Application of national forest inventory for remote sensing classification of ground lichen in nothern Sweden

↓ Direkt till sidans innehåll
↓ Direkt till sidans sekundära innehåll (sidomenyn)

Search: onr:"swepub:oai:DiVA.org:umu-206481" > Application of nati...

1 of 1
Previous record
Next record
To hitlist

Application of national forest inventory for remote sensing classification of ground lichen in nothern Sweden

Gilichinsky, Michael (author): Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management

Sandström, Per (author): Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management

Reese, Heather (author): Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management

Kivinen, Sonja (author): Umeå universitet,Institutionen för ekologi, miljö och geovetenskap

Moen, Jon (author): Umeå universitet,Institutionen för ekologi, miljö och geovetenskap

Nilsson, Mats (author): Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management

show less...

(creator_code:org_t)

International Society for Photogrammetry and Remote Sensing, 2010
2010
English.
In: ISPRS Archives. - : International Society for Photogrammetry and Remote Sensing. ; 38-4-8, s. 146-152

Related links:: https://www.isprs.or...; show more...; https://www.isprs.or...; https://urn.kb.se/re...; https://res.slu.se/i...; show less...

Conference paper (peer-reviewed)

Abstract Subject headings

Lichen is a major forage resource for reindeer and may constitute up to 80% of a reindeer's winter diet. The reindeer grazing area in Sweden covers almost half of the country, with reindeer using mountainous areas in the summer and forested areas in the winter. Knowledge about the spatial distribution of ground lichens is important for both practical and sustainable decisionmaking purposes. Since the early 1980s, remote sensing research of lichen cover in northern environments has focused on reindeer grazing issues. The objective of the present study was to use lichen information from the Swedish Forest Inventory (NFI) for classification of satellite data into ground lichen classes. The classification procedure was focused on using of NFI plots as training sets for supervised classification of the ground lichen cover in purpose to classify areas with different lichen coverage. The present research has shown the advantage of use forest inventory plot data by assessment of three methods: mahalanobis distance (MD) classification, maximum likelihood (ML) classification and spectral mixture analysis (SMA). The results of this study demonstrate high classification accuracy of SPOT imagery in distinction between lichenabundant and lichen-poor areas by mahalanobis distance classifier (overall accuracy 84.3%, kappa=0.68). The highest classification accuracy for Landsat scene was achieved by maximumlikelihood classification (overall accuracy 76.8%, kappa=0.53). The continuation research on more detailed fragmentation of lichen cover into fractions is proposed.

Subject headings

LANTBRUKSVETENSKAPER -- Annan lantbruksvetenskap -- Miljö- och naturvårdsvetenskap (hsv//swe)
AGRICULTURAL SCIENCES -- Other Agricultural Sciences -- Environmental Sciences related to Agriculture and Land-use (hsv//eng)
LANTBRUKSVETENSKAPER -- Lantbruksvetenskap, skogsbruk och fiske -- Skogsvetenskap (hsv//swe)
AGRICULTURAL SCIENCES -- Agriculture, Forestry and Fisheries -- Forest Science (hsv//eng)
TEKNIK OCH TEKNOLOGIER -- Naturresursteknik -- Fjärranalysteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY -- Environmental Engineering -- Remote Sensing (hsv//eng)

Keyword

Landsat 7 ETM
Lichen classification
National forest inventory
SPOT-5

Publication and Content Type

ref (subject category)
kon (subject category)

Find in a library

ISPRS Archives (Search for host publication in LIBRIS)

To the university's database

1 of 1
Previous record
Next record
To hitlist

Find more in SwePub

By the author/editor: Gilichinsky, Mic ...; Sandström, Per; Reese, Heather; Kivinen, Sonja; Moen, Jon; Nilsson, Mats

About the subject

AGRICULTURAL SCIENCES: AGRICULTURAL SCI ...; and Other Agricultur ...; and Environmental Sc ...

AGRICULTURAL SCIENCES: AGRICULTURAL SCI ...; and Agriculture Fore ...; and Forest Science

ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Environmental En ...; and Remote Sensing

Articles in the publication: ISPRS Archives; International Ar ...

By the university: Umeå University; Swedish University of Agricultural Sciences

Search outside SwePub

Extend your search to:: Google; Google Book Search; Google Scholar

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

LIBRIS.kb.se