UrbanPy: A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions

Andres Regal; Claudio Ortega; Antonio Vazquez Brust; Michelle Rodriguez; Patricio Zambrano-Barragan

doi:10.1007/978-3-031-06862-1_34

UrbanPy: A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions

Andres Regal, Claudio Ortega, Antonio Vazquez Brust, Michelle Rodriguez, Patricio Zambrano-Barragan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Research demonstrates that the large-scale access and analysis to data can help cities plan for more inclusive and efficient growth. However, policy makers and researchers around the world still lack sufficient access to granular and dynamic sources of data – a challenge that has come to prominence as cities attempt to respond to the local impacts of the COVID-19 pandemic. To address this challenge, this paper presents UrbanPy, a new open-source library that makes the automated collection, processing, and visualization of spatial urban data simple and consistent for cities. UrbanPy, first developed as a tool to help Latin American cities design rapid responses to COVID-19, presents six innovative capabilities for researchers and practitioners focused on data collection, processing and visualization. To illustrate the potential applications of UrbanPy, this paper presents a case study from Lima, Peru, where the library helped municipal leaders with their COVID-19 response by identifying vulnerable populations, creating food accessibility metrics, and optimizing the location of food supply facilities.

Original language	English
Title of host publication	Production and operations management
Subtitle of host publication	POMS Lima, Peru, December 2-4, 2021 (Virtual Edition)
Editors	Jorge Vargas Florez, Irineu de Brito Junior, Adriana Leiras, Sandro Alberto Paz Collado, Miguel Domingo González Alvarez, Carlos Alberto González-Calderón, Sebastian Villa Betancur, Michelle Rodríguez, Diana Ramirez-Rios
Pages	463-473
Number of pages	11
ISBN (Electronic)	978-3-031-06862-1
DOIs	https://doi.org/10.1007/978-3-031-06862-1_34
State	Published - 2022
Event	Production and Operations Management Society - Lima - Pontificia Universidad Católica del Perú , Lima, Peru Duration: 2 Dec 2021 → 4 Dec 2021 https://congreso.pucp.edu.pe/poms/es/organizacion/?seccion=comite-organizador

Publication series

Name	Springer Proceedings in Mathematics and Statistics
Volume	391
ISSN (Print)	2194-1009
ISSN (Electronic)	2194-1017

Conference

Conference	Production and Operations Management Society - Lima
Abbreviated title	POMS Lima
Country/Territory	Peru
City	Lima
Period	2/12/21 → 4/12/21
Internet address	https://congreso.pucp.edu.pe/poms/es/organizacion/?seccion=comite-organizador

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Transportation
Urban data
Urban planning decisions

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-06862-1_34

Cite this

Regal, A., Ortega, C., Vazquez Brust, A., Rodriguez, M., & Zambrano-Barragan, P. (2022). UrbanPy: A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions. In J. Vargas Florez, I. de Brito Junior, A. Leiras, S. A. Paz Collado, M. D. González Alvarez, C. A. González-Calderón, S. Villa Betancur, M. Rodríguez, & D. Ramirez-Rios (Eds.), Production and operations management: POMS Lima, Peru, December 2-4, 2021 (Virtual Edition) (pp. 463-473). (Springer Proceedings in Mathematics and Statistics; Vol. 391). https://doi.org/10.1007/978-3-031-06862-1_34

Regal, Andres ; Ortega, Claudio ; Vazquez Brust, Antonio et al. / UrbanPy : A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions. Production and operations management: POMS Lima, Peru, December 2-4, 2021 (Virtual Edition). editor / Jorge Vargas Florez ; Irineu de Brito Junior ; Adriana Leiras ; Sandro Alberto Paz Collado ; Miguel Domingo González Alvarez ; Carlos Alberto González-Calderón ; Sebastian Villa Betancur ; Michelle Rodríguez ; Diana Ramirez-Rios. 2022. pp. 463-473 (Springer Proceedings in Mathematics and Statistics).

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title = "UrbanPy: A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions",

abstract = "Research demonstrates that the large-scale access and analysis to data can help cities plan for more inclusive and efficient growth. However, policy makers and researchers around the world still lack sufficient access to granular and dynamic sources of data – a challenge that has come to prominence as cities attempt to respond to the local impacts of the COVID-19 pandemic. To address this challenge, this paper presents UrbanPy, a new open-source library that makes the automated collection, processing, and visualization of spatial urban data simple and consistent for cities. UrbanPy, first developed as a tool to help Latin American cities design rapid responses to COVID-19, presents six innovative capabilities for researchers and practitioners focused on data collection, processing and visualization. To illustrate the potential applications of UrbanPy, this paper presents a case study from Lima, Peru, where the library helped municipal leaders with their COVID-19 response by identifying vulnerable populations, creating food accessibility metrics, and optimizing the location of food supply facilities.",

keywords = "Transportation, Urban data, Urban planning decisions",

author = "Andres Regal and Claudio Ortega and {Vazquez Brust}, Antonio and Michelle Rodriguez and Patricio Zambrano-Barragan",

