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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Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap
2014
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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 |
_version_ |
1772818136547983360 |