The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. An approach based on field- and satellite data.
The rich broadleaved forests of North Norway have high species diversity. Mappings of biodiversity have been undertaken in the two municipalities Målselv and Bardu, but these mappings are far from exhaustive. This study examines classification methods for mapping rich broadleaved forests with the us...
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Universitetet i Tromsø
2007
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ftunivtroemsoe:oai:munin.uit.no:10037/1205 2024-06-02T08:04:05+00:00 The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. An approach based on field- and satellite data. Stabursvik, Ellen Margrethe 2007-08 2559423 bytes application/pdf https://hdl.handle.net/10037/1205 eng eng Universitetet i Tromsø University of Tromsø https://hdl.handle.net/10037/1205 URN:NBN:no-uit_munin_960 openAccess Copyright 2007 The Author(s) VDP::Matematikk og naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488 VDP::Agriculture and fishery disciplines: 900::Agriculture disciplines: 910::Management of natural resources: 914 Landsat rich broadleaved forest classification vegetation indices NDVI Målselv Bardu vegetation mapping satellite mapping biodiversity Master thesis Mastergradsoppgave 2007 ftunivtroemsoe 2024-05-07T08:41:49Z The rich broadleaved forests of North Norway have high species diversity. Mappings of biodiversity have been undertaken in the two municipalities Målselv and Bardu, but these mappings are far from exhaustive. This study examines classification methods for mapping rich broadleaved forests with the use of Landsat ETM+ images, and with vegetation indices as ancillary data. Three classifications were made; one supervised (on a July image) and two unsupervised (on the July image and a September image). Of these, the unsupervised classification of the July image had the best Overall Accuracy at 60.59 % and a Kappa coefficient of 0.4262. It seems that it is somewhat difficult to differentiate between the various rich broadleaved forest types with the use of Landsat ETM+ images, with their medium resolution, and a per-pixel classification. But with the added use of a tresholded NDVI it is possible to discern richer forest types in the study area, and to some degree imply what kind of forest we might expect to find based on the best classifications. I have compared my findings with the earlier biodiversity maps, and on this background I suggest that a new, and more thorough, mapping of the region is carried out. Master Thesis Bardu Målselv North Norway University of Tromsø: Munin Open Research Archive Bardu ENVELOPE(18.347,18.347,68.859,68.859) Målselv ENVELOPE(18.615,18.615,69.124,69.124) Norway |
institution |
Open Polar |
collection |
University of Tromsø: Munin Open Research Archive |
op_collection_id |
ftunivtroemsoe |
language |
English |
topic |
VDP::Matematikk og naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488 VDP::Agriculture and fishery disciplines: 900::Agriculture disciplines: 910::Management of natural resources: 914 Landsat rich broadleaved forest classification vegetation indices NDVI Målselv Bardu vegetation mapping satellite mapping biodiversity |
spellingShingle |
VDP::Matematikk og naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488 VDP::Agriculture and fishery disciplines: 900::Agriculture disciplines: 910::Management of natural resources: 914 Landsat rich broadleaved forest classification vegetation indices NDVI Målselv Bardu vegetation mapping satellite mapping biodiversity Stabursvik, Ellen Margrethe The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. An approach based on field- and satellite data. |
topic_facet |
VDP::Matematikk og naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488 VDP::Agriculture and fishery disciplines: 900::Agriculture disciplines: 910::Management of natural resources: 914 Landsat rich broadleaved forest classification vegetation indices NDVI Målselv Bardu vegetation mapping satellite mapping biodiversity |
description |
The rich broadleaved forests of North Norway have high species diversity. Mappings of biodiversity have been undertaken in the two municipalities Målselv and Bardu, but these mappings are far from exhaustive. This study examines classification methods for mapping rich broadleaved forests with the use of Landsat ETM+ images, and with vegetation indices as ancillary data. Three classifications were made; one supervised (on a July image) and two unsupervised (on the July image and a September image). Of these, the unsupervised classification of the July image had the best Overall Accuracy at 60.59 % and a Kappa coefficient of 0.4262. It seems that it is somewhat difficult to differentiate between the various rich broadleaved forest types with the use of Landsat ETM+ images, with their medium resolution, and a per-pixel classification. But with the added use of a tresholded NDVI it is possible to discern richer forest types in the study area, and to some degree imply what kind of forest we might expect to find based on the best classifications. I have compared my findings with the earlier biodiversity maps, and on this background I suggest that a new, and more thorough, mapping of the region is carried out. |
format |
Master Thesis |
author |
Stabursvik, Ellen Margrethe |
author_facet |
Stabursvik, Ellen Margrethe |
author_sort |
Stabursvik, Ellen Margrethe |
title |
The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. An approach based on field- and satellite data. |
title_short |
The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. An approach based on field- and satellite data. |
title_full |
The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. An approach based on field- and satellite data. |
title_fullStr |
The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. An approach based on field- and satellite data. |
title_full_unstemmed |
The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. An approach based on field- and satellite data. |
title_sort |
challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area. an approach based on field- and satellite data. |
publisher |
Universitetet i Tromsø |
publishDate |
2007 |
url |
https://hdl.handle.net/10037/1205 |
long_lat |
ENVELOPE(18.347,18.347,68.859,68.859) ENVELOPE(18.615,18.615,69.124,69.124) |
geographic |
Bardu Målselv Norway |
geographic_facet |
Bardu Målselv Norway |
genre |
Bardu Målselv North Norway |
genre_facet |
Bardu Målselv North Norway |
op_relation |
https://hdl.handle.net/10037/1205 URN:NBN:no-uit_munin_960 |
op_rights |
openAccess Copyright 2007 The Author(s) |
_version_ |
1800748707283468288 |