level, which indicated the availability unbalanced growth of drivable street network in the sample cities. Moreover, the study has also founded relationship between spatial connectivity and socioeconomic status of cities which in turn have implications to the sustainability of urban areas.
Original languageEnglish
JournalGeo Journal
DOIs
Publication statusPublished - 2023

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