From Perception to Prediction: Modelling Pastoral (Im)Mobility in the West Sahel

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• Aline Van Driessche, University of Cambridge
• Friday 07 November 2025, 13:00-14:00
• Room GS15 at the William Gates Building and on Zoom: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon .

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Abstract

Modelling climate-induced mobility is one of the most pressing challenges in the Central Sahel and neighbouring regions, where environmental stressors such as droughts, extreme temperatures, and erratic rainfall are increasingly displacing vulnerable communities. This is especially true for pastoralists, a type of herders that move across landscapes with their livestock in search of fresh forage and water, while allowing the land to recover. Changing climatic circumstances disrupt the availability of these resources, diminishing crop yields and forcing pastoralists to adjust their traditional routes in search of suitable grazing areas. Although climate models provide reasonably reliable projections of future climate conditions such temperature and precipitation patterns, they do not directly reveal how such environmental shifts shape human decisions. Similarly, many migration models exist, but few capture the combined environmental, socio-cultural and behavioural mechanisms that shape pastoral mobility.

This research presents a novel approach to modelling mobility, introducing a conceptual framework that integrates perception-based knowledge with data-driven techniques to better understand the relationship between climate variability and pastoral movements. Early hypotheses are informed by conversations with pastoralists, offering insights into locally grounded decision rules. Complementing this, initial modelling efforts aim to identify and predict key mediating variables, such as pasture availability, and link them to both climate conditions and mobility outcomes. Establishing these connections is a critical step toward translating qualitative understanding into quantitative, predictive analytics.

Bio

Aline is a 2nd year PhD student co-supervised by Emily So and Emily Shuckburgh in the Departments of Architecture and Computer Science at the University of Cambridge. Her research sits at the intersection of data science, urban planning and climate adaptation, exploring how remote-sensing and data-drive approaches can support responses to humanitarian crises.

This talk is part of the Energy and Environment Group, Department of CST series.

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