Inter-American Development Bank
facebook
twitter
youtube
linkedin
instagram
Abierto al públicoBeyond BordersCaribbean Development TrendsCiudades SosteniblesEnergía para el FuturoEnfoque EducaciónFactor TrabajoGente SaludableGestión fiscalGobernarteIdeas MatterIdeas que CuentanIdeaçãoImpactoIndustrias CreativasLa Maleta AbiertaMoviliblogMás Allá de las FronterasNegocios SosteniblesPrimeros PasosPuntos sobre la iSeguridad CiudadanaSostenibilidadVolvamos a la fuente¿Y si hablamos de igualdad?Home
Citizen Security and Justice Creative Industries Development Effectiveness Early Childhood Development Education Energy Envirnment. Climate Change and Safeguards Fiscal policy and management Gender and Diversity Health Labor and pensions Open Knowledge Public management Science, Technology and Innovation  Trade and Regional Integration Urban Development and Housing Water and Sanitation
  • Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer

Abierto al público

  • HOME
    • About this blog 
    • Editorial guidelines
  • CATEGORIES
    • Knowledge Management
    • Open Data
    • Open Learning
    • Open Source
    • Open Systems
  • Authors
  • English
urbanpy-analisis-distancias

Open-Source technology and AI-powered Data to strengthen Urban Planning

November 15, 2024 by Laura McGorman - Brittney Butler - Julia Dias - Hector Antonio Vázquez Brust 3 Comments


UrbanPy is a python-based tool offered in an open-source fashion as part of the Open Urban Planning Toolbox. It was designed to support urban planning by bringing together specific local data focused on geographic regions defined by municipal authorities, making it useful across various contexts.  The tool was developed by the Inter-American Development Bank (IDB) in collaboration with the Universidad del Pacífico and the Economic Development Office of the Municipality of Lima.  Among its features, UrbanPy incorporates Meta’s AI-powered population maps, which aim to provide helpful information for supporting investment and development programs throughout Latin America and elsewhere.

Challenges in urban planning 

During the COVID-19 pandemic, urban planners struggled to measure and address accessibility issues, specifically those enabling the delivery of public health services. Metropolitan governments in Latin America needed immediate solutions to plan the distribution of care at the intra-urban level, but it was difficult to know where services such as medical aid, medicines, and financial assistance should be deployed. Responding to these challenges, the IDB’s Urban Development and Housing Division created UrbanPy, which includes high-resolution mapping techniques, information on population density, as well as the location of key points of interest.

This tool can produce detailed accessibility metrics and heat maps that indicate the degree of isolation from services provided by pharmacies, hospitals, banks, and schools, allowing for tailored delivery of interventions. This tool was initially developed by IDB’s City Lab to support the city of Lima, Peru in identifying areas lacking essential services during the COVID-19. However, the tool has since grown in its application potential, covering many additional projects including those focused on education and infrastructure.

How UrbanPy Works

UrbanPy functions as an all-encompassing tool for urban planners, offering a range of automated analytical capabilities. It allows users to:

  • Download open-source spatial data: city/state/region limits, local road networks, and key points of interest such as hospitals, pharmacies, banks & ATMs, and other services.
  • Allow for the use of a grid system or administrative boundaries as spatial units.
  • Origin-destination travel matrix calculation by any mode using a routing API
  • Obtain travel time from spatial units to the closest facilities for any service, producing accessibility indices
  • Consolidate the results as tables and/or shapefiles (georeferenced datasets)
  • Visualize the results as interactive maps

Data for Good’s AI-Powered Population Density Maps

A new key data source integrated into UrbanPy is  the High-Resolution Population Density Maps provided by Meta’s Data for Good program. These maps leverage artificial intelligence to estimate the number of people living within 30-meter grid tiles worldwide, by using advanced computer vision techniques to identify structures in satellite imagery and then combining these findings with census data. In addition to total population counts, these maps also provide demographic breakdowns, such as the number of children under five, women of reproductive age, and elderly populations in very small areas. Meta’s AI-powered population maps include estimates for populations in both urban and rural settings and are openly available for over 160 countries. 

UrbanPy allows users to easily download Data for Good’s High-Resolution Population Density Maps for any country, state, or city of interest. Users can then combine population counts with UrbanPy’s accessibility indices to provide highly granular maps that pinpoint where there are areas of people living with scarce access to essential services.

Impact and Future Potential

UrbanPy was used during the early days of the COVID-19 pandemic in support of the City of Lima, Peru to prioritize emergency assistance. This map showcases UrbanPy’s calculations for travel times to the nearest pharmacy in the environs of Lima, Peru:

Over the past several years, the tool’s use has expanded to include several projects in Brazil, including IDB operations to support the expansion of school infrastructure, helping government officials in identifying the optimal location for new public schools in the State of Pará, a region with more than 8 million inhabitants. UrbanPy and its associated population estimates from Meta have also been used to assess school accessibility in the Amazon Region and calculate measures such as the average travel time to school among school-aged children. 

Collaborations between multilateral institutions like IDB and technology companies in the form of open-source tooling allow cutting edge analytical approaches and advances in artificial intelligence to directly benefit communities. By combining Meta’s AI-powered population maps into a tool developed by regional experts, urban planners throughout Latin America can integrate global advances in mapping and transportation into their work. UrbanPy’s open-source nature also allows local officials to tailor it to their own unique settings and solve problems for their specific contexts.

How will you use UrbanPy? Tell us in the comments below.


