liu.seSök publikationer i DiVA
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Delineating northern peatlands using Sentinel-1 time series and terrain indices from local and regional digital elevation models
Linköpings universitet, Institutionen för tema, Tema Miljöförändring. Linköpings universitet, Filosofiska fakulteten. Linköpings universitet, Centrum för klimatpolitisk forskning, CSPR.ORCID-id: 0000-0002-3926-3671
Linköpings universitet, Institutionen för tema, Tema Miljöförändring. Linköpings universitet, Filosofiska fakulteten.ORCID-id: 0000-0003-1107-3929
Stockholm Univ, Sweden.
LSCE, France.
Visa övriga samt affilieringar
2019 (Engelska)Ingår i: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 231, artikel-id UNSP 111252Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

The spatial extent of northern peatlands remains highly uncertain in spite of rapidly developing satellite observation datasets. This is limiting progress in the understanding of fundamental biogeochemical processes, such as the global carbon (C) cycle and climate feedback effects on C fluxes. In this study, we evaluated the capabilities of two new satellite datasets that enable regional scale mapping of peatland extent at high spatial resolution, including Sentinel-1 synthetic aperture radar (SAR) and the Arctic digital elevation model (ArcticDEM). Terrain indices and temporal features derived from these datasets provided input to Random Forest models for delineating four main land cover classes (forest, open upland, water and peatland) in an area in northern Sweden consisting of both lowland and mountainous terrain. The contribution of ArcticDEM to the classification accuracy was assessed by comparing the results with those derived when a high quality LiDAR based DEM (LiDEM) was used as alternative model input. This study shows that multi-seasonal SAR alone can produce reasonable classification results in terms of overall accuracy (OA; 81.6%), but also that it has limitations. The inclusion of terrain indices improved classification performance substantially. OA increased to 87.5% and 90.9% when terrain indices derived from ArcticDEM and LiDEM were included, respectively. The largest increase in accuracy was achieved for the peatland class, which suggests that terrain indices do have the ability to capture the features in the geographic context that aid the discrimination of peatland from other land cover classes. The relatively small difference in classification accuracy between LiDEM and ArcticDEM is encouraging since the latter provides circumpolar coverage. Thus, the combination of Sentinel-1 time series and terrain indices derived from ArcticDEM presents opportunities for substantially improving regional estimates of peatland extent at high latitudes.

Ort, förlag, år, upplaga, sidor
ELSEVIER SCIENCE INC , 2019. Vol. 231, artikel-id UNSP 111252
Nyckelord [en]
Sentinel-1; Satellite image time series; Digital elevation model; Arctic DEM; Terrain index; Land cover mapping; Wetland; Peatland
Nationell ämneskategori
Naturgeografi
Identifikatorer
URN: urn:nbn:se:liu:diva-160586DOI: 10.1016/j.rse.2019.111252ISI: 000484643900026OAI: oai:DiVA.org:liu-160586DiVA, id: diva2:1362726
Anmärkning

Funding Agencies|Swedish Research Council VRSwedish Research Council [VR 2012-48]; IZOMET project [VR 2014-6584]; Swedish Research Council for Sustainable Development (Formas)Swedish Research Council Formas [2018-00570, 2018-01794]

Tillgänglig från: 2019-10-21 Skapad: 2019-10-21 Senast uppdaterad: 2021-06-17

Open Access i DiVA

fulltext(2109 kB)596 nedladdningar
Filinformation
Filnamn FULLTEXT01.pdfFilstorlek 2109 kBChecksumma SHA-512
91e21b9fc0f9693cb7c8427e82eac2522038eaa140caf43e1252702a3bbb61c2c9274819f0f73db9b290a3fc4f1d0a73cfcb16122e546dc16494111fee34435e
Typ fulltextMimetyp application/pdf

Övriga länkar

Förlagets fulltext

Sök vidare i DiVA

Av författaren/redaktören
Karlson, MartinGålfalk, MagnusBastviken, David
Av organisationen
Tema MiljöförändringFilosofiska fakultetenCentrum för klimatpolitisk forskning, CSPR
I samma tidskrift
Remote Sensing of Environment
Naturgeografi

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 596 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

doi
urn-nbn

Altmetricpoäng

doi
urn-nbn
Totalt: 101 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf