Abstract
Public services are essential to satisfy the needs of healthcare, education, justice, Etc. in citizens’ daily life. Thus, individuals need these services in a certain proximity to their homes. Nonetheless, in big cities, some public services are not close enough. This is especially true for poor individuals who need public transportation to reach such services. To assess the accessibility of individuals to public services using the public transportation system, we propose a methodology to compute profile districts based on the accessibility to different services. We apply our methodology to Lima and Cusco cities in Peru, showing the tool’s utility while being simple to understand. We profile fifty different districts in four groups, allowing policymakers and urban planners to observe the lack of public services to understand the urban dynamics and social exclusion.
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Data availability
The code for the experiments is available at https://github.com/leiparov/intercon-simbig-2021.git. The dataset for public transportation in Cusco are publish in https://data.mendeley.com/v1/datasets/2rbs4pc894/draft?preview=1. The public transportation network for Lima is available upon request at https://soluciones.atu.gob.pe/saip_portal/.
Notes
- 1.
OpenStreetMap: www.openstreetmap.org.
- 2.
OSMnx Python package https://github.com/gboeing/osmnx.
- 3.
Python recipe: https://code.activestate.com/recipes/119466/.
- 4.
- 5.
GostNets: https://github.com/worldbank/GOSTnets.
- 6.
Smartbus: https://smartbus.pe/.
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Acknowledgement
The authors thank Smart Innovation Group S.R.L., the company that helped us to gather public transportation routes in Cusco using their Smartbus solution.
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Rojas-Bustamante, L., Alfaro, C., Molero, I., Aparicio, D., Nunez-del-Prado, M. (2023). Profiling Public Service Accessibility Based on the Public Transport Infrastructure. In: Lossio-Ventura, J.A., Valverde-Rebaza, J., Díaz, E., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2022. Communications in Computer and Information Science, vol 1837. Springer, Cham. https://doi.org/10.1007/978-3-031-35445-8_14
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