Filed Under: Open Source Tagged With: Actionable Resources, Code for Development, Geospatial Data

Laura McGorman

Director of Data for Good at Meta, a program that shares open datasets and AI models with governments, researchers, and nonprofits around the world to assist with economic development, crisis response, and climate change.

Brittney Butler

Brittney has been a Program Manager with Data for Good for nearly two years. She has research experience in health economics and policy, conducting cost-effectiveness analyses of interventions in rural Nepal, analyzing the live impact of COVID-19 on communities of color in the U.S., and investigating the effect of prescribed fires on vulnerable communities in California.

Julia Dias

Julia Dias es consultora en innovación digital y lidera las iniciativas de Código para el Desarrollo y el Development Data Partnership en el Banco Interamericano de Desarrollo (BID). Además de promover la adopción de código y datos abiertos en la América Latina y el Caribe, Julia también apoya los sectores del BID en materia de innovación, sea por medio de la innovación abierta, o apoyándolos a desarrollar herramientas digitales que utilizan tecnologías disruptivas para mejorar el diseño y ejecución de políticas públicas. Julia tiene más de 10 años de experiencia en organizaciones multilaterales y de impacto social en la región, es ingeniera industrial por la UNICAMP, y cuenta con una maestría en Administración Pública por Columbia University. Julia está especialmente interesada en políticas transversales que busquen reducir la pobreza extrema.

Hector Antonio Vázquez Brust

Científico de datos urbanos. Trabaja con ONGs, gobiernos y agencias internacionales ayudando a comprender y gestionar los procesos urbanos y territoriales. Su área de interés es la aplicación del análisis computacional a gran escala para la mejora de las políticas públicas.

Reader Interactions

Comments

  1. Liana says

    December 27, 2024 at 5:00 am

    thanks for info.

    Reply
  2. Jorge Vinces Polar says

    January 18, 2025 at 5:07 am

    Para análisis de densidad de ciudades peruanas

    Reply
  3. Angel Hernandez says

    February 3, 2025 at 9:53 am

    Para analisis de Gobierno Gracias por su ayuda

    Reply

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Primary Sidebar

Follow Us

Subscribe

About this blog

Open knowledge can be described as information that is usable, reusable, and shareable without restrictions due to its legal and technological attributes, enabling access for anyone, anywhere, and at any time worldwide.

In the blog 'Abierto al Público,' we explore a wide range of topics, resources, and initiatives related to open knowledge on a global scale, with a specific focus on its impact on economic and social development in the Latin American and Caribbean region. Additionally, we highlight the Inter-American Development Bank's efforts to consistently disseminate actionable open knowledge generated by the organization.

Search

Topics

Access to Information Actionable Resources Artificial Intelligence BIDAcademy Big Data Citizen Participation Climate Change Code for Development Coronavirus Creative Commons Crowdsourcing Data Analysis Data Journalism Data Privacy Data Visualization Development projects Digital Badges Digital Economy Digital Inclusion Entrepreneurship Events Gender and Diversity Geospatial Data Hackathons How to Instructional Design Key Concepts Knowledge Products Lessons Learned Methodologies MOOC Most Read Natural Language Processing Numbers for Development Open Access Open Government Open Innovation Open Knowledge Open Science Solidarity Sustainable Development Goals Taxonomy Teamwork Text Analytics The Publication Station

Similar Posts

  • Presenting the Open Urban Planning Toolbox
  • Meet BA Obras: an open platform for monitoring public works
  • How an open-source algorithm was reused to improve health services in New York City
  • Getting the most out of your open source software initiative
  • The IDB is committed to the open source model for development

Footer

Banco Interamericano de Desarrollo
facebook
twitter
youtube
youtube
youtube

    Blog posts written by Bank employees:

    Copyright © Inter-American Development Bank ("IDB"). This work is licensed under a Creative Commons IGO 3.0 Attribution-NonCommercial-NoDerivatives. (CC-IGO 3.0 BY-NC-ND) license and may be reproduced with attribution to the IDB and for any non-commercial purpose. No derivative work is allowed. Any dispute related to the use of the works of the IDB that cannot be settled amicably shall be submitted to arbitration pursuant to the UNCITRAL rules. The use of the IDB's name for any purpose other than for attribution, and the use of IDB's logo shall be subject to a separate written license agreement between the IDB and the user and is not authorized as part of this CC- IGO license. Note that link provided above includes additional terms and conditions of the license.


    For blogs written by external parties:

    For questions concerning copyright for authors that are not IADB employees please complete the contact form for this blog.

    The opinions expressed in this blog are those of the authors and do not necessarily reflect the views of the IDB, its Board of Directors, or the countries they represent.

    Attribution: in addition to giving attribution to the respective author and copyright owner, as appropriate, we would appreciate if you could include a link that remits back the IDB Blogs website.



    Privacy Policy

    Copyright © 2025 · Magazine Pro on Genesis Framework · WordPress · Log in

    Banco Interamericano de Desarrollo

    Aviso Legal

    Las opiniones expresadas en estos blogs son las de los autores y no necesariamente reflejan las opiniones del Banco Interamericano de Desarrollo, sus directivas, la Asamblea de Gobernadores o sus países miembros.

    facebook
    twitter
    youtube
    This site uses cookies to optimize functionality and give you the best possible experience. If you continue to navigate this website beyond this page, cookies will be placed on your browser.
    To learn more about cookies, click here
    x
    Manage consent

    Privacy Overview

    This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
    Necessary
    Always Enabled
    Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
    Non-necessary
    Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.
    SAVE & ACCEPT