First assessment of optical and microwave remotely sensed vegetation proxies in monitoring aboveground carbon in tropical Asia

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • Tianxiang Cui
  • Lei Fan
  • Philippe Ciais
  • Fensholt, Rasmus
  • Frédéric Frappart
  • Stephen Sitch
  • Jérome Chave
  • Zhongbing Chang
  • Xiaojun Li
  • Mengjia Wang
  • Xiangzhuo Liu
  • Mingguo Ma
  • Jean Pierre Wigneron

Tropical Asia has shown a strong greening trend in recent years. However, detailed knowledge about changes in carbon stocks remain uncertain as only few studies have used remotely sensed vegetation products for monitoring spatial and temporal changes of aboveground live biomass carbon (AGC) in that region. This study aims at evaluating optical- and microwave-based vegetation proxies (i.e., LAI, percent tree cover (PTC), L−/X-/C-band vegetation optical depths (VOD)) for understanding the spatio-temporal variations of tropical Asian AGC between 2013 and 2019. Our results indicated that the spatial distributions of L-VOD and PTC were highly spatially correlated with four benchmark AGC maps used for comparison (R > 0.79 and R > 0.75, respectively). By employing L-VOD as the reference data in assessing AGC dynamics, the X-/C-VOD showed advantages in capturing AGC changes for low-medium (20–40 Mg C/ha) carbon density vegetation, respectively, while other vegetation proxies showed limited capabilities. All proxies presented limitations in tracking AGC dynamics at high AGC density (> 60 Mg C/ha). Tropical Asian AGC stocks estimated using the L-VOD product indicated that tropical Asia accumulated carbon in biomass at a rate of +44+39+53 Tg C/yr between 2013 and 2019. This small sink is dominated by non-forest biomes (65.9%). The non-forest regions in southern India, southwest China, and southern Vietnam and southwest China showed a continuous AGC increase while forests in northern Laos, Malaysia, and central Indonesia experienced continuous decreases between 2013 and 2019 caused by deforestation.

OriginalsprogEngelsk
Artikelnummer113619
TidsskriftRemote Sensing of Environment
Vol/bind293
Antal sider19
ISSN0034-4257
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
This work was supported by the National Natural Science Foundation of China ( 42201364 , 42171339 ), Natural Science Foundation of Jiangsu Province ( BK20190764 ), and the Open Fund of State Key Laboratory of Remote Sensing Science ( OFSLRSS202005 ). J.-P·W acknowledges funding support from the CNES ( Centre National d’Etudes Spatiales , France) TOSCA programme. P.C. and J.-P·W acknowledge support from the ESA CCI RECCAP2-A project ( ESRIN/4000123002/18/I-NB ).

Publisher Copyright:
© 2023 Elsevier Inc.

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