Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar

Detailed snowpack observations, meteorology, topography and landcover classification were integrated with multi‐temporal SAR data to assess its capability for landscape scale snowmelt mapping at the forest–tundra ecotone. At three sites along an approximately 8° latitudinal gradient in the Fennoscan...

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Published in:International Journal of Remote Sensing
Main Authors: Dean, A. M., Brown, I. A., Huntley, B., Thomas, C. J.
Format: Article in Journal/Newspaper
Language:unknown
Published: Taylor & Francis 2006
Subjects:
Online Access:https://eprints.lincoln.ac.uk/id/eprint/41253/
https://doi.org/10.1080/01431160600851793
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spelling ftulincoln:oai:eprints.lincoln.ac.uk:41253 2023-05-15T14:24:34+02:00 Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar Dean, A. M. Brown, I. A. Huntley, B. Thomas, C. J. 2006-09-30 https://eprints.lincoln.ac.uk/id/eprint/41253/ https://doi.org/10.1080/01431160600851793 unknown Taylor & Francis Dean, A. M., Brown, I. A., Huntley, B. and Thomas, C. J. (2006) Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar. International Journal of Remote Sensing, 27 (19). pp. 4347-4370. ISSN 0143-1161 doi:10.1080/01431160600851793 Article PeerReviewed 2006 ftulincoln https://doi.org/10.1080/01431160600851793 2022-03-02T20:13:30Z Detailed snowpack observations, meteorology, topography and landcover classification were integrated with multi‐temporal SAR data to assess its capability for landscape scale snowmelt mapping at the forest–tundra ecotone. At three sites along an approximately 8° latitudinal gradient in the Fennoscandian mountain range, 16 multi‐temporal spaceborne ERS‐2 synthetic aperture radar (SAR) were used for mapping snowmelt. Comparison of field measurements and backscatter values demonstrates the difficulty of interpreting observed backscatter response because of complex changes in snow properties on diurnal and seasonal temporal scales. Diurnal and seasonal melt–freeze effects in the snowpack, relative to the timing of ERS‐2 SAR image acquisition, effectively reduce the temporal resolution of such data for snow mapping, even at high latitudes. The integration of diverse data sources did reveal significant associations between vegetation, topography and snowmelt. Several problems with the application of thresholding for the automatic identification of snowmelt were encountered. These largely related to changes in backscattering from vegetation in the late stages of snowmelt. Due to the impact of environmental heterogeneity in vegetation at the forest–tundra ecotone, we suggest that the potential to map snow cover using single polarization C‐band SAR at the forest–tundra ecotone may be limited to tundra areas. Article in Journal/Newspaper Arctic Arctic Fennoscandian Tundra University of Lincoln: Lincoln Repository Arctic International Journal of Remote Sensing 27 19 4347 4370
institution Open Polar
collection University of Lincoln: Lincoln Repository
op_collection_id ftulincoln
language unknown
description Detailed snowpack observations, meteorology, topography and landcover classification were integrated with multi‐temporal SAR data to assess its capability for landscape scale snowmelt mapping at the forest–tundra ecotone. At three sites along an approximately 8° latitudinal gradient in the Fennoscandian mountain range, 16 multi‐temporal spaceborne ERS‐2 synthetic aperture radar (SAR) were used for mapping snowmelt. Comparison of field measurements and backscatter values demonstrates the difficulty of interpreting observed backscatter response because of complex changes in snow properties on diurnal and seasonal temporal scales. Diurnal and seasonal melt–freeze effects in the snowpack, relative to the timing of ERS‐2 SAR image acquisition, effectively reduce the temporal resolution of such data for snow mapping, even at high latitudes. The integration of diverse data sources did reveal significant associations between vegetation, topography and snowmelt. Several problems with the application of thresholding for the automatic identification of snowmelt were encountered. These largely related to changes in backscattering from vegetation in the late stages of snowmelt. Due to the impact of environmental heterogeneity in vegetation at the forest–tundra ecotone, we suggest that the potential to map snow cover using single polarization C‐band SAR at the forest–tundra ecotone may be limited to tundra areas.
format Article in Journal/Newspaper
author Dean, A. M.
Brown, I. A.
Huntley, B.
Thomas, C. J.
spellingShingle Dean, A. M.
Brown, I. A.
Huntley, B.
Thomas, C. J.
Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar
author_facet Dean, A. M.
Brown, I. A.
Huntley, B.
Thomas, C. J.
author_sort Dean, A. M.
title Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar
title_short Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar
title_full Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar
title_fullStr Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar
title_full_unstemmed Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar
title_sort monitoring snowmelt across the arctic forest–tundra ecotone using synthetic aperture radar
publisher Taylor & Francis
publishDate 2006
url https://eprints.lincoln.ac.uk/id/eprint/41253/
https://doi.org/10.1080/01431160600851793
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
Fennoscandian
Tundra
genre_facet Arctic
Arctic
Fennoscandian
Tundra
op_relation Dean, A. M., Brown, I. A., Huntley, B. and Thomas, C. J. (2006) Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar. International Journal of Remote Sensing, 27 (19). pp. 4347-4370. ISSN 0143-1161
doi:10.1080/01431160600851793
op_doi https://doi.org/10.1080/01431160600851793
container_title International Journal of Remote Sensing
container_volume 27
container_issue 19
container_start_page 4347
op_container_end_page 4370
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