Work

Assessing the impacts of local urban development intensity on vegetation phenology: Mechanisms and future scenario simulation

Year: 2026

Type: article

Abstract: Urbanization reshapes vegetation phenology through interacting environmental pathways, yet the individual and combined associations of local urban-development characteristics with phenological dynamics remain unresolved. Here, we develop the Local Urban Development Intensity Characteristics (LUDICs) framework, integrating nighttime-light intensity (NTL), the blue-to-red light ratio (BRR), and building volume (BV). The framework extends urban phenology assessment from broad spatial contrasts to component-specific analysis of phenological timing, spatial coherence, and future responses across climatic settings. Using satellite-derived phenology, nighttime-light imagery, and building data for 30 Chinese cities, we combined spatial statistics and covariate-adjusted partial correlations with interpretable machine-learning analysis. An eight-scenario factorial design evaluated the individual and combined effects of LUDICs under three socioeconomic pathways for 2030–2100. Urban areas exhibited lower spatial coherence of growing-season length than surrounding non-urban areas, with 53.7% of discontinuity hotspots located along urban–non-urban edges. In monsoon-dominated cities, higher BRR was associated with longer growing seasons, whereas higher NTL and BV were associated with shorter seasons; BRR and NTL showed opposite associations in continental-dominated cities. LUDICs accounted for 20.4–31.4% of model-explained phenological variation. Model interpretation revealed threshold-like shifts for BRR and NTL, whereas BV contributions gradually changed from positive to negative and strengthened toward both extremes. NTL-inclusive scenarios produced the largest projected changes, while the established LUDIC background accounted for most late-century responses. These findings provide a component-specific basis for evaluating urban-development alternatives and support climate-adaptive planning and environmental assessment.

Source: Environmental Impact Assessment Review

DOI: 10.1016/j.eiar.2026.108696