The resilience paradox in transport corridors: Ecological thresholds, spatial spillovers, and infrastructure divergence in Tanzania

Abstract Across the Global South, transport corridor expansion increasingly exhibits a resilience paradox in which large-scale infrastructure investments fail to generate sustained regional convergence under conditions of ecological instability and climatic stress. Existing analytical approaches remain methodologically fragmented, often treating infrastructure systems as isolated physical assets while overlooking the spatial and environmental processes governing resilience. This study addresses this limitation through the Geospatial Engineering Informatics Framework (GEIF), operationalized across 2,680 standardized hexagonal units in Tanzania using longitudinal multi-source datasets spanning 2002–2022. By integrating multi-sensor Earth Observation data with a hybrid GeoAI–spatial econometric architecture, the framework evaluates spatial spillovers, ecological thresholds, and nonlinear infrastructure–environment interactions across major transport corridors. The results demonstrate strong explanatory performance (Pseudo R² = 0.8822) and significant spatial dependence (ρ = 0.417), confirming that regional development outcomes are shaped by interconnected spillover processes rather than isolated local effects. The analysis further identifies a critical ecological threshold (NDVI ≤ −0.8σ), beyond which infrastructure effectiveness declines substantially and spillover propagation weakens. In addition, a strong infrastructure–environment interaction effect (6.7576) indicates that economic returns are significantly amplified when infrastructure connectivity aligns with ecological stability. These findings demonstrate that infrastructure-led growth is fundamentally conditioned by environmental resilience rather than physical connectivity alone. Overall, the study advances infrastructure resilience theory by conceptualizing transport corridors as dynamic socio-ecological systems shaped by spatial interaction, ecological thresholds, and regional diffusion processes. By integrating Earth Observation, Spatial Durbin Modeling, and GeoAI diagnostics within a unified analytical framework, the research provides a scalable and spatially explicit foundation for anticipatory, threshold-informed infrastructure governance in climate-sensitive development corridors.