Rapid urbanisation in arid environments often requires a trade-off between economic expansion and environmental stability, leading to uncoordinated or unsustainable development. This study proposes a pixel-based Coupling Coordination Degree (CCD) model that shifts analysis from coarse administrative statistics to fine-scale spatial diagnosis to quantitatively evaluate the relationship between environmental risk and urban economic vitality. The framework integrates multi-source remote sensing indices and was applied to Assiut City, a dense historic settlement in Egypt, and New Assiut City, a planned desert satellite city, for the years 2013, 2018, and 2023. A sensitivity analysis carried out to assess model uncertainty by assigning different weighting coefficients confirmed stability. The Coefficient of Variation (CV) for Assiut City remained low, ranging between 5.61% and 8.38%. New Assiut City showed moderate variation with CV values between 8.64% and 13.08%; initially, moderate sensitivity reflected the instability of the early construction phase, characterised by "Severe Imbalance." The analysis reveals different development paths. Assiut City exhibits environmental lock-in, characterised by stable coordination scores and a distinct ring of degradation at its peri-urban fringe. Conversely, New Assiut City demonstrates a positive transition with the rapid development of infrastructure, where nearly 45% of transitional areas improved to "Good Coordination”. This study proposes the CCD model as a scalable diagnostic open-source tool for data-scarce regions, enabling policymakers to identify specific spatial conflicts between urban growth and environmental risk to guide targeted resilient and sustainable planning.
Ahmed M.S. Mohammed (2026) studied this question.