Open data and open-source software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities

Introduction

Policies that determine cities’ urban form, land use patterns, and transport opportunities also determine health and sustainability. Creating healthier and more sustainable cities is a global priority integral to achieving the UN's Sustainable Development Goals (SDGs) and WHO's health equity goals. Various indicator frameworks have been proposed to monitor progress towards these goals. However, most existing frameworks rely on citywide measures and focus on comparisons between cities. Although such comparisons are useful for determining priorities and interventions at the international and national levels, within-city (ie, neighbourhood-level) comparisons are key to unlocking the full potential of city planning to unmask and attenuate local urban health inequities.

Within-city versus between-city spatial indicators

Maps can help local and regional planners to reveal the spatial distribution of health-promoting infrastructure and amenities within cities (eg, walkable streets, public transport, daily living needs, and green spaces), and identify inequities in access. Mapped neighbourhood-level spatial indicators facilitate comparisons within cities, highlight resource distribution and areas needing interventions, encourage accountability, and empower communities to advocate for improvements. Growing access to big data and high-powered computing enables neighbourhood-level spatial indicators to be developed and disseminated more readily.

Urban policy targets are often set at a citywide level (eg, percentage of city population with access to amenities).3?Neighbourhood-level spatial indicators help planners to identify differences in access to urban design and transport features that support healthy and sustainable lifestyles, to better target local interventions. However, planners also need a means of aggregating consistently measured neighbourhood-level spatial indicators to the city scale, to compare between cities (benchmarking) and over time (monitoring). These are crucial first steps towards achieving urban health and sustainability goals. Nevertheless, many prominent indicator guidelines do not address measurement standards, indicator targets, or data acquisition.

Creating globally applicable city planning spatial indicators

Creating high-quality, fine-grained spatial indicators to measure progress towards healthy and sustainable cities worldwide presents technical challenges for both between-city and within-city comparisons.?Although some cities collect and maintain high-quality,?fine-grained data on land use, transport infrastructure, and socioeconomic characteristics, many do not. Even when such data exist, they might not be publicly available to researchers and practitioners. Researchers doing comparative analyses—particularly international analyses—must account for region-specific and dataset-specific inconsistencies in assumptions, standards, scales, and timelines. Data quality varies widely, as do digitisation standards and encodings, collection dates, local meanings of transport infrastructure or land use classifications, and spatial scales (eg, defining the city as an incorporated municipality, urbanised area, or metropolitan area).

Lack of access to software, training, and resources also constrains indicator creation. Closed-source, proprietary geographic information systems are often expensive, do not lend themselves to open science or reproducibility, and fit poorly with modern data science practices. Advanced spatial analysis requires extensive training, but such expertise can be uncommon in government agencies and can be difficult or expensive to procure from the private sector. Resource constraints pose a particular challenge in low-income and middle-income countries, where data availability, data quality, and local technical capacity might be scarce. These limitations thwart efforts to develop actionable indicators to track the creation of healthy and sustainable urban environments in our planet's most rapidly developing cities, and constrain governments’ capacity to develop evidence-based policies and monitor their effects.

A 21st century approach to calculating spatial indicators

Given the importance of urban spatial indicators to benchmark and monitor cities and inform interventions, a better model for creating indicators would leverage emerging open-source software and open-data commons to build high-quality, accessible, free tools for calculating and visualising such indicators. Open-data sources with global scope offer opportunities to measure and analyse urban health and sustainability indicators in diverse geographical contexts. OpenStreetMap (OSM) is a crowdsourced mapping project that provides open access to regularly updated spatial data worldwide, coded according to consistent and community-led guidelines.

This third paper in the Series on urban design, transport, and health addresses the need to better measure, map, and compare urban design and transport features important for creating healthy and sustainable cities. We present an open-source software framework that uses open data to calculate spatial indicators within and between cities around the world, including in understudied and under-resourced countries. We show the feasibility and utility of our approach by creating a cross-sectional snapshot of priority indicators recommended in the first?Lancet?Series (Series 1) on urban design, transport, and health, showing between-city comparisons, and mapping within-city spatial inequities.?We link these indicators to the local policy contexts identified by Lowe and colleagues in the first paper in this Series (Series 2),?and identify populations living above and below the critical thresholds identified by Cerin and colleagues in the second paper in this Series.?We discuss the practical value of this tool and empirical findings for policy making. The paper concludes with a call for action: to build healthy and sustainable cities, we must better measure city building and we must build healthy and sustainable cities for all—not just for some—by reducing within-city inequities.

Full Article: https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(22)00072-9/fulltext

Reference:

Geoff Boeing, PhD , Carl Higgs, MPH, Shiqin Liu, MS, Prof Billie Giles-Corti, PhD, Prof James F Sallis, PhD, Prof Ester Cerin, et al, 2022. Using open data and open-source software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities. Lancet Glob. Heal. 10, 907–918. https://doi.org/https://doi.org/10.1016/S2214-109X(22)00072-9