Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020

Devon Ice Cap in Nunavut, Canada, is one of the largest ice caps in the Canadian Arctic. A complete melting of the glacier would mean a global sea level rise of 1 cm. Since data collection and exploration of the glacier began in 1961, the glacier area has decreased by 2.4% (about 340 km2) (Boon et a...

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Bibliographic Details
Main Author: Rieger, Maximilian
Format: Thesis
Language:unknown
Published: 2020
Subjects:
Online Access:https://elib.dlr.de/137411/
id ftdlr:oai:elib.dlr.de:137411
record_format openpolar
spelling ftdlr:oai:elib.dlr.de:137411 2023-05-15T15:15:47+02:00 Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020 Rieger, Maximilian 2020-11 https://elib.dlr.de/137411/ unknown Rieger, Maximilian (2020) Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020. Bachelorarbeit, Hochschule München. Dynamik der Landoberfläche Hochschulschrift NonPeerReviewed 2020 ftdlr 2021-03-08T00:03:52Z Devon Ice Cap in Nunavut, Canada, is one of the largest ice caps in the Canadian Arctic. A complete melting of the glacier would mean a global sea level rise of 1 cm. Since data collection and exploration of the glacier began in 1961, the glacier area has decreased by 2.4% (about 340 km2) (Boon et al., 2010). This bachelor thesis deals with the classification and mapping of the different glacier zones for the observation period from 2017 to 2020 by analysing satellite radar data. As source data, TerraSAR-X backscatter values in the X-band pre-processed by the German Aerospace Center (DLR) into the MutliSAR System were used. These contain the backscatter values of radar image scenes as georeferenced raster files. The data are available for the observation period for three orbits in temporal resolution of 11 days. The geometric resolution is 40 m * 40 m per pixel. Backscatter values of objects in the radar image depend on their dielectric constant (signal transmission) and the image geometry of the radar zone. The backscatter of glacier zones can be used for the detection of zone classes. In this work, backscattered areas are associated with specific glacier zones, linked to an elevation model of the TanDEM-X mission and temperature data to provide information about the structure of the Devon Ice Cap and its development over the observation period. The goal of this work is to use remote sensing data to make statements about the composition and changes of the glacier and to link these to local meteorological data. Finally, the influence of the topography of the terrain on the classification quality is analyzed. To visualize the results, maps and time series are generated, on which the seasonal and long-term effects can be traced. Thesis Arctic glacier* Ice cap Nunavut German Aerospace Center: elib - DLR electronic library Arctic Nunavut Canada Devon Ice Cap ENVELOPE(-82.499,-82.499,75.335,75.335)
institution Open Polar
collection German Aerospace Center: elib - DLR electronic library
op_collection_id ftdlr
language unknown
topic Dynamik der Landoberfläche
spellingShingle Dynamik der Landoberfläche
Rieger, Maximilian
Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020
topic_facet Dynamik der Landoberfläche
description Devon Ice Cap in Nunavut, Canada, is one of the largest ice caps in the Canadian Arctic. A complete melting of the glacier would mean a global sea level rise of 1 cm. Since data collection and exploration of the glacier began in 1961, the glacier area has decreased by 2.4% (about 340 km2) (Boon et al., 2010). This bachelor thesis deals with the classification and mapping of the different glacier zones for the observation period from 2017 to 2020 by analysing satellite radar data. As source data, TerraSAR-X backscatter values in the X-band pre-processed by the German Aerospace Center (DLR) into the MutliSAR System were used. These contain the backscatter values of radar image scenes as georeferenced raster files. The data are available for the observation period for three orbits in temporal resolution of 11 days. The geometric resolution is 40 m * 40 m per pixel. Backscatter values of objects in the radar image depend on their dielectric constant (signal transmission) and the image geometry of the radar zone. The backscatter of glacier zones can be used for the detection of zone classes. In this work, backscattered areas are associated with specific glacier zones, linked to an elevation model of the TanDEM-X mission and temperature data to provide information about the structure of the Devon Ice Cap and its development over the observation period. The goal of this work is to use remote sensing data to make statements about the composition and changes of the glacier and to link these to local meteorological data. Finally, the influence of the topography of the terrain on the classification quality is analyzed. To visualize the results, maps and time series are generated, on which the seasonal and long-term effects can be traced.
format Thesis
author Rieger, Maximilian
author_facet Rieger, Maximilian
author_sort Rieger, Maximilian
title Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020
title_short Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020
title_full Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020
title_fullStr Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020
title_full_unstemmed Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020
title_sort classification and mapping of the devon ice cap based on terrasar-x data from 2017 to 2020
publishDate 2020
url https://elib.dlr.de/137411/
long_lat ENVELOPE(-82.499,-82.499,75.335,75.335)
geographic Arctic
Nunavut
Canada
Devon Ice Cap
geographic_facet Arctic
Nunavut
Canada
Devon Ice Cap
genre Arctic
glacier*
Ice cap
Nunavut
genre_facet Arctic
glacier*
Ice cap
Nunavut
op_relation Rieger, Maximilian (2020) Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020. Bachelorarbeit, Hochschule München.
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