Monitoring long‐term vegetation dynamics over the Yangtze River Basin, China, using multi‐temporal remote sensing data

Author:

Fu Jing1234ORCID,Liu Jianxiong1ORCID,Qin Jianxin3,Yang Liguo124,Zhang Zhongbo5,Deng Yunyuan124,Hu Yong1,Su Baoling1

Affiliation:

1. College of Geography and Tourism, Hengyang Normal University Hengyang Hunan China

2. Hunan National‐Local Joint Engineering Laboratory on Digital Preservation and Innovative Technologies for the Culture of Traditional Villages and Towns Hengyang Normal University Hengyang Hunan China

3. Hunan Key Laboratory of Geospatial Big Data Mining and Application Hunan Normal University Changsha Hunan China

4. International Centre on Space Technologies for Natural and Cultural Heritage (HIST) under the Auspices of UNESCO, Hengyang Base Hengyang Hunan China

5. Hunan Weather Modification Office Changsha Hunan China

Abstract

AbstractVegetation plays a crucial role in nature, with intricate interactions between it and the geographical environment. The Yangtze River Basin (YRB) refers to the third largest river basin globally and an essential ecological security barrier in China. Monitoring vegetation dynamics in the basin is of profound significance for addressing climate change, soil erosion, and biodiversity loss in the basin's ecosystems. Here, we investigate the spatiotemporal variations of vegetation at both the basin and land cover scales in the YRB from 2000 to 2020. We elucidate the determinants driving the changes and explore future normalized difference vegetation index (NDVI) trends. The results indicate that NDVI in the YRB increased at a rate of 0.0032 year−1 (p < 0.01) over the past 21 years, and it is anticipated to maintain an upward trend in the future. Regions in the upper and middle reaches of the YRB demonstrated higher NDVI, whereas regions in the headwater area and the lower reaches showed lower NDVI. Significant vegetation improvement was primarily concentrated in the central part of the basin, while noticeable vegetation degradation was observed in the eastern region. Temperature and wind speed were identified as the primary controlling factors affecting vegetation greenness. Global‐scale climate oscillations played a significant role in driving periodic variations in NDVI, with La Niña events tending to increase NDVI, while El Niño events hindered its rise. Land cover types were influenced by long‐term interactions between natural factors and human activities, although short‐term vegetation variations might be more affected by the latter. Our findings provide valuable insights into the mechanisms behind vegetation variability driven by multiple variables, and the strong vegetation carbon sink capacity advances the conservation and development of ecosystems.

Publisher

Wiley

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