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dcterms:title "Aboveground woody carbon density and change in tropical dry forests and savannas, with land cover change process fractions and raw annual biomass predictions, 2015-2024" ;
dcterms:identifier <https://catalogue.ceh.ac.uk/id/2fd38433-cf42-4dc2-afe9-a4a885486c73> ;
adms:identifier <https://doi.org/10.5285/2fd38433-cf42-4dc2-afe9-a4a885486c73> ;
dcterms:bibliographicCitation "Harrison, S.B., Godlee, J.L., Milodowski, D.T., Asiyabi, R., Mograbi, P.J., Aguirre, Z., Almeida, J.S., Ametsitsi, G.K.D., Araujo-Murakami, A., Archibald, S., Arroyo Padilla, L., Benitez, L., Bowers, S.J., Brade, T.K., Cardoso, D., Carreiras, J.M.B., Castro, A.A.J.F., Chalo, D., Compaore, H., da Costa, I.S.C., Coutinho, Í.A.C., das Neves, E.C., De Cauwer, V., de Sousa Oliveira, T.C., Diesse, H., Domingues, T.F., Elias, F., Farrapo, C.L., Feig, G., Feldpausch, T.R., Fernandes, M.F., Galbraith, D.R., Gasparri, N.I., Gloor, E., Gonçalves, F.M., Gotore, T., Guimaraes, K.S., Gutierrez-Sibauty, G., Harrison, R.D., Higginbottom, T.P., Ishida, F.Y., Issifu, H., Kigomo, J.N., Killeen, T.J., Levesley, A., Lewis, S.L., Lima, J.R.S., Loto, D., Mariano, E.S., Marimon, B.S., Marimon-Junior, B.H., Espírito-Santo, M.M., Marques, A.M.L., Martins, M.S., Masinde, C.W., Mbuvi, M.T.E., McNicol, I.M., Melgaço, K., Mogonong, B., Moonlight, P.W., Morandi, P.S., Morellato, L.P.C., Moura, M.S.B.D., Muchawona, A., Muledi, J.I., Naftal, L., Oliveira Silva, J., Parr, C.L., Prestes, N.C.C.S., Queiroz, L.P.D., Ramaswiela, T., Ramos, D.M., Reis, S.M., Ribeiro, N.S., Rocha, R.R., Rodrigues, P.M.S., Saiz, G., Santos, R.M., Shutcha, M.N., da Silva, D.F.P.F., Smart, K.G., Sonké, B., Veenendaal, E., Wekesa, C., Wells, L.H., Zuanny, D., Baker, T.R., Dexter, K.G., Hegerl, G.C., Pennington, R.T., Phillips, O.L., Sitch, S., Staver, A.C., Williams, M., Quegan, S., Hancock, S., Augustin, N.H., Ryan, C.M. (2026). Aboveground woody carbon density and change in tropical dry forests and savannas, with land cover change process fractions and raw annual biomass predictions, 2015-2024. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/2fd38433-cf42-4dc2-afe9-a4a885486c73" ;
dcterms:description "This dataset consists of four complementary geospatial products, and the model calibration data, that quantify woody carbon stocks and their dynamics across the world's dry tropical forests and savannas from 2015 to 2024. It includes a 100 m resolution map of time‑averaged aboveground woody carbon density (AGCD; MgC ha-1), a 100 m map of annual AGCD change expressed as a per‑pixel linear trend (MgC ha-1 yr-1), a 10 km four‑band raster of the proportion of each cell affected by major land cover change processes (deforestation, degradation, densification, extensification) over the period, and a 100 m ten‑band stack of annual aboveground biomass density (AGBD; Mg ha-1) predictions for 2015-2024 before any quality corrections, masking, temporal smoothing, or gap‑filling. The mapped domain follows the study's definition of the dry tropical forests and savanna biome, excluding very arid zones, Mediterranean/temperate climates, and evergreen closed‑canopy moist forests. The products were created by linking annual‑minimum L‑band radar backscatter from ALOS‑2 PALSAR‑2 ScanSAR (HV, γ0 in natural/linear units) to aboveground carbon estimates from a global network of large field plots using a generalized additive model with a log link. The ScanSAR scenes were speckle‑filtered and, for each year, the per‑pixel minimum HV backscatter was taken to reduce soil‑moisture effects, then aggregated to 100 m. Quality filters and temporal smoothing was applied to the time series, including continent‑specific quality masks, exclusion of pixel‑years where the surface soil moisture was high, interpolation across short gaps, and a five‑year Savitzky-Golay temporal smoothing. Annual change was derived from the linear trend of the AGCD time series for 2015 to 2024. Where ScanSAR coverage was sparse, a secondary model based on ALOS‑2 annual mosaic data was used to fill spatial gaps. Land cover change processes were defined from the AGCD time series, using a wooded threshold (>10 MgC ha-1) and a major‑change threshold (>20% over the period) and then aggregated to 10 km cells as proportions of each process within each cell. The raw AGBD stack is also shared without QA, smoothing, or gap‑filling. These data enable spatially explicit assessment of woody carbon stocks and dynamics in the dry tropics and support national reporting, monitoring of change processes, and assessment of regional drivers. This work is part of the SECO project, resolving the current and future carbon dynamics of the dry tropics funded by NERC (NE/T01279X/1)." ;
dcterms:provenance [
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rdfs:label "These products were generated by linking annual-minimum L-band SAR backscatter data to field-estimated carbon data in a generalised additive model. Plot data (n≈237, ≥ 0.25 ha) from dry tropical forests and savannas provided aboveground woody carbon density estimates (AGCD; MgC ha-1) with Monte Carlo propagated uncertainties; tree inventories were converted to AGCD using biome specific allometry and wood density. The radar data used was the annual minimum ALOS‑2 PALSAR‑2 ScanSAR HV (Level 2.2), speckle‑filtered (refined Lee 3×3), converted to γ0 (natural/linear units), and aggregated to 100 m. A generalized additive model (log link; weights by plot area) models AGCD from γ0 and was used to make annual pixel predictions of AGCD from 2015 to 2024 across the study domain. The time series underwent continent‑specific quality masking, exclusion of pixel‑years with high surface soil moisture, gap interpolation, and a five‑year Savitzky-Golay smoothing was applied. Annual change was estimates from the linear slope on the pixel time series (MgC ha-1 yr-1). Land cover change processes were classified from the time series, using thresholds to designated a pixel-year as wooded (>10 MgC ha-1) and undergoing a major change (>20%). These were aggregated to 10 km as proportions (0-1) of the cell that experiences each land cover change process. Where ScanSAR coverage was sparse, gaps were filled using a secondary ALOS‑2 annual mosaic‑based model. The 'raw' AGBD stack (Mg ha-1) is provided without masking, smoothing or gap‑filling. Validation via leave‑one‑site‑out across 98 groups of geographically proximate plots yielded RMSD ~15.1 MgC ha-1."
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<http://www.eionet.europa.eu/gemet/concept/2040>,
<http://vocabs.lter-europe.net/EnvThes/21249>,
<http://www.eionet.europa.eu/gemet/concept/6883>,
"savanna",
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