Spatial Analysis of Kuwait Street Networks التحليل المكاني لشبكة الشوارع في الكويت

Alattar, Mohammad; Beecroft, Mark; Albanai, Jasem · 2024 · Crossref

DOI: 10.34120/jss.v52i2.2861

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Summary

This study addresses a significant geographical and temporal gap in urban morphology literature by providing the first comprehensive spatial analysis of street networks (SNs) in Kuwait. While SN characteristics have been extensively studied in developed nations, data for developing countries, particularly in the Gulf Cooperation Council region, remains scarce. The research is motivated by Kuwait’s rapid urbanization, high car dependency, and associated challenges such as traffic congestion and housing shortages. The primary objective is to quantify the griddedness, transportation efficiency, and connectivity of Kuwait’s built environment to inform sustainable urban planning and future infrastructure development. The methodology utilizes the Python package OSMnx to extract, model, and analyze street network data from the open-source repository OpenStreetMap. The study area comprises 110 polygons representing Kuwait’s urban districts, validated against Kuwait Municipality data. The authors calculated six key indicators: orientation-order (griddedness), average street length, street circuity (transportation efficiency), average node degree (connectivity), proportion of dead-ends, and proportion of four-way intersections. Spatial dependence was assessed using univariate Moran’s I tests via the GeoDa software. Qualitative analysis complemented the quantitative findings to interpret the results within the context of Kuwait’s urban form. The results reveal distinct patterns between residential and non-residential areas. Orientation-order was highest in modular residential areas like Riqqa (φ = 0.78), indicating strong grid patterns, while coastal areas such as Sabah Al Ahmad Sea City exhibited the lowest orientation-order (φ = 0.02) due to shoreline constraints. Non-residential areas generally featured coarse-grained networks with longer average street lengths and lower intersection connectivity, whereas residential areas displayed finer-grained networks. Street circuity varied significantly, with grid-like residential areas like Qadsiya showing minimal deviation from straight-line distances (3.7%), while other residential areas like Naeem showed high circuity (43.8%). Notably, the study found no significant correlation between orientation-order and other indicators, nor did it find spatial autocorrelation among the indicators, suggesting a lack of consistency in Kuwait’s urban planning. The significance of this work lies in its contribution to the understanding of urban morphology in understudied regions. The findings highlight the inconsistent nature of Kuwait’s street networks, which often favor automobile dependency and may discourage walking, particularly in non-residential zones with long street blocks. The authors conclude that these insights can guide more sustainable urban planning for future expansions. Additionally, the study provides an open Python script and data repository, facilitating further research on Kuwait’s built environment and enabling comparative studies with other global cities.

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• urban rural setting