# **Methodology**

To begin, a 0.5x0.5km grid was created over each city. This grid functioned as the base unit of measurement for all the indicator analysis. All spatial data layers were aggregated to this resolution and joined to this grid.

Urban footprints (city boundaries) were created by combining a population density layer (Landscan) with an urban footprint layer (Global Human Settlement Layer ‐ GHSL). Created by European Commission’s Joint Research Centre (JRC), the GHSL offers a systematic and detailed representation of ‘built‐up’ areas, and classifies each 30m pixel as ‘built‐up’ if it intersects with a building or road.<sup>54</sup> In order to make these datasets comparable they were overlaid and summarized to the 0.5x0.5km grid.

Grid cells comprised of more than 10% built‐up land and had more than 100 inhabitants were labeled as urban. These thresholds were created from visual interpretation, and are consistent with previous urban mapping studies.<sup>55</sup> While the city boundary created in this study differs from the administrative border, it more accurately reflects each city’s physical ‘built‐up’ land and hence it is better suited for inter‐city comparisons.

Following the creation of the city footprints, the land cover classification layers were converted to 0.5x0.5km grids. Each grid cell was labeled as a class (vegetation, residential regular, residential irregular, etc.) based on the majority land cover class contained in that cell. The following analyses use only grid cells within a 15km buffer from the CBD.

# **Centrality**

Urban sprawl is defined as areas with low density, and scattered, discontinuous, and commercial strip development patterns.<sup>56</sup> Sprawl reduces inner‐urban connectivity and typically places higher transportation costs on families living in these areas. However, the effects of sprawl are not just felt in the areas experiencing sprawl, but are also felt by firms and employers in the inner city. Without a competitive workforce in the vicinity, employment centers may experience the ripples of sprawl in the form of increased costs of labor. Similarly, increased infrastructure investments, such as road networks, sewage pipes, and school systems are required to service these sprawling populations, placing a monetary burden on local governments as well.<sup>57</sup> Additionally, non‐monetary effects of sprawl include increased air pollution, loss of natural land, and ecosystem fragmentation.<sup>58</sup> City decentralization is a common effect of sprawl, and leads to longer travel distances and time for households. To measure the degree to which development has diffused across the city, an index

> 54 Pesaresi, M.; Guo Huadong; Blaes, X.; Ehrlich, D.; Ferri, S.; Gueguen, L.; Halkia, M.; Kauffmann, M.; Kemper, T.; Linlin Lu; Marin‐Herrera, M.A.; Ouzounis, G.K.; Scavazzon, M.; Soille, P.; Syrris, V.; Zanchetta, L., "A Global Human Settlement Layer From Optical HR/VHR RS Data: Concept and First Results," _Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of_ , vol.6, no.5, pp.2102,2131, Oct. 2013 doi: 10.1109/JSTARS.2013.2271445.

> 55 Azar et al 2010. Spatial refinement of census population distribution using remotely sensed estimates of impervious surfaces in Haiti. International Journal of Remote Sensing. Taylor and Frances. page 5641.

> 56 Ewing, Reid. 1997. Is Los Angeles‐style sprawl desireable? Journal of American Planning Association, 63 (1): 107‐ 126.

> 57 Squires, Gregory. 2002. Urban Sprawl: Causes, Consequences, & Policy Responses. 2002. The Urban Institute: Washington, DC.

> 58 Johnson, Michael. 2001. Environmental impacts of urban sprawl: a survey of the literature and proposed research agenda. Enviornment and Planning A, 33: 717‐735.

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