Remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic Finland
The relationship between vegetation and snow depth has been studied with a view to subsequent incorporation in hydrological modelling. Study areas were designated at Kilpisjärvi and Kevo, northern Finland, to represent variations in altitude. Landsat MSS data for Kilpisjärvi were processed through...
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Geographical Society of Finland
1985
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ftdoajarticles:oai:doaj.org/article:61644b0c898542bda392c4f8e18a900f 2023-05-15T15:07:52+02:00 Remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic Finland Michael Clark Angela M. Gurnell Edward J. Milton Matti Seppälä Maarit Kyöstilä 1985-02-01T00:00:00Z https://doaj.org/article/61644b0c898542bda392c4f8e18a900f EN eng Geographical Society of Finland https://fennia.journal.fi/article/view/9060 https://doaj.org/toc/1798-5617 1798-5617 https://doaj.org/article/61644b0c898542bda392c4f8e18a900f Fennia: International Journal of Geography, Vol 163, Iss 2 (1985) Geography (General) G1-922 article 1985 ftdoajarticles 2022-12-31T07:12:41Z The relationship between vegetation and snow depth has been studied with a view to subsequent incorporation in hydrological modelling. Study areas were designated at Kilpisjärvi and Kevo, northern Finland, to represent variations in altitude. Landsat MSS data for Kilpisjärvi were processed through a series of interim classifications using simple density slicing of a band 7/5 ratio, incorporating ground radiometric data and vegetation identification progressively to refine the classification. The Kevo data were processed through a contrasting approach using principal components analysis. The resulting classifications were evaluated by further ground radiometry, and the snow retention capabilities of the individual classes were assessed by field snow surveys. The analysis established that MSS data provided sufficient discrimination to allow six distinct vegetation classes plus areas of water to be identified. The ground surveys of snow depth confirmed that these classes had clearly distinguishable snow retention properties, ranging from 5 cm for medium altitude heath to 85 cm for birch forest. The technique developed relies upon the availability of field data, but is efficient in the sense that limited data permit wide extrapolation of the estimates. It was concluded that despite the relative crudity of the classifications, they did offer a viable basis for rapid estimation of basin water equivalent storage in subarctic areas. Article in Journal/Newspaper Arctic Kilpisjärvi Northern Finland Directory of Open Access Journals: DOAJ Articles Arctic Kevo ENVELOPE(27.020,27.020,69.758,69.758) Kilpisjärvi ENVELOPE(20.767,20.767,69.034,69.034) |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Geography (General) G1-922 |
spellingShingle |
Geography (General) G1-922 Michael Clark Angela M. Gurnell Edward J. Milton Matti Seppälä Maarit Kyöstilä Remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic Finland |
topic_facet |
Geography (General) G1-922 |
description |
The relationship between vegetation and snow depth has been studied with a view to subsequent incorporation in hydrological modelling. Study areas were designated at Kilpisjärvi and Kevo, northern Finland, to represent variations in altitude. Landsat MSS data for Kilpisjärvi were processed through a series of interim classifications using simple density slicing of a band 7/5 ratio, incorporating ground radiometric data and vegetation identification progressively to refine the classification. The Kevo data were processed through a contrasting approach using principal components analysis. The resulting classifications were evaluated by further ground radiometry, and the snow retention capabilities of the individual classes were assessed by field snow surveys. The analysis established that MSS data provided sufficient discrimination to allow six distinct vegetation classes plus areas of water to be identified. The ground surveys of snow depth confirmed that these classes had clearly distinguishable snow retention properties, ranging from 5 cm for medium altitude heath to 85 cm for birch forest. The technique developed relies upon the availability of field data, but is efficient in the sense that limited data permit wide extrapolation of the estimates. It was concluded that despite the relative crudity of the classifications, they did offer a viable basis for rapid estimation of basin water equivalent storage in subarctic areas. |
format |
Article in Journal/Newspaper |
author |
Michael Clark Angela M. Gurnell Edward J. Milton Matti Seppälä Maarit Kyöstilä |
author_facet |
Michael Clark Angela M. Gurnell Edward J. Milton Matti Seppälä Maarit Kyöstilä |
author_sort |
Michael Clark |
title |
Remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic Finland |
title_short |
Remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic Finland |
title_full |
Remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic Finland |
title_fullStr |
Remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic Finland |
title_full_unstemmed |
Remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic Finland |
title_sort |
remotely-sensed vegetation classification as a snow depth indicator for hydrological analysis in sub-arctic finland |
publisher |
Geographical Society of Finland |
publishDate |
1985 |
url |
https://doaj.org/article/61644b0c898542bda392c4f8e18a900f |
long_lat |
ENVELOPE(27.020,27.020,69.758,69.758) ENVELOPE(20.767,20.767,69.034,69.034) |
geographic |
Arctic Kevo Kilpisjärvi |
geographic_facet |
Arctic Kevo Kilpisjärvi |
genre |
Arctic Kilpisjärvi Northern Finland |
genre_facet |
Arctic Kilpisjärvi Northern Finland |
op_source |
Fennia: International Journal of Geography, Vol 163, Iss 2 (1985) |
op_relation |
https://fennia.journal.fi/article/view/9060 https://doaj.org/toc/1798-5617 1798-5617 https://doaj.org/article/61644b0c898542bda392c4f8e18a900f |
_version_ |
1766339279269658624 |