Response of vegetation phenology to urbanization in urban agglomeration areas: A dynamic urban–rural gradient perspective

城市化 物候学 植被(病理学) 地理 城市气候 自然地理学 环境科学 梯度分析 农村地区 生态学 生物 医学 病理 排序
作者
Zhenhuan Liu,Yi Zhou,Zhitao Feng
出处
期刊:Science of The Total Environment [Elsevier]
卷期号:864: 161109-161109 被引量:39
标识
DOI:10.1016/j.scitotenv.2022.161109
摘要

Being an important theme in global warming, the response of vegetation phenology to urbanization has become an increasing concern at both the local and global levels. Previous studies have focused on spatial or temporal responses across urban-rural gradients; thus, the influence of urbanization on vegetation phenology along the dynamic urbanization gradient has not been well quantified. In this study, we comprehensively analyzed the response of vegetation phenology to urbanization in the Guangdong-Hong Kong-Macao Greater Bay Area (GHM-GBA) from a dynamic urban-rural gradient perspective. The results show that the response of vegetation phenology to urbanization level has a distinct spatiotemporal difference across the urban-rural gradient. Compared to rural areas, the change rate of advancements in the start-of-season (SOS) in urban domains was 1.16 DOY/year and that of the end-of-season (EOS) was 0.63 days/year from 2001 to 2020. In the GHM-GBA region, 61.03 % of the remote sensing pixels showed an advancing trend for SOS and 55.75 % for EOS. Urbanization advanced the SOS and EOS but did not extend the growing season length, and the SOS and EOS were advanced by 7 and 6 days along the urban-to-rural gradient, respectively. For every 10 % increase in urbanization levels, the SOS and EOS advanced by 1.085 and 1.091 days across the urban-rural gradient, respectively; the spring land surface temperature (LST) advanced the SOS at a rate of 1.71 days/°C, while the autumn LST advanced the EOS at a rate of 1.88 days/°C. The phenological shift in the urban-rural gradient was more significant than that over time, which was mainly because of land surface warming under different urbanization levels. These quantitative findings are of great importance for understanding the complicated impacts of urbanization on vegetation phenology and for developing models to predict vegetation phenological changes under future urbanization.
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