Comparative evaluation of ALMAZ, ERS-1, JERS-1, and Landsat-TM for discriminating wet tundra habitats

Abstract Systematic image-classification methods were applied to ALMAZ, ERS-1, and JERS-1 synthetic aperture radar (SAR) and Landsat-TM multispectral satellite images to evaluate the relative information content of the satellite data for discriminating wet tundra habitats in northern Alaska. Results...

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Bibliographic Details
Published in:Polar Record
Main Authors: Belchansky, Gennady I., Ovchinnikov, Gregory K., Douglas, David C.
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 1995
Subjects:
General Earth and Planetary Sciences
Ecology
Geography, Planning and Development
Polar Record
Tundra
Alaska
Online Access:http://dx.doi.org/10.1017/s0032247400013668
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0032247400013668
Description
Summary:Abstract Systematic image-classification methods were applied to ALMAZ, ERS-1, and JERS-1 synthetic aperture radar (SAR) and Landsat-TM multispectral satellite images to evaluate the relative information content of the satellite data for discriminating wet tundra habitats in northern Alaska. Results suggest that SAR data can be used to concurrently detect a maximum of four or five landcover classes using the methods of this study. Combining two or more SAR images from different satellites improved the detection of some classes, particularly water bodies. Combining full-resolution SAR data with Landsat-TM did not improve the detection capabilities of Landsat-TM alone. Further research is needed to assess other image-classification and SAR data processing methods.

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