Articles | Volume 18, issue 3
https://doi.org/10.5194/essd-18-2371-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-2371-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Toward better conservation: a spatial analysis of species occurrence data from the Global Biodiversity Information Facility
Susmita Dasgupta
Development Economics Research Group, World Bank Group, 1818 H Street, Washington DC 20433, USA
Brian Blankespoor
CORRESPONDING AUTHOR
Development Economics Data Group, World Bank Group, 1818 H Street, Washington DC 20433, USA
David Wheeler
Development Economics Data Group, World Bank Group, 1818 H Street, Washington DC 20433, USA
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Yating Ru, Brian Blankespoor, Ulrike Wood-Sichra, Timothy S. Thomas, Liangzhi You, and Erwin Kalvelagen
Earth Syst. Sci. Data, 15, 1357–1387, https://doi.org/10.5194/essd-15-1357-2023, https://doi.org/10.5194/essd-15-1357-2023, 2023
Short summary
Short summary
Economic statistics are frequently produced at an administrative level that lacks detail to examine development patterns and the exposure to natural hazards. This paper disaggregates national and subnational administrative statistics of agricultural GDP into a global dataset at the local level using satellite-derived indicators. As an illustration, the paper estimates that the exposure of areas with extreme drought to agricultural GDP is USD 432 billion, where nearly 1.2 billion people live.
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Short summary
This study leverages recent advances in machine-based pattern recognition to estimate occurrence maps for over 600,000 species, using georeferenced data from the Global Biodiversity Information Facility (GBIF). A pilot application for priority-setting identifies 30 nations that host nearly 80 percent of threatened species with small ranges limited to a single country. The algorithms are designed for rapid map updates and estimating new maps as growth in GBIF species occurrence reports continues.
This study leverages recent advances in machine-based pattern recognition to estimate occurrence...
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