Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery

The focus of this work is to investigate and apply the remote sensing method of object-based image analysis (OBIA) for vegetation classification of a permafrost underlain peatland in sub-arctic Sweden, by using aerial imagery of high resolution. Since the northern landscapes are an important source...

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Main Author: Giljum, Marco
Format: Other/Unknown Material
Language:English
Published: Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap 2014
Subjects:
Online Access:http://lup.lub.lu.se/student-papers/record/4679307
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spelling ftulundlupsp:oai:lup-student-papers.lub.lu.se:4679307 2023-07-30T03:55:22+02:00 Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery Giljum, Marco 2014 application/pdf http://lup.lub.lu.se/student-papers/record/4679307 eng eng Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap http://lup.lub.lu.se/student-papers/record/4679307 Physical Geography and Ecosystem Analysis Object-Based Image Analysis OBIA Vegetation Classification Permafrost Arctic Peatland Remote Sensing Aerial Photography Environmental Monitoring Landscape Analysis Earth and Environmental Sciences H2 2014 ftulundlupsp 2023-07-11T20:07:44Z The focus of this work is to investigate and apply the remote sensing method of object-based image analysis (OBIA) for vegetation classification of a permafrost underlain peatland in sub-arctic Sweden, by using aerial imagery of high resolution. Since the northern landscapes are an important source of naturally stored CH4 and CO2, their contribution to the global carbon cycle is a focus in research about climate change and the global methane exchange. Climate change affects permafrost soils by future increases in the mean temperature and precipitation. It further influences the depth of the frozen layer, and the thickness of the active layer above permafrost increases. This complex relationship results into a changing future landscape distribution of the vegetation at permafrost peatlands. The change has an effect on the exchange of CH4 in particular permafrost areas. For that reason, knowledge about the vegetation distribution of plant communities is interesting for ecological studies. In this work, the observed area is Stordalen mire, which is situated in Swedish Lapland. At this peatland, a landscape change is currently visible as it occurs as variations in the vegetation pattern above the permafrost and by an obvious permafrost thaw. A number of studies focus on the mire and the place has a long history of research in climate change. So far, there is no detailed vegetation map of Stordalen available, indicating the relative spatial distribution of vegetation. Therefore, the main aim is to use a suitable technique to derive a detailed vegetation map by supervised classification. To carry out the information needed, digital aerial photography of high spatial resolution was used. The extraction of thematic information from that data was done by a combination of OBIA methods. Remote sensing has the capability to explore distant regions, and the usage of digital aerial imagery of high resolution allowed to captures the small size of structures of vegetation. It was possible to identify single plant communities ... Other/Unknown Material Abisko Arctic Climate change permafrost Lapland Lund University Publications Student Papers (LUP-SP) Arctic Abisko ENVELOPE(18.829,18.829,68.349,68.349) Stordalen ENVELOPE(7.337,7.337,62.510,62.510)
institution Open Polar
collection Lund University Publications Student Papers (LUP-SP)
op_collection_id ftulundlupsp
language English
topic Physical Geography and Ecosystem Analysis
Object-Based Image Analysis
OBIA
Vegetation Classification
Permafrost
Arctic Peatland
Remote Sensing
Aerial Photography
Environmental Monitoring
Landscape Analysis
Earth and Environmental Sciences
spellingShingle Physical Geography and Ecosystem Analysis
Object-Based Image Analysis
OBIA
Vegetation Classification
Permafrost
Arctic Peatland
Remote Sensing
Aerial Photography
Environmental Monitoring
Landscape Analysis
Earth and Environmental Sciences
Giljum, Marco
Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery
topic_facet Physical Geography and Ecosystem Analysis
Object-Based Image Analysis
OBIA
Vegetation Classification
Permafrost
Arctic Peatland
Remote Sensing
Aerial Photography
Environmental Monitoring
Landscape Analysis
Earth and Environmental Sciences
description The focus of this work is to investigate and apply the remote sensing method of object-based image analysis (OBIA) for vegetation classification of a permafrost underlain peatland in sub-arctic Sweden, by using aerial imagery of high resolution. Since the northern landscapes are an important source of naturally stored CH4 and CO2, their contribution to the global carbon cycle is a focus in research about climate change and the global methane exchange. Climate change affects permafrost soils by future increases in the mean temperature and precipitation. It further influences the depth of the frozen layer, and the thickness of the active layer above permafrost increases. This complex relationship results into a changing future landscape distribution of the vegetation at permafrost peatlands. The change has an effect on the exchange of CH4 in particular permafrost areas. For that reason, knowledge about the vegetation distribution of plant communities is interesting for ecological studies. In this work, the observed area is Stordalen mire, which is situated in Swedish Lapland. At this peatland, a landscape change is currently visible as it occurs as variations in the vegetation pattern above the permafrost and by an obvious permafrost thaw. A number of studies focus on the mire and the place has a long history of research in climate change. So far, there is no detailed vegetation map of Stordalen available, indicating the relative spatial distribution of vegetation. Therefore, the main aim is to use a suitable technique to derive a detailed vegetation map by supervised classification. To carry out the information needed, digital aerial photography of high spatial resolution was used. The extraction of thematic information from that data was done by a combination of OBIA methods. Remote sensing has the capability to explore distant regions, and the usage of digital aerial imagery of high resolution allowed to captures the small size of structures of vegetation. It was possible to identify single plant communities ...
format Other/Unknown Material
author Giljum, Marco
author_facet Giljum, Marco
author_sort Giljum, Marco
title Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery
title_short Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery
title_full Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery
title_fullStr Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery
title_full_unstemmed Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery
title_sort object-based classification of vegetation at stordalen mire near abisko by using high-resolution aerial imagery
publisher Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap
publishDate 2014
url http://lup.lub.lu.se/student-papers/record/4679307
long_lat ENVELOPE(18.829,18.829,68.349,68.349)
ENVELOPE(7.337,7.337,62.510,62.510)
geographic Arctic
Abisko
Stordalen
geographic_facet Arctic
Abisko
Stordalen
genre Abisko
Arctic
Climate change
permafrost
Lapland
genre_facet Abisko
Arctic
Climate change
permafrost
Lapland
op_relation http://lup.lub.lu.se/student-papers/record/4679307
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