Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Past decade above-ground biomass change comparisons from four multi-temporal global maps

Araza, Arnan ; Herold, Martin ; de Bruin, Sytze ; Ciais, Philippe ; Gibbs, David A. ; Harris, Nancy ; Santoro, Maurizio ; Wigneron, Jean Pierre ; Yang, Hui and Málaga, Natalia , et al. (2023) In International Journal of Applied Earth Observation and Geoinformation 118.
Abstract

Above-ground biomass (AGB) is considered an essential climate variable that underpins our knowledge and information about the role of forests in mitigating climate change. The availability of satellite-based AGB and AGB change (ΔAGB) products has increased in recent years. Here we assessed the past decade net ΔAGB derived from four recent global multi-date AGB maps: ESA-CCI maps, WRI-Flux model, JPL time series, and SMOS-LVOD time series. Our assessments explore and use different reference data sources with biomass re-measurements within the past decade. The reference data comprise National Forest Inventory (NFI) plot data, local ΔAGB maps from airborne LiDAR, and selected Forest Resource Assessment country data from countries with... (More)

Above-ground biomass (AGB) is considered an essential climate variable that underpins our knowledge and information about the role of forests in mitigating climate change. The availability of satellite-based AGB and AGB change (ΔAGB) products has increased in recent years. Here we assessed the past decade net ΔAGB derived from four recent global multi-date AGB maps: ESA-CCI maps, WRI-Flux model, JPL time series, and SMOS-LVOD time series. Our assessments explore and use different reference data sources with biomass re-measurements within the past decade. The reference data comprise National Forest Inventory (NFI) plot data, local ΔAGB maps from airborne LiDAR, and selected Forest Resource Assessment country data from countries with well-developed monitoring capacities. Map to reference data comparisons were performed at levels ranging from 100 m to 25 km spatial scale. The comparisons revealed that LiDAR data compared most reasonably with the maps, while the comparisons using NFI only showed some agreements at aggregation levels <10 km. Regardless of the aggregation level, AGB losses and gains according to the map comparisons were consistently smaller than the reference data. Map-map comparisons at 25 km highlighted that the maps consistently captured AGB losses in known deforestation hotspots. The comparisons also identified several carbon sink regions consistently detected by all maps. However, disagreement between maps is still large in key forest regions such as the Amazon basin. The overall ΔAGB map cross-correlation between maps varied in the range 0.11–0.29 (r). Reported ΔAGB magnitudes were largest in the high-resolution datasets including the CCI map differencing (stock change) and Flux model (gain-loss) methods, while they were smallest according to the coarser-resolution LVOD and JPL time series products, especially for AGB gains. Our results suggest that ΔAGB assessed from current maps can be biased and any use of the estimates should take that into account. Currently, ΔAGB reference data are sparse especially in the tropics but that deficit can be alleviated by upcoming LiDAR data networks in the context of Supersites and GEO-Trees.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Above-ground biomass, Above-ground biomass change, Carbon flux, Earth observation, Global carbon cycle, Map assessment
in
International Journal of Applied Earth Observation and Geoinformation
volume
118
article number
103274
publisher
Elsevier
external identifiers
  • scopus:85151860917
ISSN
1569-8432
DOI
10.1016/j.jag.2023.103274
language
English
LU publication?
yes
id
a6567c9c-7042-4210-b08f-1de22a9b6876
date added to LUP
2023-07-13 15:21:22
date last changed
2023-07-13 15:21:22
@article{a6567c9c-7042-4210-b08f-1de22a9b6876,
  abstract     = {{<p>Above-ground biomass (AGB) is considered an essential climate variable that underpins our knowledge and information about the role of forests in mitigating climate change. The availability of satellite-based AGB and AGB change (ΔAGB) products has increased in recent years. Here we assessed the past decade net ΔAGB derived from four recent global multi-date AGB maps: ESA-CCI maps, WRI-Flux model, JPL time series, and SMOS-LVOD time series. Our assessments explore and use different reference data sources with biomass re-measurements within the past decade. The reference data comprise National Forest Inventory (NFI) plot data, local ΔAGB maps from airborne LiDAR, and selected Forest Resource Assessment country data from countries with well-developed monitoring capacities. Map to reference data comparisons were performed at levels ranging from 100 m to 25 km spatial scale. The comparisons revealed that LiDAR data compared most reasonably with the maps, while the comparisons using NFI only showed some agreements at aggregation levels &lt;10 km. Regardless of the aggregation level, AGB losses and gains according to the map comparisons were consistently smaller than the reference data. Map-map comparisons at 25 km highlighted that the maps consistently captured AGB losses in known deforestation hotspots. The comparisons also identified several carbon sink regions consistently detected by all maps. However, disagreement between maps is still large in key forest regions such as the Amazon basin. The overall ΔAGB map cross-correlation between maps varied in the range 0.11–0.29 (r). Reported ΔAGB magnitudes were largest in the high-resolution datasets including the CCI map differencing (stock change) and Flux model (gain-loss) methods, while they were smallest according to the coarser-resolution LVOD and JPL time series products, especially for AGB gains. Our results suggest that ΔAGB assessed from current maps can be biased and any use of the estimates should take that into account. Currently, ΔAGB reference data are sparse especially in the tropics but that deficit can be alleviated by upcoming LiDAR data networks in the context of Supersites and GEO-Trees.</p>}},
  author       = {{Araza, Arnan and Herold, Martin and de Bruin, Sytze and Ciais, Philippe and Gibbs, David A. and Harris, Nancy and Santoro, Maurizio and Wigneron, Jean Pierre and Yang, Hui and Málaga, Natalia and Nesha, Karimon and Rodriguez-Veiga, Pedro and Brovkina, Olga and Brown, Hugh C.A. and Chanev, Milen and Dimitrov, Zlatomir and Filchev, Lachezar and Fridman, Jonas and García, Mariano and Gikov, Alexander and Govaere, Leen and Dimitrov, Petar and Moradi, Fardin and Muelbert, Adriane Esquivel and Novotný, Jan and Pugh, Thomas A.M. and Schelhaas, Mart Jan and Schepaschenko, Dmitry and Stereńczak, Krzysztof and Hein, Lars}},
  issn         = {{1569-8432}},
  keywords     = {{Above-ground biomass; Above-ground biomass change; Carbon flux; Earth observation; Global carbon cycle; Map assessment}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{International Journal of Applied Earth Observation and Geoinformation}},
  title        = {{Past decade above-ground biomass change comparisons from four multi-temporal global maps}},
  url          = {{http://dx.doi.org/10.1016/j.jag.2023.103274}},
  doi          = {{10.1016/j.jag.2023.103274}},
  volume       = {{118}},
  year         = {{2023}},
}