The Sino-Congolese SICOMINES agreement (2008) is a prime example of a “resources-for-infrastructure” deal, but assessing its impact has been notoriously difficult due to the structural opacity surrounding Chinese-funded projects in Africa. This study uses the SICOMINES agreement as a case study to demonstrate how Geographic Information Systems (GIS) and remote sensing can systematically address these epistemological challenges. Focusing on the Munkamba–Mbuji-Mayi road in the Kasaï Oriental province of the Democratic Republic of the Congo, a corridor explicitly promised under the agreement, the research applies a longitudinal GIS methodology based on counterfactual scenarios, drawing on USGS Landsat satellite imagery and WorldPop demographic data. Road conditions and accessibility are analyzed across four temporal scenarios: a pre-agreement baseline (2008), a deterioration phase (2023), an initial restoration phase (2025), and a normative counterfactual representing road conditions if SICOMINES' infrastructure commitments had been fulfilled on schedule. Through road classification and accessibility modelling, the study quantifies travel times and the affected population across the different scenarios, linking infrastructure implementation to spatial inequality in Kasaï Oriental. Methodologically, the study contributes to Africa-China research by validating GIS and remote sensing as a rigorous and replicable approach to studying opaque infrastructure-for-resources deals, with broader implications for accountability and renegotiation frameworks.
GIS Contribution To Africa-China Studies: The Case Of The Sicomines Agreement In The DRC
BARGELLINI, CHIARA
2025/2026
Abstract
The Sino-Congolese SICOMINES agreement (2008) is a prime example of a “resources-for-infrastructure” deal, but assessing its impact has been notoriously difficult due to the structural opacity surrounding Chinese-funded projects in Africa. This study uses the SICOMINES agreement as a case study to demonstrate how Geographic Information Systems (GIS) and remote sensing can systematically address these epistemological challenges. Focusing on the Munkamba–Mbuji-Mayi road in the Kasaï Oriental province of the Democratic Republic of the Congo, a corridor explicitly promised under the agreement, the research applies a longitudinal GIS methodology based on counterfactual scenarios, drawing on USGS Landsat satellite imagery and WorldPop demographic data. Road conditions and accessibility are analyzed across four temporal scenarios: a pre-agreement baseline (2008), a deterioration phase (2023), an initial restoration phase (2025), and a normative counterfactual representing road conditions if SICOMINES' infrastructure commitments had been fulfilled on schedule. Through road classification and accessibility modelling, the study quantifies travel times and the affected population across the different scenarios, linking infrastructure implementation to spatial inequality in Kasaï Oriental. Methodologically, the study contributes to Africa-China research by validating GIS and remote sensing as a rigorous and replicable approach to studying opaque infrastructure-for-resources deals, with broader implications for accountability and renegotiation frameworks.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/111973