Multiscale effects of climate change and anthropogenic activity on vegetation dynamics in Guangdong-Hong Kong-Macao greater bay area

As a crucial indicator of terrestrial ecosystems, vegetation plays a significant role in reflecting the interactions and coupled coordination between anthropogenic activities and natural ecosystems. Understanding the drivers of vegetation change is paramount for achieving sustainable development of socio-ecological systems. Climate change and anthropogenic activities are the primary influencing factors of vegetation change. Given the current research gap in understanding the impacts of climate factors and anthropogenic activities on vegetation change at different temporal scales within the rapid urbanization process of urban agglomerations, based on the Normalized Difference Vegetation Index (NDVI), nighttime light intensity and climatic factors, this paper explores the spatial-temporal distribution of vegetation change trend through trend analysis, and uses empirical mode decomposition and partial correlation analysis to analyzes the correlation between vegetation change and climate factors and anthropogenic activities at different time scales. The relative contributions of climate factors and anthropogenic activities to vegetation change were analyzed by residual trend method. The results reveal that: NDVI exhibits an increasing trend in most regions, Land Surface Temperature (LST) has significantly increased, and the intensity of anthropogenic activities has significantly intensified in half of the regions. The correlation between vegetation change and anthropogenic activities and climate factors shows spatiotemporal heterogeneity, with significantly correlated areas increasing with the extension of temporal scales. A strong negative correlation between vegetation change and anthropogenic activity intensity is mainly distributed in the core urban areas of various cities. The regions where vegetation change is significantly negatively correlated with LST are primarily located in Zhaoqing, Jiangmen, and Huizhou. Increases in precipitation and sunshine duration promote vegetation growth. Vegetation change is primarily influenced by anthropogenic activities in the short term. In the long-term trend, most areas are dominated by climate factors, and vegetation changes caused by anthropogenic activities are mainly distributed in the core areas of cities. These findings contribute to a comprehensive understanding of the driving mechanisms of vegetation dynamic changes in the context of urbanization and provide a scientific basis for formulating more effective urban ecological management and sustainable development strategies.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2025-05-15
DOI
https://doi.org/10.3389/fenvs.2025.1574870
Citations
2
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
2.60
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article

Multiscale effects of climate change and anthropogenic activity on vegetation dynamics in Guangdong-Hong Kong-Macao greater bay area

Quanming Yang, Yuanyuan Wang, Yun Tang
2 citations
Frontiers in Environmental Science
Remote Sensing and Land Use
2.60
article

Multiscale effects of climate change and anthropogenic activity on vegetation dynamics in Guangdong-Hong Kong-Macao greater bay area

Quanming Yang, Yuanyuan Wang, Yun Tang
article en
2 citations

Abstract

As a crucial indicator of terrestrial ecosystems, vegetation plays a significant role in reflecting the interactions and coupled coordination between anthropogenic activities and natural ecosystems. Understanding the drivers of vegetation change is paramount for achieving sustainable development of socio-ecological systems. Climate change and anthropogenic activities are the primary influencing factors of vegetation change. Given the current research gap in understanding the impacts of climate factors and anthropogenic activities on vegetation change at different temporal scales within the rapid urbanization process of urban agglomerations, based on the Normalized Difference Vegetation Index (NDVI), nighttime light intensity and climatic factors, this paper explores the spatial-temporal distribution of vegetation change trend through trend analysis, and uses empirical mode decomposition and partial correlation analysis to analyzes the correlation between vegetation change and climate factors and anthropogenic activities at different time scales. The relative contributions of climate factors and anthropogenic activities to vegetation change were analyzed by residual trend method. The results reveal that: NDVI exhibits an increasing trend in most regions, Land Surface Temperature (LST) has significantly increased, and the intensity of anthropogenic activities has significantly intensified in half of the regions. The correlation between vegetation change and anthropogenic activities and climate factors shows spatiotemporal heterogeneity, with significantly correlated areas increasing with the extension of temporal scales. A strong negative correlation between vegetation change and anthropogenic activity intensity is mainly distributed in the core urban areas of various cities. The regions where vegetation change is significantly negatively correlated with LST are primarily located in Zhaoqing, Jiangmen, and Huizhou. Increases in precipitation and sunshine duration promote vegetation growth. Vegetation change is primarily influenced by anthropogenic activities in the short term. In the long-term trend, most areas are dominated by climate factors, and vegetation changes caused by anthropogenic activities are mainly distributed in the core areas of cities. These findings contribute to a comprehensive understanding of the driving mechanisms of vegetation dynamic changes in the context of urbanization and provide a scientific basis for formulating more effective urban ecological management and sustainable development strategies.

Frontiers in Environmental ScienceVol. 13
Suzhou University of Science and Technology (CN), Soochow University (CN), Huainan Normal University (CN), Anhui and Huaihe River Institute of Hydraulic Research (CN)
Openalex Percentile: Top 12%
Remote Sensing and Land Use
2.60
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