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spelling ftdatacite:10.6084/m9.figshare.13176872.v1 2023-05-15T15:15:18+02:00 SAGA GIS for information extraction on presence and conditions of vegetation of northern coast of Iceland based on the Landsat TM Lemenkova, Polina 2020 https://dx.doi.org/10.6084/m9.figshare.13176872.v1 https://figshare.com/articles/journal_contribution/SAGA_GIS_for_information_extraction_on_presence_and_conditions_of_vegetation_of_northern_coast_of_Iceland_based_on_the_Landsat_TM/13176872/1 unknown figshare https://dx.doi.org/10.6084/m9.figshare.13176872 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY 90901 Cartography FOS Environmental engineering Geography Physical Geography 40699 Physical Geography and Environmental Geoscience not elsewhere classified FOS Earth and related environmental sciences 80109 Pattern Recognition and Data Mining FOS Computer and information sciences 80106 Image Processing 120504 Land Use and Environmental Planning FOS Social and economic geography 59999 Environmental Sciences not elsewhere classified Environmental Science 50206 Environmental Monitoring 50203 Environmental Education and Extension Education 130306 Educational Technology and Computing FOS Educational sciences Text article-journal Journal contribution ScholarlyArticle 2020 ftdatacite https://doi.org/10.6084/m9.figshare.13176872.v1 https://doi.org/10.6084/m9.figshare.13176872 2021-11-05T12:55:41Z The paper aims to evaluate the presence and condition of vegetation by SAGA GIS. The study area covers northern coasts of Iceland including two fjords, the Eyjafjörður and the Skagafjörður, prosperous agricultural regions. The vegetation coverage in Iceland experience the impact of harsh climate, land use, livestock grazing, glacial ablation and volcanism. The data include the Landsat TM image. The methodology is based on computing raster bands for simulating Tassel Cap Transformation (wetness, greenness and brightness) and Enhanced Vegetation Index (EVI) sensitive to high biomass. The results include modelled three bands of brightness, greenness and wetness. Greenness variation shows the least values in ice-covered areas (-56.98 to -18.69). High values (-23.48 to 9.12) are in the valleys with dense vegetation, correlating with the geomorphology of the river network, the vegetation-free areas and ocean which corresponds to the peak of 30.87 to 41.19. The bell-shaped data distribution shows frequency 43.19–141.74 for vegetation indicating healthy state and canopy density. Maximal values are in ice-covered regions and glaciers (64°N- 65°N). Very low values (0 to -20) show desertification and mountainous rocks. Moderate values (20-40) indicate healthy vegetation. The most frequent data: -28,17 to 11,8. The EVI shows data variations (-0.14 to 0.04). The study contributes both to the regional studies of Arctic Iceland and methodological approach of remote sensing data processing by SAGA GIS. Text Arctic Iceland ice covered areas 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 90901 Cartography
FOS Environmental engineering
Geography
Physical Geography
40699 Physical Geography and Environmental Geoscience not elsewhere classified
FOS Earth and related environmental sciences
80109 Pattern Recognition and Data Mining
FOS Computer and information sciences
80106 Image Processing
120504 Land Use and Environmental Planning
FOS Social and economic geography
59999 Environmental Sciences not elsewhere classified
Environmental Science
50206 Environmental Monitoring
50203 Environmental Education and Extension
Education
130306 Educational Technology and Computing
FOS Educational sciences
spellingShingle 90901 Cartography
FOS Environmental engineering
Geography
Physical Geography
40699 Physical Geography and Environmental Geoscience not elsewhere classified
FOS Earth and related environmental sciences
80109 Pattern Recognition and Data Mining
FOS Computer and information sciences
80106 Image Processing
120504 Land Use and Environmental Planning
FOS Social and economic geography
59999 Environmental Sciences not elsewhere classified
Environmental Science
50206 Environmental Monitoring
50203 Environmental Education and Extension
Education
130306 Educational Technology and Computing
FOS Educational sciences
Lemenkova, Polina
SAGA GIS for information extraction on presence and conditions of vegetation of northern coast of Iceland based on the Landsat TM
topic_facet 90901 Cartography
FOS Environmental engineering
Geography
Physical Geography
40699 Physical Geography and Environmental Geoscience not elsewhere classified
FOS Earth and related environmental sciences
80109 Pattern Recognition and Data Mining
FOS Computer and information sciences
80106 Image Processing
120504 Land Use and Environmental Planning
FOS Social and economic geography
59999 Environmental Sciences not elsewhere classified
Environmental Science
50206 Environmental Monitoring
50203 Environmental Education and Extension
Education
130306 Educational Technology and Computing
FOS Educational sciences
description The paper aims to evaluate the presence and condition of vegetation by SAGA GIS. The study area covers northern coasts of Iceland including two fjords, the Eyjafjörður and the Skagafjörður, prosperous agricultural regions. The vegetation coverage in Iceland experience the impact of harsh climate, land use, livestock grazing, glacial ablation and volcanism. The data include the Landsat TM image. The methodology is based on computing raster bands for simulating Tassel Cap Transformation (wetness, greenness and brightness) and Enhanced Vegetation Index (EVI) sensitive to high biomass. The results include modelled three bands of brightness, greenness and wetness. Greenness variation shows the least values in ice-covered areas (-56.98 to -18.69). High values (-23.48 to 9.12) are in the valleys with dense vegetation, correlating with the geomorphology of the river network, the vegetation-free areas and ocean which corresponds to the peak of 30.87 to 41.19. The bell-shaped data distribution shows frequency 43.19–141.74 for vegetation indicating healthy state and canopy density. Maximal values are in ice-covered regions and glaciers (64°N- 65°N). Very low values (0 to -20) show desertification and mountainous rocks. Moderate values (20-40) indicate healthy vegetation. The most frequent data: -28,17 to 11,8. The EVI shows data variations (-0.14 to 0.04). The study contributes both to the regional studies of Arctic Iceland and methodological approach of remote sensing data processing by SAGA GIS.
format Text
author Lemenkova, Polina
author_facet Lemenkova, Polina
author_sort Lemenkova, Polina
title SAGA GIS for information extraction on presence and conditions of vegetation of northern coast of Iceland based on the Landsat TM
title_short SAGA GIS for information extraction on presence and conditions of vegetation of northern coast of Iceland based on the Landsat TM
title_full SAGA GIS for information extraction on presence and conditions of vegetation of northern coast of Iceland based on the Landsat TM
title_fullStr SAGA GIS for information extraction on presence and conditions of vegetation of northern coast of Iceland based on the Landsat TM
title_full_unstemmed SAGA GIS for information extraction on presence and conditions of vegetation of northern coast of Iceland based on the Landsat TM
title_sort saga gis for information extraction on presence and conditions of vegetation of northern coast of iceland based on the landsat tm
publisher figshare
publishDate 2020
url https://dx.doi.org/10.6084/m9.figshare.13176872.v1
https://figshare.com/articles/journal_contribution/SAGA_GIS_for_information_extraction_on_presence_and_conditions_of_vegetation_of_northern_coast_of_Iceland_based_on_the_Landsat_TM/13176872/1
geographic Arctic
geographic_facet Arctic
genre Arctic
Iceland
ice covered areas
genre_facet Arctic
Iceland
ice covered areas
op_relation https://dx.doi.org/10.6084/m9.figshare.13176872
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.13176872.v1
https://doi.org/10.6084/m9.figshare.13176872
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