Smart Roads: Transforming Road Investments with Biodiversity Intelligence

Biodiversity is fundamental to food security, clean water, climate stability, and livelihoods, making it critical to sustainable development and poverty alleviation. However, it is declining at alarming rates. A major UN report (IPBES 2019) warns that one million species face extinction, with current extinction rates over 1,000 times the natural baseline. The Living Planet Index shows a 69% drop in vertebrate populations since 1970. Despite global commitments like the Kunming-Montreal Global Biodiversity Framework (GBF) and the “30x30” goal to protect 30% of land and ocean areas by 2030, integrating biodiversity into development sectors, especially infrastructure, remains a challenge, mainly due to the lack of actionable biodiversity data. In this blog, we explore how new data-driven approaches can help integrate biodiversity considerations into road corridor planning, offering practical solutions to align infrastructure development with conservation goals.
 

Data for Biodiversity-Smart Roads

To address the lack of actionable biodiversity data, the World Bank has developed a Global Species Database that compiles over 600,000 georeferenced species observations from the Global Biodiversity Information Facility (GBIF), processed using machine learning and rigorous quality control. Unlike traditional maps that focus mainly on vertebrates, this database includes plants, invertebrates, fungi, and other species, providing a more comprehensive picture of biodiversity.
 

Scalable Corridor Identification

Using this database, we developed a scalable methodology that overlays high-resolution species distribution maps with national road networks. This approach identifies road corridors where biodiversity is at high risk and highlights areas where infrastructure development could have significant ecological impacts. Case studies from the Philippines and Sub-Saharan Africa reveal that biodiversity-critical corridors are limited in number and spatially concentrated, making it possible to focus protection efforts where they will have the greatest impact.
 

Prioritizing Biodiversity

To guide these efforts, our framework classifies species into four priority groups based on two criteria: the size of their occurrence region and whether they are endemic, meaning found solely within the borders of one country. Endemic species with small geographic ranges receive the highest priority, as they are most vulnerable to habitat loss and other threats. By overlaying these species maps with a global grid, we produce high-resolution species count maps across 190 countries. These maps help pinpoint biodiversity hotspots that are likely to intersect with proposed infrastructure projects.
 

Ecological Corridor Mapping

To guide infrastructure planning, we build road corridor networks using OpenStreetMap road data, forest cover from Tuanmu and Jetz (2014), and topographic data from MERIT-DEM. Road links are categorized by type, and corridors are widened in forested regions to reflect higher ecological sensitivity. We generate 2.5-km buffers around each road segment and exclude sections with slopes too steep for feasible construction. This method creates reproducible and realistic, ecologically informed corridor maps.
 

Mapping Species-Rich Corridors

By overlaying corridors with species distribution maps, we calculate species richness within each road corridor for each biodiversity priority group. Results are standardized and visualized, allowing easy comparisons within and across countries. Case studies from the Philippines and Sub-Saharan Africa show how the method identifies biodiversity-critical corridors at national and regional scales, helping planners target mitigation efforts.
 

Key Patterns for Planning

Several key findings emerge. Biodiversity within road corridors varies widely, both across and within countries. Endemic species often determine the location of high-priority corridors, which are typically limited in number and spatially concentrated. This means that protection efforts can be cost-effective if focused on these critical areas. For policymakers, the implication is clear: protecting biodiversity is achievable even with limited resources, provided efforts are targeted where they will have the greatest impact.
 

Aligning Roads with Biodiversity

Integrating biodiversity insights early in infrastructure planning can help countries meet both development and conservation goals. Our methodology enables timely identification of sensitive corridors, even in data-scarce regions, and is regularly updated as new species data emerge. This creates opportunities for governments, donors, and developers to design road networks that avoid or minimize biodiversity loss. As infrastructure expands across the global South, this data-driven, scalable approach offers a practical path to align infrastructure development with biodiversity protection.

Our approach provides a flexible framework that combines a comprehensive database with a practical methodology, allowing policymakers and planners to tailor their strategies to specific needs. Users can select species of interest, apply custom criteria to identify those most at risk, and incorporate locally sourced biodiversity data to guide infrastructure decisions. By integrating detailed, location-specific biodiversity data into road corridor planning, countries can ensure that infrastructure investments are development-oriented and protect biodiversity. Leveraging advanced data and analytics, planners can identify areas where infrastructure development poses the greatest threats to vulnerable species and habitats and take action to mitigate these risks.

^{Our Key Roads Database is available on World Bank’s Development Data Hub.}

^{For methodology and applications, see WPS 11238: Biodiversity Guidance for Road Corridor Investments: Mobilizing New Data from the Global Biodiversity Information Facility.}

^{If you are interested in understanding more about the species’ occurrence region maps, please see: Revisiting Global Biodiversity: A Spatial Analysis of Species Occurrence Data from the Global Biodiversity Information Facility, World Bank Policy Research Working Paper 10821.}

^{We gratefully acknowledge funding from the Global Data Facility for the research.}