It also furthers the science of cities by providing a better understanding of urban patterns and how they correspond to evolutionary mechanisms, planning, and design. Measuring these network patterns can help researchers, planners, and community members understand local histories of urban design, transportation planning, and morphology evaluate existing transportation system patterns and configurations and explore new infrastructure proposals and alternatives. In particular, network orientation and geometry have played an outsized role in urban planning since its earliest days (Smith 2007). These networks in turn structure the human interactions and transportation processes that run along them, forming an important pillar of city planners’ quest for spatial order (Rose-Redwood and Bigon 2018). A city’s development eras, design paradigms, underlying terrain, culture, and local economic conditions influence the pattern, topology, and grain of its street networks (Jackson 1985 Kostof 1991). This study considers the spatial logic and geometric ordering that arise through street network orientation. Theories of urban order span sociological frameworks of physical-social disorder (e.g., “broken windows” theory), to public health goals of opening-up and sanitizing pathogenic urban spaces, to city planners’ pursuit of functional differentiation and regulation (Boyer 1983 Hatuka and Forsyth 2005 Mele 2017 O’Brien et al. One research stream has explored the nature of entropy and order in urban street networks, seeking to quantify patterns of spatial order and disorder in urban circulation systems (Gudmundsson and Mohajeri 2013 Li et al. In these spatial networks, entropy has deep theoretical connections with complexity (Batty 2005b Batty et al. 2013 Nilsson and Gil 2019 Tsiotas and Polyzos 2018 Wang 2015). 2014 Jiang and Claramunt 2004 Marshall 2004 Masucci et al. 2011 Ducruet and Beauguitte 2014 Jiang et al. 2013 Batty 2005a Boeing 2018a Buhl et al. Accordingly, researchers have recently devoted much attention to street network patterns, performance, complexity, and configuration (Barthelemy et al. They shape travel behavior, location decisions, and the texture of the urban fabric (Jacobs 1995 Levinson and El-Geneidy 2009 Parthasarathi et al. Spatial networks such as streets, paths, and transit lines organize the human dynamics of complex urban systems. These methods demonstrate automatic, scalable, reproducible tools to empirically measure and visualize city spatial order, illustrating complex urban transportation system patterns and configurations around the world. These indicators, taken in concert, help reveal the extent and nuance of the grid. On average, US/Canadian study sites are far more grid-like than those elsewhere, exhibiting less entropy and circuity. Significant statistical relationships exist between city orientation-order and other indicators of spatial order, including street circuity and measures of connectedness. A cluster analysis is performed to explore similarities and differences among these study sites in multiple dimensions. It also develops a new indicator of orientation-order that quantifies how a city’s street network follows the geometric ordering logic of a single grid. It measures the entropy of street bearings in weighted and unweighted network models, along with each city’s typical street segment length, average circuity, average node degree, and the network’s proportions of four-way intersections and dead-ends. This study examines street network orientation, configuration, and entropy in 100 cities around the world using OpenStreetMap data and OSMnx. Past studies have explored individual cases of orientation and entropy, but little is known about broader patterns and trends worldwide. Measures of entropy reveal a city’s streets’ order and disorder. Street networks may be planned according to clear organizing principles or they may evolve organically through accretion, but their configurations and orientations help define a city’s spatial logic and order.
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