Research for Good

Our team includes researchers at world-leading universities who are actively publishing innovative peer-reviewed scientific research that we think may offer new solutions for important challenges that you are passionate about.

New study uses digital data to monitor unprecedented displacement in Gaza in near real time

A new study by Oxford researchers from the Leverhulme Centre for Demographic Science (LCDS), Edith Darin, Ridhi Kashyap, and Douglas Leasure, introduces a novel approach to tracking population movements in conflict zones, offering a near real-time view of forced displacement in the Gaza Strip. The research, published in Population and Development Review, leverages high-frequency digital data to provide one of the most detailed accounts of population dynamics during the first six months of the Israel–Hamas war.

Darin, E., Kashyap, R., & Leasure, D. R. (2026). Leveraging High-Frequency Digital Data to Analyze Forced Displacement Dynamics: A Case Study from the Gaza Strip. Population and Development Review. https://doi.org/10.1111/padr.70064

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Nowcasting daily population displacement in Ukraine through social media advertising data

In collaboration with the UN International Organization for Migration (IOM), this paper developed a method to estimate populations in near real-time for humanitarian response in Ukraine when other data sources were not available.

Leasure DR, Kashyap R, Rampazzo F, Dooley CA, Elbers B, Bondarenko M, et al. 2023. Population and Development Review, 49:231-254. doi:10.1111/padr.12558

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High-resolution population mapping from sparse survey data and building footprints in DRC

By linking household surveys to high-resolution building footprints derived from recent satellite imagery, this project estimated population sizes by age and sex for every 100-m grid cell in the Democratic Republic of Congo.

Boo G, Darin E, Leasure DR, Dooley CA, Chamberlain HR, et al. 2022. Nature Communications, 13(1):1330. doi:10.1038/s41467-022-29094-x

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Mapping hard-to-reach communities in Colombia by linking high-tech satellite data with low-tech community workshops

Working with DANE, we developed a method linking satellite remote sensing of buildings with information from community workshops and partial census data to strengthen representation of difficult-to-access communities.

Sanchez-Cespedes LM, Leasure DR, Tejedor-Garavito N, et al. 2024. Population Studies, 78(1):3-20. doi:10.1080/00324728.2023.2190151

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National population mapping from sparse survey data in Nigeria while accounting for uncertainty

This paper developed a Bayesian statistical method to provide up-to-date population estimates for every 100-m grid cell across Nigeria, where census timing and quality created major data gaps.

Leasure DR, Jochem WC, Weber EM, Seaman V, Tatem AJ. 2020. Proceedings of the National Academy of Sciences, 117(39):24173-24179. doi:10.1073/pnas.1913050117

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Classifying settlement types from multi-scale spatial patterns of building footprints

This paper introduced a method to identify and map settlement types from building patterns observed via satellite remote sensing, supporting urban analytics and planning applications.

Jochem WC, Leasure DR, Pannell O, Chamberlain HR, Jones P, Tatem AJ. 2021. Environment and Planning B, 48(5):1161-1179. doi:10.1177/2399808320921208

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Forecasting trout populations using satellite remote sensing to assess extinction risk

This paper developed a Bayesian population forecasting approach using remotely-sensed habitat and climate characteristics to estimate extinction risk for isolated Lahontan cutthroat trout populations.

Leasure DR, Wenger SJ, Chelgren ND, et al. 2019. Ecology, 100(1):e02538. doi:10.1002/ecy.2538

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