A regime-based framework for identifying coupled urban environmental dynamics from remote sensing time series

Urban environmental change results from complex interactions among vegetation dynamics, urban expansion, and thermal processes. However, conventional remote sensing approaches often evaluate these components independently, limiting the identification of heterogeneous urban transformation pathways. This study proposes a data-driven regime-based framework to identify and couple ecological and thermal–urban dynamics in a semi-arid urban system, covering the urban core and surrounding detached regions during 2017–2025. The framework integrates Sentinel-2-based vegetation health trajectories derived from NDVI (greenness/productivity), PSRI (senescence), and MSI (moisture stress) with Random Forest-downscaled Landsat 8 thermal dynamics and urban growth indicators using the Regime of Combined Urban Growth and UHI Dynamics (RCGUD) classification. Temporal changes were quantified using Mann–Kendall trend analysis and Theil–Sen slope estimation, while PCA-based weighting integrated multiple vegetation dimensions. The spatial coupling between vegetation regimes and RCGUD was evaluated using chi-square statistics, Cramer's V, and Pearson residual analysis. The results revealed distinct urban evolution pathways, including Intensive Growth (Warming) associated with vegetation degradation and thermal intensification, Ecological Recovery (Cooling) associated with vegetation improvement and reduced thermal intensity, and warming processes independent of recent physical expansion. The spatial correspondence between vegetation regimes and RCGUD was statistically significant and regime-specific (χ 2 = 619,507.19, p < 0.001; Cramer's V = 0.555). Sensitivity analysis using a 90% significance threshold reduced the overall strength of association to Cramer's V = 0.369, while the principal spatial co-occurrence pathways remained comparatively consistent. These findings indicate that thermal evolution was not necessarily synchronized with recent physical expansion and could occur under both degrading and stable or improving vegetation conditions. The proposed framework provides a potentially transferable approach for identifying coupled urban environmental trajectories and can support environmental screening and further assessment of areas exhibiting contrasting combinations of urban growth, thermal change, and vegetation dynamics. Further operational intervention prioritization would require additional information on socioeconomic vulnerability, population exposure, adaptive capacity, and intervention effectiveness.