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Multi‐Source Mapping of Peatland Types Using Sentinel‐1, Sentinel‐2, and Terrain Derivatives—A Comparison Between Five High‐Latitude Landscapes
Linköpings universitet, Institutionen för tema, Tema Miljöförändring. Linköpings universitet, Filosofiska fakulteten.ORCID-id: 0000-0002-3926-3671
Linköpings universitet, Institutionen för tema, Tema Miljöförändring. Linköpings universitet, Filosofiska fakulteten.ORCID-id: 0000-0003-0038-2152
2023 (Engelska)Ingår i: Journal of Geophysical Research - Biogeosciences, ISSN 2169-8953, E-ISSN 2169-8961, Vol. 128, nr 4, artikel-id e2022JG007195Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Mapping wetland types in northern-latitude regions with Earth Observation (EO) data is important for several practical and scientific applications, but at the same time challenging due to the variability and dynamic nature in wetland features introduced by differences in geophysical conditions. The objective of this study was to better understand the ability of Sentinel-1 radar data, Sentinel-2 optical data and terrain derivatives derived from Copernicus digital elevation model to distinguish three main peatland types, two upland classes, and surface water, in five contrasting landscapes located in the northern parts of Alaska, Canada and Scandinavia. The study also investigated the potential benefits for classification accuracy of using regional classification models constructed from region-specific training data compared to a global classification model based on pooled reference data from all five sites. Overall, the results show high promise for classifying peatland types and the three other land cover classes using the fusion approach that combined all three EO data sources (Sentinel-1, Sentinel-2 and terrain derivatives). Overall accuracy for the individual sites ranged between 79.7% and 90.3%. Class specific accuracies for the peatland types were also high overall but differed between the five sites as well as between the three classes bog, fen and swamp. A key finding is that regional classification models consistently outperformed the global classification model by producing significantly higher classification accuracies for all five sites. This suggests for progress in identifying effective approaches for continental scale peatland mapping to improve scaling of for example, hydrological- and greenhouse gas-related processes in Earth system models.

Ort, förlag, år, upplaga, sidor
John Wiley & Sons, 2023. Vol. 128, nr 4, artikel-id e2022JG007195
Nyckelord [en]
peatland types; land cover classification; data fusion; arctic; northern latitude regions; terrain derivatives
Nationell ämneskategori
Multidisciplinär geovetenskap Fjärranalysteknik Naturgeografi
Identifikatorer
URN: urn:nbn:se:liu:diva-193214DOI: 10.1029/2022jg007195ISI: 000972246100001OAI: oai:DiVA.org:liu-193214DiVA, id: diva2:1752259
Anmärkning

Funding: Swedish Research Council Formas [2017-01944, 2018-01794, 2018-00570]; European Space Agency

Tillgänglig från: 2023-04-21 Skapad: 2023-04-21 Senast uppdaterad: 2023-09-15

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Karlson, MartinBastviken, David

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Journal of Geophysical Research - Biogeosciences
Multidisciplinär geovetenskapFjärranalysteknikNaturgeografi
Karlson, M. (2023). Multi-source Mapping of Peatland Types using Sentinel-1, Sentinel-2 and Terrain Derivatives – A Comparison Between Five High-latitude Landscapes. Linköping University Electronic Press

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