Impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ...

Using multispectral remote sensing, glacier surfaces can be classified into a range of zones. The properties of these classes are used for a range of glaciological applications including mass balance measurements, glacial hydrology, and melt modelling. However, it is not immediately evident that mul...

Full description

Bibliographic Details
Main Authors: Pope, A, Rees, WG
Format: Text
Language:unknown
Published: Apollo - University of Cambridge Repository 2014
Subjects:
Online Access:https://dx.doi.org/10.17863/cam.15555
https://www.repository.cam.ac.uk/handle/1810/301386
id ftdatacite:10.17863/cam.15555
record_format openpolar
spelling ftdatacite:10.17863/cam.15555 2023-05-15T15:10:19+02:00 Impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ... Pope, A Rees, WG 2014 https://dx.doi.org/10.17863/cam.15555 https://www.repository.cam.ac.uk/handle/1810/301386 unknown Apollo - University of Cambridge Repository Glaciers Snow Multispectral Classification Principal component analysis Article ScholarlyArticle article-journal Text 2014 ftdatacite https://doi.org/10.17863/cam.15555 2023-04-03T12:56:20Z Using multispectral remote sensing, glacier surfaces can be classified into a range of zones. The properties of these classes are used for a range of glaciological applications including mass balance measurements, glacial hydrology, and melt modelling. However, it is not immediately evident that multispectral data should be optimal for imaging glaciers and ice caps. Thus, this investigation takes an inverse perspective. Taking into account spectral and radiometric properties, in situ spectral reflectance data were used to simulate glacier surface response for a suite of multispectral sensors. Sensor-simulated data were classified and compared. In addition, airborne multispectral imagery was classified for a range of spatial resolutions and intercompared in three different ways. In these analyses, the most important property which determined the suitability of a multispectral imager for glacier surface classification was its radiometric range (i.e. gain settings). Low resolution imagery (250. m. pixels) is ... : A. Pope was supported by the National Science Foundation Graduate Research Fellowship Programme under Grant No. DGE-1038596. Further research support came from UK Natural Environment Research Council's Field Spectroscopy Facility, ARCFAC (the European Centre for Arctic Environmental Research), Trinity College Cambridge, Sigma Xi, the Norwegian Marshall Fund, the Explorers Club, the National Geographic Society Young Explorers Program, the Scott Polar Research Institute, the Cambridge University Geography Department, the Cambridge University Department of Anglo-Saxon, Norse, and Celtic Studies, and the Cambridge University Worts Fund. ... Text Arctic Scott Polar Research Institute DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Glaciers
Snow
Multispectral
Classification
Principal component analysis
spellingShingle Glaciers
Snow
Multispectral
Classification
Principal component analysis
Pope, A
Rees, WG
Impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ...
topic_facet Glaciers
Snow
Multispectral
Classification
Principal component analysis
description Using multispectral remote sensing, glacier surfaces can be classified into a range of zones. The properties of these classes are used for a range of glaciological applications including mass balance measurements, glacial hydrology, and melt modelling. However, it is not immediately evident that multispectral data should be optimal for imaging glaciers and ice caps. Thus, this investigation takes an inverse perspective. Taking into account spectral and radiometric properties, in situ spectral reflectance data were used to simulate glacier surface response for a suite of multispectral sensors. Sensor-simulated data were classified and compared. In addition, airborne multispectral imagery was classified for a range of spatial resolutions and intercompared in three different ways. In these analyses, the most important property which determined the suitability of a multispectral imager for glacier surface classification was its radiometric range (i.e. gain settings). Low resolution imagery (250. m. pixels) is ... : A. Pope was supported by the National Science Foundation Graduate Research Fellowship Programme under Grant No. DGE-1038596. Further research support came from UK Natural Environment Research Council's Field Spectroscopy Facility, ARCFAC (the European Centre for Arctic Environmental Research), Trinity College Cambridge, Sigma Xi, the Norwegian Marshall Fund, the Explorers Club, the National Geographic Society Young Explorers Program, the Scott Polar Research Institute, the Cambridge University Geography Department, the Cambridge University Department of Anglo-Saxon, Norse, and Celtic Studies, and the Cambridge University Worts Fund. ...
format Text
author Pope, A
Rees, WG
author_facet Pope, A
Rees, WG
author_sort Pope, A
title Impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ...
title_short Impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ...
title_full Impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ...
title_fullStr Impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ...
title_full_unstemmed Impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ...
title_sort impact of spatial, spectral, and radiometric properties of multispectral imagers on glacier surface classification ...
publisher Apollo - University of Cambridge Repository
publishDate 2014
url https://dx.doi.org/10.17863/cam.15555
https://www.repository.cam.ac.uk/handle/1810/301386
geographic Arctic
geographic_facet Arctic
genre Arctic
Scott Polar Research Institute
genre_facet Arctic
Scott Polar Research Institute
op_doi https://doi.org/10.17863/cam.15555
_version_ 1766341367132323840