首页|Spring and autumn phenology across the Tibetan Plateau inferred from normalized difference vegetation index and solar-induced chlorophyll fluorescence

Spring and autumn phenology across the Tibetan Plateau inferred from normalized difference vegetation index and solar-induced chlorophyll fluorescence

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  • NETL
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  • 万方数据
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Plant phenology is a key parameter for accurately modeling eco-system dynamics.Limited by scarce ground observations and ben-efiting from the rapid growth of satellite-based Earth observations,satellite data have been widely used for broad-scale phenology studies.Commonly used reflectance vegetation indices represent the emergence and senescence of photosynthetic structures(leaves),but not necessarily that of photosynthetic activities.Leveraging data of the recently emerging solar-induced chlorophyll fluorescence (SIF) that is directly related to photosynthesis,and the traditional MODIS Normalized Difference Vegetation Index (NDVI),we investigated the similarities and differences on the start and end of the growing season (SOS and EOS,respectively) of the Tibetan Plateau.We found similar spatiotemporal patterns in SIF-based SOS(SOSSIF) and NDVl-based SOS (SOSNDVI).These spatial patterns were mainly driven by temperature in the east and by precipitation in the west.Yet the two satellite products produced different spatial patterns in EOS,likely due to their different climate dependencies.Our work demonstrates the value of big Earth data for discovering broad-scale spatiotemporal patterns,especially on regions with scarce field data.This study provides insights into extending the definition of phenology and fosters a deeper understanding of ecosystem dynamics from big data.

SIFNDVIphenologyphotosynthesisbig dataclimate changeTibetan plateau

Fandong Meng、Ling Huang、Anping Chen、Yao Zhang、Shilong Piao

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Sino-French Institute for Earth System Science,College of Urban and Environmental Sciences,Peking University,Beijing,China

Department of Biology and Graduate Degree Program in Ecology,Colorado State University,Fort Collins,CO,USA

Climate and Ecosystem Science Division,Lawrence Berkeley National Laboratory,Berkeley,CA,USA

This study was supported by the National Natural Science Foundation of ChinaThis study was supported by the National Natural Science Foundation of Chinaby the Second Tibetan Plateau Scientific Expedition and Research Program

4186113403641988101Grant 2019QZKK0405

2021

地球大数据(英文版)

地球大数据(英文版)

ISSN：
年,卷(期)：2021.5(2)
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