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author:

Leng, Song (Leng, Song.) [1] | Huete, Alfredo (Huete, Alfredo.) [2] | Cleverly, Jamie (Cleverly, Jamie.) [3] | Yu, Qiang (Yu, Qiang.) [4] | Zhang, Rongrong (Zhang, Rongrong.) [5] | Wang, Qianfeng (Wang, Qianfeng.) [6] (Scholars:王前锋)

Indexed by:

EI Scopus SCIE

Abstract:

Accurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) and the Enhanced Vegetation Index (EVI) along the North Australian Tropical Transect (NATT). Substantial impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation are observed by both SIF and EVI, especially in the arid/semiarid interior of Australia without detectable seasonality in the dry year of 2018-2019. The greenness-based vegetation index (EVI) can more accurately capture the seasonal and interannual variation in vegetation production than SIF (EVI r(2): 0.47 similar to 0.86, SIF r(2): 0.47 similar to 0.78). However, during the brown-down periods, the rate of decline in EVI is evidently slower than that in SIF and in situ measurement of gross primary productivity (GPP), due partially to the advanced seasonality of absorbed photosynthetically active radiation. Over 70% of the variability of EVI (except for Hummock grasslands) and 40% of the variability of SIF (except for shrublands) can be explained by the water-related drivers (rainfall and soil moisture). By contrast, air temperature contributed to 25 similar to 40% of the variability of the effective fluorescence yield (SIFyield) across all biomes. In spite of high retrieval noises and variable accuracy in phenological metrics (MAE: 8 similar to 60 days), spaceborne SIF observations, offsetting the drawbacks of greenness-based phenology products with a potentially lagged end of the season, have the promising capability of mapping and characterizing the spatiotemporal dynamics of dryland vegetation phenology.

Keyword:

EVI NATT phenology SIF

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, Fac Sci, Ultimo, NSW 2007, Australia
  • [ 5 ] [Huete, Alfredo]Univ Technol Sydney, Fac Sci, Ultimo, NSW 2007, Australia
  • [ 6 ] [Cleverly, Jamie]James Cook Univ, Coll Sci & Engn, Cairns, Qld 4878, Australia
  • [ 7 ] [Yu, Qiang]Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Xianyang 712100, Peoples R China
  • [ 8 ] [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: 13

Volume: 14

5 . 0

JCR@2022

4 . 2 0 0

JCR@2023

ESI Discipline: GEOSCIENCES;

ESI HC Threshold:51

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 23

SCOPUS Cited Count: 23

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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