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author:

Leng, Song (Leng, Song.) [1] | Huete, Alfredo (Huete, Alfredo.) [2] | Cleverly, Jamie (Cleverly, Jamie.) [3] | Gao, Sicong (Gao, Sicong.) [4] | Yu, Qiang (Yu, Qiang.) [5] | Meng, Xianyong (Meng, Xianyong.) [6] | Qi, Junyu (Qi, Junyu.) [7] | Zhang, Rongrong (Zhang, Rongrong.) [8] | Wang, Qianfeng (Wang, Qianfeng.) [9] (Scholars:王前锋)

Indexed by:

EI SCIE

Abstract:

Satellite-estimated solar-induced chlorophyll fluorescence (SIF) is proven to be an effective indicator for dynamic drought monitoring, while the capability of SIF to assess the variability of dryland vegetation under water and heat stress remains challenging. This study presents an analysis of the responses of dryland vegetation to the worst extreme drought over the past two decades in Australia, using multi-source spaceborne SIF derived from the Global Ozone Monitoring Experiment-2 (GOME-2) and TROPOspheric Monitoring Instrument (TROPOMI). Vegetation functioning was substantially constrained by this extreme event, especially in the interior of Australia, in which there was hardly seasonal growth detected by neither satellite-based observations nor tower-based flux measurements. At a 16-day interval, both SIF and enhanced vegetation index (EVI) can timely capture the reduction at the onset of drought over dryland ecosystems. The results demonstrate that satellite-observed SIF has the potential for characterizing and monitoring the spatiotemporal dynamics of drought over water-limited ecosystems, despite coarse spatial resolution coupled with high-retrieval noise as compared with EVI. Furthermore, our study highlights that SIF retrieved from TROPOMI featuring substantially enhanced spatiotemporal resolution has the promising capability for accurately tracking the drought-induced variation of heterogeneous dryland vegetation.

Keyword:

dryland EVI extreme drought SIF TROPOMI

Community:

  • [ 1 ] [Leng, Song]Fuzhou Univ, Coll Environm & Safety Engn, Fujian Prov Key Lab Remote Sensing Soil Eros, Fuzhou 350116, Peoples R China
  • [ 2 ] [Zhang, Rongrong]Fuzhou Univ, Coll Environm & Safety Engn, Fujian Prov Key Lab Remote Sensing Soil Eros, Fuzhou 350116, Peoples R China
  • [ 3 ] [Wang, Qianfeng]Fuzhou Univ, Coll Environm & Safety Engn, Fujian Prov Key Lab Remote Sensing Soil Eros, Fuzhou 350116, Peoples R China
  • [ 4 ] [Leng, Song]Univ Technol Sydney, Sch Life Sci, Ultimo, NSW 2007, Australia
  • [ 5 ] [Huete, Alfredo]Univ Technol Sydney, Sch Life Sci, Ultimo, NSW 2007, Australia
  • [ 6 ] [Yu, Qiang]Univ Technol Sydney, Sch Life Sci, Ultimo, NSW 2007, Australia
  • [ 7 ] [Cleverly, Jamie]James Cook Univ, Coll Sci & Engn, Cairns, Qld 4878, Australia
  • [ 8 ] [Gao, Sicong]CSIRO, Land & Water, Adelaide, SA 5064, Australia
  • [ 9 ] [Yu, Qiang]Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Xianyang 712100, Peoples R China
  • [ 10 ] [Meng, Xianyong]Nanjing Univ Informat Sci & Technol, Sch Atmospher Phys, Nanjing 210044, Peoples R China
  • [ 11 ] [Qi, Junyu]Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20740 USA
  • [ 12 ] [Wang, Qianfeng]Minist Educ China, Key Lab Spatial Data Min & Informat Sharing, Fuzhou 350116, Peoples R China

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Source :

REMOTE SENSING

ISSN: 2072-4292

Year: 2022

Issue: 7

Volume: 14

5 . 0

JCR@2022

5 . 0 0 0

JCR@2022

ESI Discipline: GEOSCIENCES;

ESI HC Threshold:38

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 24

SCOPUS Cited Count: 24

ESI Highly Cited Papers on the List: 1 Unfold All

  • 2023-1

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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