Detecting Spatial Impacts of Violence through Remote Sensing: A Case Study of Conflict-Affected Regions in Central Mali

Abstract

This study investigates if socio-economic indicators can reliably be derived from remotely sensed data and can serve as proxies for detecting and monitoring the spatial impacts of the violent conflict in the Mopti region of Mali. Traditional conflict event databases - like the Armed Conflict Location & Event Data Project (ACLED) – provide point-based event data but often fail to capture gradual spatial shifts that occur when insurgent groups like Jama’at Nusrat al-Islam wal-Muslimin (JNIM) gain territorial control. This study addresses this gap by integrating geospatial intelligence (GEOINT) using remote sensing to track changes in cropland activity, night-time light emissions and changes in built-up area in the Mopti region between 2016 and 2023.
The methodology in this study consists of a multi-indicator approach in which natural environmental variability like seasonal rainfall is filtered out. This was done to ensure that the observed changes can be attributed to the conflict dynamics. Agricultural activity was analysed using the 3-Period TimeScan (3PTS) method, which uses Sentinel-2 NDVI data to visualize the agricultural cycle and makes it possible to identify land abandonment. Population displacements and economic stability were assessed through built-up area growth by using Impact Observatory’s Land Classification Land Use (LCLU) deep learning AI algorithms and NASA’s Black Marble night-time light radiance values. Different statistical methods were used to evaluate the relationship between these indicators and recorded conflict events in the ACLED event database.
The results of this study suggest that cropland activity serves as a useful indicator of violence-related spatial change, as demonstrated by the identification of villages like Bobosso and Doukoro. In these villages significant agricultural abandonment was directly linked to violent actions by insurgency actors. While a two-way fixed effects model indicated a correlation between night-time light fluctuations and conflict frequencies, this is caused by structural overfitting due to the fixed effect dummies. The variations in night-time light also suggest a broader institutional grid instability due to maintenance issues and fuel shortages. While horizontal urban built-up area growth is evident within the study areas cities and timeframe, a predictive relationship between IDP numbers and built-up area growth could not be established in statistically significant terms. Qualitative research confirmed that an influx of displaced persons does not immediately contribute to an expanded built-up area footprint. IDPs initially find shelter with friends or family or in other communal existing structures.

Popular Abstract

The ongoing conflict in Mali has seen insurgent groups like Jama'at Nusrat al-Islam wal-Muslimin (JNIM) – a prominent Al-Qaeda affiliate- getting more influence and grip over an increasing amount of territory. These areas become dangerous and therefore it is often impossible for researchers and aid workers to visit. As a result collecting data on the ground has become nearly impossible in those areas. As the conflict results in direct and indirect changes, this study assesses if satellite imagery and geospatial measurements can serve as proxies for this data and can help us monitor the progression of the conflict and understand its human costs from afar.
This study focuses on three key indicators: cropland activity, night-time light brightness and physical expansion of urban areas. Natural environmental factors like rainfall were filtered out, to ensure that the observed changes were truly caused by conflict.
The most striking results were found looking at cropland activity. By measuring the greenness of croplands during the 60 to 100-day growing season, the study identified significant land abandonment. In villages like Bobosso and Doukoro agricultural activity plummeted as a direct result of violence by insurgent actors. Statistically, the study confirmed that violence against civilians as recorded in conflict event databases is a powerful predictor of whether fields will be left unplanted.
The study found not all indicators to be as equally straightforward. Night-time lights can reflect economic activity, but its reliability as a conflict indicator as tested in this specific study showed to be limited. Although expansion of urban areas was clearly visible during the time period of this study, it could not be statistically linked to occurring conflict events or number of displaced persons. It is assumed that displaced people often arrive with few resources and it takes considerable time for them to re-establish their livelihoods and contribute to the physical growth of an urban area.
By applying these views from space, it is possible to create a clearer picture of what is happening in areas under siege, even when we cannot visit them in person. This "spatial triage" approach provides a vital tool for humanitarian organizations, helping them prioritize which areas are in most desperate need of assistance.

• author: van Diest, Johannes Cornelis Wilhelmus
• supervisor: David Tenenbaum
• organization: Department of Earth and Environmental Sciences (MGeo)
• course: GISM01 20261
• year: 2026
• type: H2 - Master's Degree (Two Years)
• subject: Earth and Environmental Sciences
• keywords: Geography, Geographical Information Systems (GIS), Mali, Remote Sensing, Human Security, Conflict
• publication/series: Master Thesis in Geographical Information Science
• report number: 215
• language: English
• id: 9241761
• date added to LUP: 2026-06-22 13:52:54
• date last changed: 2026-06-22 13:52:54