Advances in Earth Science ›› 2021, Vol. 36 ›› Issue (1): 9-16. doi: 10.11867/j.issn.1001-8166.2021.006

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Advances in Remote Sensing Extraction of Vegetation Phenology and Its Driving Factors

Linli CUI 1( ), Jun SHI 1 , 2, Huaqiang DU 3   

  1. 1.Shanghai Ecological Forecasting and Remote Sensing Center,Shanghai 200030,China
    2.Key Laboratory of Cities Mitigation and Adaptation to Climate Change in Shanghai (CMACC),Shanghai 200030,China
    3.College of Environmental and Resource Sciences,Zhejiang A&F University,Lin'an Zhejiang 311300,China
  • Received:2020-10-28 Revised:2020-12-22 Online:2021-03-19 Published:2021-03-19
  • About author:CUI Linli (1975-), female, Changzhi City, Shanxi Province, Professor. Research areas include remote sensing of vegetation and the atmosphere. E-mail:
  • Supported by:
    the Open Research Fund Program of the State Key Laboratory of Subtropical Silviculture of Zhejiang A & F University "Spatiotemporal patterns of carbon cycle and their response on the extreme climate in subtropical forests"(KF2017-5);The Science and Technology Planning Project of Shanghai Municipality "Research on ecological environment monitoring and early warning based on remote sensing—Taking Yangtze River Delta integration demonstration zone as an example"(20232410100)

Linli CUI, Jun SHI, Huaqiang DU. Advances in Remote Sensing Extraction of Vegetation Phenology and Its Driving Factors[J]. Advances in Earth Science, 2021, 36(1): 9-16.

Phenology is considered as an important indicator for understanding the vegetation dynamics and the impact of climate change on ecosystem. It has significant influences on surface albedo, roughness, evapotranspiration, CO2 flux, and human activities. This study presents the progress on the phenology extraction methods based on satellite, and the driving factors of vegetation phenology dynamics. The key weaknesses in our current understanding of vegetation phenology in the context of climate change are also raised, including the difficulty in estimating the phenology of evergreen vegetation based on remote sensing directly from the perspective of leaf and canopy structure, the low comparability between satellite products and ground-based measurements due to the scale effect, the unclear synergistic mechanisms between climate factors (rainfall and day/night temperature) and urbanization, the lack of phenological products and models for specific vegetation types, as well as the inconsideration of lag effect of phenology. So, it is important to focus on the following four aspects in future research: the development of satellite phenology extraction methods for evergreen vegetation; the research on the mechanisms and forecast of climate change and extreme weather on phenology; the study of the impact of urbanization and vegetation types on phenology, together with their synergistic effects; the establishment of phenological model at community scale which considers precipitation, lag effect and scale effect.

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