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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 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.
Original language | English |
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Article number | 103274 |
Number of pages | 12 |
Journal | International Journal of Applied Earth Observation and Geoinformation |
Volume | 118 |
DOIs | |
Publication status | Published - 4 Apr 2023 |
Bibliographical note
Funding Information:This study was partly supported by the (1) IFBN/FOS (contract no. 4000114425/15/NL/FF/gp), SEN4LDN and CCI Biomass (contract no. 4000123662/18/I-NB) projects funded by the European Space Agency; (2) VERIFY Project: Observation-based system for monitoring and verification of greenhouse gases (GA number 776810, RIA). Acknowledgement is also given to the Open Earth Monitor Project from European Union's Horizon Europe research an innovation programme (grant agreement 101059548); the World Resources Institute (WRI) land and carbon lab support to WUR and GFZ; and the CGIAT MITIGATE+ project. Authors TAMP, AEM and MJS acknowledge funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 758873, TreeMort). This study contributes to the Strategic Research Areas BECC and MERGE. Czech Republic data was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program, grant number LM2023048. Polish data was supported by Project LIFE+ ForBioSensing (contract number LIFE13 ENV/PL/000048) and Poland's National Fund for Environmental Protection and Water Management (contract number 485/2014/WN10/OP-NMLF/D). We sincerely thank Nicolas Labriere for processing and providing the LiDAR reference data. We also thank Maciej Lisiewicz and Lukasz Kuberski, for their assistance in Polish data preparation.
Publisher Copyright:
© 2023 The Author(s)
Keywords
- Above-ground biomass
- Above-ground biomass change
- Carbon flux
- Earth observation
- Global carbon cycle
- Map assessment
ASJC Scopus subject areas
- Global and Planetary Change
- Earth-Surface Processes
- Computers in Earth Sciences
- Management, Monitoring, Policy and Law
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