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year = "2022",

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Regal, A, Ortega, C, Vazquez Brust, A, Rodriguez, M & Zambrano-Barragan, P 2022, UrbanPy: A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions. in J Vargas Florez, I de Brito Junior, A Leiras, SA Paz Collado, MD González Alvarez, CA González-Calderón, S Villa Betancur, M Rodríguez & D Ramirez-Rios (eds), Production and operations management: POMS Lima, Peru, December 2-4, 2021 (Virtual Edition). Springer Proceedings in Mathematics and Statistics, vol. 391, pp. 463-473, Production and Operations Management Society - Lima, Lima, Peru, 2/12/21. https://doi.org/10.1007/978-3-031-06862-1_34

UrbanPy: A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions. / Regal, Andres; Ortega, Claudio; Vazquez Brust, Antonio et al.
Production and operations management: POMS Lima, Peru, December 2-4, 2021 (Virtual Edition). ed. / Jorge Vargas Florez; Irineu de Brito Junior; Adriana Leiras; Sandro Alberto Paz Collado; Miguel Domingo González Alvarez; Carlos Alberto González-Calderón; Sebastian Villa Betancur; Michelle Rodríguez; Diana Ramirez-Rios. 2022. p. 463-473 (Springer Proceedings in Mathematics and Statistics; Vol. 391).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - UrbanPy

T2 - Production and Operations Management Society - Lima

AU - Regal, Andres

AU - Ortega, Claudio

AU - Vazquez Brust, Antonio

AU - Rodriguez, Michelle

AU - Zambrano-Barragan, Patricio

PY - 2022

Y1 - 2022

N2 - Research demonstrates that the large-scale access and analysis to data can help cities plan for more inclusive and efficient growth. However, policy makers and researchers around the world still lack sufficient access to granular and dynamic sources of data – a challenge that has come to prominence as cities attempt to respond to the local impacts of the COVID-19 pandemic. To address this challenge, this paper presents UrbanPy, a new open-source library that makes the automated collection, processing, and visualization of spatial urban data simple and consistent for cities. UrbanPy, first developed as a tool to help Latin American cities design rapid responses to COVID-19, presents six innovative capabilities for researchers and practitioners focused on data collection, processing and visualization. To illustrate the potential applications of UrbanPy, this paper presents a case study from Lima, Peru, where the library helped municipal leaders with their COVID-19 response by identifying vulnerable populations, creating food accessibility metrics, and optimizing the location of food supply facilities.

AB - Research demonstrates that the large-scale access and analysis to data can help cities plan for more inclusive and efficient growth. However, policy makers and researchers around the world still lack sufficient access to granular and dynamic sources of data – a challenge that has come to prominence as cities attempt to respond to the local impacts of the COVID-19 pandemic. To address this challenge, this paper presents UrbanPy, a new open-source library that makes the automated collection, processing, and visualization of spatial urban data simple and consistent for cities. UrbanPy, first developed as a tool to help Latin American cities design rapid responses to COVID-19, presents six innovative capabilities for researchers and practitioners focused on data collection, processing and visualization. To illustrate the potential applications of UrbanPy, this paper presents a case study from Lima, Peru, where the library helped municipal leaders with their COVID-19 response by identifying vulnerable populations, creating food accessibility metrics, and optimizing the location of food supply facilities.

KW - Transportation

KW - Urban data

KW - Urban planning decisions

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U2 - 10.1007/978-3-031-06862-1_34

DO - 10.1007/978-3-031-06862-1_34

M3 - Conference contribution

AN - SCOPUS:85140740744

SN - 978-3-031-06861-4

T3 - Springer Proceedings in Mathematics and Statistics

SP - 463

EP - 473

BT - Production and operations management

A2 - Vargas Florez, Jorge

A2 - de Brito Junior, Irineu

A2 - Leiras, Adriana

A2 - Paz Collado, Sandro Alberto

A2 - González Alvarez, Miguel Domingo

A2 - González-Calderón, Carlos Alberto

A2 - Villa Betancur, Sebastian

A2 - Rodríguez, Michelle

A2 - Ramirez-Rios, Diana

Y2 - 2 December 2021 through 4 December 2021

ER -

Regal A, Ortega C, Vazquez Brust A, Rodriguez M, Zambrano-Barragan P. UrbanPy: A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions. In Vargas Florez J, de Brito Junior I, Leiras A, Paz Collado SA, González Alvarez MD, González-Calderón CA, Villa Betancur S, Rodríguez M, Ramirez-Rios D, editors, Production and operations management: POMS Lima, Peru, December 2-4, 2021 (Virtual Edition). 2022. p. 463-473. (Springer Proceedings in Mathematics and Statistics). doi: 10.1007/978-3-031-06862-1_34

UrbanPy: A library to download, process and visualize high resolution urban data to support transportation and urban planning decisions

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Production and operations management: POMS Lima, Peru, December 2-4, 2021 (Virtual Edition)

Cite this