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Vegetation mapping of Svalbard utilising Landsat TM/ETM+ data

Published online by Cambridge University Press:  29 November 2011

Bernt E. Johansen ,
Stein Rune Karlsen  and
Hans Tømmervik
Bernt E. Johansen
Affiliation:
Northern Research Institute - Tromsø, Tromsø Science Park, N-9294 Tromsø, Norway ([email protected])
Stein Rune Karlsen
Affiliation:
Northern Research Institute - Tromsø, Tromsø Science Park, N-9294 Tromsø, Norway ([email protected])
Hans Tømmervik
Affiliation:
Norwegian Institute for Nature Research, The Polar Environmental Centre, N-9296 Tromsø, Norway
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Abstract

The overall objective of this paper is to present and discuss the most recently developed vegetation map for Svalbard, Arctic Norway. The map is based on satellite images in which several Landsat TM/ETM+ images were processed through six operational stages involving: (1) automatic image classification, (2) spectral similarity analysis, (3) generation of classified image mosaics, (4) ancillary data analysis, (5) contextual correction, and (6) standardisation of the final map products. The developed map is differentiated into 18 map units interpreted from 37 spectral classes. Among the 18 units separated, six of the units comprise rivers, lakes and inland waters, glaciers, as well as non- to sparsely vegetated areas. The map unit 7 is a result of shadow effects and different types of distortions in the satellite image. The vegetation of the remaining eleven units varies from dense marshes and moss tundra communities to sparsely vegetated polar deserts and moist gravel snowbeds. The accuracy of the map is evaluated in areas were access to traditional maps have been available. The vegetation density and fertility is reflected in computed NDVI values. The map product is in digital format, which gives the opportunity to produce maps in different scales. A map sheet portraying the entire archipelago is one of the main products from this study, produced at a scale of 1:500,000.

Type
Research Article
Information
Polar Record , Volume 48 , Special Issue 1: Papers from the 11th Circumpolar Remote Sensing Symposium , January 2012 , pp. 47 - 63
Copyright
Copyright © Cambridge University Press 2011

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