From Coast to Inland: Nonlinear and Temperature-Mediated Urbanization Effects on Vegetation Phenology in Shandong Province, China
Year: 2025
Type: article
Abstract: Urbanization exerts profound influences on vegetation phenology, but the nature of these impacts can differ markedly between coastal and inland regions due to distinct climatic and geographic settings. However, most studies have treated urban areas as spatially homogeneous and relied primarily on linear models, which limits our understanding of region-specific, nonlinear, and threshold-driven phenological responses. To address this gap, we examined Shandong Province, China, as a representative region encompassing both coastal and inland urban–rural gradients. Using satellite-derived EVI time series, we extracted the Start (SOS) and End (EOS) of the growing season and applied an XGBoost–SHAP framework to disentangle the relative contributions of multiple environmental drivers. In addition, we analyzed the relationships between phenology and land surface temperature (LST) along the urban–rural gradient to identify thermal pathways through which urbanization influences vegetation cycles. The results showed that: (1) significant regional variation in SOS and EOS was observed across Shandong Province; (2) in the context of urbanization, SOS advanced by 0.48 days/km, and EOS was delayed by 0.4 days/km from rural to urban areas; (3) temperature and LST influenced phenology in a nonlinear manner, with relationships varying across seasons and regions, and seasonal as well as geographical differences significantly affecting the intensity and pattern of phenological changes; and (4) the effects of nighttime and daytime LST on phenology differed substantially between inland and coastal areas. This study investigates the complex nonlinear relationships between temperature and vegetation phenology, offering a deeper understanding of vegetation’s influence on the global carbon cycle.
Source: Remote Sensing
DOI: 10.3390/rs17233833
Authors: Xianxin Meng, Zhenxiang Ling, Yingbiao Chen, Junyu Kuang, Lianchong Zhang, Zhifeng Wu, Zihao Zheng, Jinnian Wang
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,258
Award: G1984381014
OpenAlex ID: W4416764878
