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dcterms:title "Peatland distribution maps for lowland Peruvian Amazonia, 2022" ;
dcterms:identifier "https://catalogue.ceh.ac.uk/id/db3de2d7-b094-4d15-a40b-edb618ede889","https://doi.org/10.5285/db3de2d7-b094-4d15-a40b-edb618ede889" ;
dcterms:bibliographicCitation "Hastie, A., Honorio Coronado, E.H., Reyna Huaymacari, J., Mitchard, E.T., Åkesson, C., Baker, T.R., Cole, L.E.S., Cordova Oroche, C.J., Dargie, G.C., Dávila, N., De Grandi, E.C., del Aguila-Pasquel, J., Del Castillo Torres, D., De la Cruz Paiva, R., Draper, F.C., Flores, G., Grandez Ríos, J., Hergoualc’h, K., Householder, J.E., Janovec, J.P., Lähteenoja, O., Reyna, D., Rodríguez-Veiga, P., Roucoux, K.H., Tobler, M., Wheeler, C.E., Williams, M., Lawson, I.T. (2024). Peatland distribution maps for lowland Peruvian Amazonia, 2022. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/db3de2d7-b094-4d15-a40b-edb618ede889" ;
dcterms:description "Spatial datasets of predicted land cover, peatland extent, peat thickness and peatland carbon storage for the Lowland Peruvian Amazon." ;
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rdfs:label "A total of 1,128 ground reference points of vegetation type, peat presence/absence and (where applicable) peat thickness from the lowland Peruvian Amazon (LPA) were used to train (50% of the data) and validate (the remaining 50% of the data) predictive models of land cover, peatland extent, peat thickness and (in conjunction with laboratory measurements on peat samples) peat carbon storage. Input data to the model included a stack of seven remote-sensing layers, including two Sentinel-2 indices, three ALOS PALSAR-2 bands, SRTM digital elevation data, and a previous land-cover map."
] ;
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<http://www.eionet.europa.eu/gemet/concept/5013>,
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<http://www.eionet.europa.eu/gemet/concept/7102>,
<http://onto.nerc.ac.uk/CAST/270> ;
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