How far to the nearest city? Global map of travel time to cities published

IMAGE: The accessibility map has a spatial resolution of approximately 1?×?1?km, spans 60° south to 85° north latitude, and enumerates travel time to the city with the shortest associated journey....

Image credit: 
2018 OpenStreetMap contributors, creative commons attribution 4.0

Over 80% of people - 5.88 billion individuals - reside within one hour of a city. However, accessibility is not equally distributed across the development spectrum. While people live within one hour of a city in over 90% of cases in high-income countries - concentrated in Europe and North America - for low-income countries concentrated in sub-Saharan Africa, the figure is 50.9%.

These figures are one result of work from a team of researchers, led by Oxford University and with expert input from the Joint Research Centre (JRC), the European Commission's science and knowledge service, now published in Nature. In mapping urban accessibility worldwide, the study provides an actionable dataset that will support global and local decision-making on development and environmental policies.

The results of the study confirm that the economic and manmade resources that sustain human wellbeing are not distributed evenly across the world, but are instead heavily concentrated in cities. Poor access to the opportunities and services offered by urban centres is a major barrier to improved livelihoods and overall development. By further triangulating this map against socioeconomic datasets, the scientists demonstrate how access to urban centres stratifies the economic, educational, and health status of humanity.

Advancing this accessibility worldwide underpins the equity agenda of 'leaving no one behind' established by the Sustainable Development Goals of the United Nations.

A versatile map for policymakers

To demonstrate the map's usefulness for global and local decision-making, the report provides exploratory analyses examining relationships between accessibility and national- level income - as well as economic prosperity, educational attainment, and healthcare utilisation at the level of household clusters.

The report also shows the potential of the map to contribute to natural science research, conservation efforts, and formulation of environmental policy.

Although the results are useful in a variety of contexts, their potential impact centres around a more unifying aim: catalysing action to narrow gaps in opportunity by improving accessibility for remote populations and/or reducing disparities between populations with differing degrees of connectivity to cities.

The map is also likely to serve as a critical input for future geospatial modelling endeavours, including those that highlight positive aspects of low accessibility, such as the protective effect that remoteness provides to wilderness areas, or reinforce the need for strategic road building that avoids unnecessary environmental damage.

The JRC's input

The JRC's pioneering work on accessibility dates back to 2008, with the first effort to produce a "Global Map of Accessibility". Since then, JRC scientists have produced more ground-breaking reference datasets, including both the Global Human Settlement Layer and the Global Surface Water Explorer, which are cited in this report. As part of their input, JRC scientists also looked at the role of roads in accessibility and the link to forest degradation, climate change and biodiversity impacts, especially in tropical environments.

JRC work on the map stemmed from a focus on road development in tropical forest areas through the Roadless Forest project, funded by the European Commission's Directorate General for Climate Action. In this context, scientists explored the relationship between roads, especially illegal roads linked to logging, and forest loss and degradation.

The previous Global Map of Accessibility, produced almost a decade ago, predated the baseline for the Sustainable Development Goals and used data that was limited in resolution and accuracy. This new map obviously takes into account the subsequent expansion in infrastructure networks, particularly outside of urban areas.

For this study, the opportunities for using new data sources resulted in an almost five-fold increase in the amount of road data included in the analysis. By combining crowdsourced road data (OpenStreetMap) with data derived from commercial datasets and the use of high performance computing environments like the Google Earth Engine, scientists were able to expand the scope of the research considerably.

Credit: 
European Commission Joint Research Centre