Show simple item record

dc.contributor.authorGuo, Wenkai
dc.contributor.authorRees, Gareth
dc.contributor.authorHofgaard, Annika
dc.coverage.spatialArcticen_US
dc.date.accessioned2020-06-23T12:52:49Z
dc.date.available2020-06-23T12:52:49Z
dc.date.created2020-06-19T09:48:49Z
dc.date.issued2020
dc.identifier.citationInternational Journal of Remote Sensing. 2020, 41 (16), 6384-6408.en_US
dc.identifier.issn0143-1161
dc.identifier.urihttps://hdl.handle.net/11250/2659183
dc.description.abstractThe transition zone between the boreal forest and Arctic tundra, the forest-tundra ecotone (FTE), is an area of high ecological and climatological significance. Despite its importance, a globally consistent high spatial resolution mapping is lacking. Accurate mapping of the FTE requires the use of satellite remote sensing data. Here we use the Landsat Vegetation Continuous Fields (VCF) product and Reference point data to derive the location and characteristics of the FTE. An image texture-based supervised classification scheme is developed based on a study area in Central Eurasia to statistically exploit the spatial patterns of the transition zone. Texture statistics for the VCF image are derived from the grey-level co-occurrence matrix (GLCM) based on which the study area is classified into forest, tundra, and FTEs. Adaptive parameterization is implemented to achieve optimal classification performance in the study area. This method is further applied to six additional study areas around the circumarctic region to test its adaptability. In all study areas, this method achieves better FTE delineation results than previously reported methods, showing better classification accuracies (average of 0.826) and more realistic and complete representation of the FTE as shown by visual examination. This shows the universal applicability of the method and it is potential to be used to achieve more detailed and accurate circumarctic mapping of the FTE, which could serve as the basis of time series analysis of FTE positions, eventually contributing to a better understanding of the inter-relations between climate change and shifts in sub-arctic vegetation.en_US
dc.language.isoengen_US
dc.titleDelineation of the forest-tundra ecotone using texture-based classification of satellite imageryen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.subject.nsiVDP::Zoologiske og botaniske fag: 480en_US
dc.subject.nsiVDP::Zoology and botany: 480en_US
dc.source.pagenumber6384-6408en_US
dc.source.volume41en_US
dc.source.journalInternational Journal of Remote Sensingen_US
dc.source.issue16en_US
dc.identifier.doi10.1080/01431161.2020.1734254
dc.identifier.cristin1816258
dc.relation.projectNorges forskningsråd: 260400en_US
dc.relation.projectNorges forskningsråd: 244557en_US
dc.relation.projectAndre: Cambridge Trusten_US
dc.relation.projectAndre: University of Cambridgeen_US
dc.relation.projectAndre: Fitzwilliam Collegeen_US
dc.relation.projectAndre: Trinity Collegeen_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record