A Review of Spatial Network Insights and Methods in the Context of Planning: Applications, Challenges, and Opportunities

Abstract

With the rise of geospatial big data, new narratives of cities based on spatial networks and flows have replaced the traditional focus on locations. While plenty of research have empirically analyzed network structures, there lacks a state-of-the-art synthesis of applicable insights and methods of spatial networks in the planning context. In this chapter, we reviewed the theories, concepts, methods, and applications of spatial network analysis in cities and their insights for planners from four areas of concern: spatial structures, urban infrastructure optimizations, indications of economic wealth, social capital, and residential mobility, and public health control (especially COVID-19). We also outlined four challenges that planners face when taking the planning knowledge from spatial networks to actions: data openness and privacy, linkage to direct policy implications, lack of civic engagement, and the difficulty to visualize and integrate with GIS. Finally, we envisioned how spatial networks can be integrated into a collaborative planning framework.

arXiv commentpeer-reviewed book chapter

References in corpus (23)

• Community detection in graphs
• Finding community structure in very large networks
• Maps of random walks on complex networks reveal community structure
• The Building Blocks of Economic Complexity
• Spatial Networks
• Statistical Mechanics of Community Detection
• The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles
• OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks
• Evidence of economic segregation from mobility lockdown during COVID-19 epidemic
• Centrality Measures in Spatial Networks of Urban Streets
• Mapping change in large networks
• A Comparative Analysis of Community Detection Algorithms on Artificial Networks
• Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters in the world economy
• Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data
• Urban Spatial Order: Street Network Orientation, Configuration, and Entropy
• Multiscale Dynamic Human Mobility Flow Dataset in the U.S. during the COVID-19 Epidemic
• Delineating geographical regions with networks of human interactions in an extensive set of countries
• Spatial Heterogeneity Can Lead to Substantial Local Variations in COVID-19 Timing and Severity
• Mobility Changes in Response to COVID-19
• Estimation of Regional Economic Development Indicator from Transportation Network Analytics
• LSTM-TrajGAN: A Deep Learning Approach to Trajectory Privacy Protection
• Deck.gl: Large-scale Web-based Visual Analytics Made Easy
• Social networks and geography: a review of the literature and its implications