ISO Cluster Classifier by ArcGIS for Unsupervised Classification of the Landsat TM Image of Reykjavík
The paper presents the use of the Landsat TM image processed by the ArcGIS Spatial Analyst Tool for environmental mapping of southwestern Iceland, region of Reykjavik. Iceland is one of the most special Arctic regions with unique flora and landscapes. Its environment is presented by vulnerable ecosy...
Published in: | Frontiers in Marine Science |
---|---|
Main Author: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Zenodo
2021
|
Subjects: | |
Online Access: | https://doi.org/10.5281/zenodo.5068505 |
id |
ftzenodo:oai:zenodo.org:5068505 |
---|---|
record_format |
openpolar |
spelling |
ftzenodo:oai:zenodo.org:5068505 2024-09-15T18:13:18+00:00 ISO Cluster Classifier by ArcGIS for Unsupervised Classification of the Landsat TM Image of Reykjavík Lemenkova, Polina 2021-07-04 https://doi.org/10.5281/zenodo.5068505 eng eng Zenodo https://doi.org/10.5937/bnsr11-30488 https://doi.org/10.5281/zenodo.5068504 https://doi.org/10.5281/zenodo.5068505 oai:zenodo.org:5068505 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Bulletin of Natural Sciences Research, 11(1), 29-37, (2021-07-04) Machine learning Landsat TM ArcGIS Cartography info:eu-repo/semantics/article 2021 ftzenodo https://doi.org/10.5281/zenodo.506850510.5937/bnsr11-3048810.5281/zenodo.5068504 2024-07-26T11:58:15Z The paper presents the use of the Landsat TM image processed by the ArcGIS Spatial Analyst Tool for environmental mapping of southwestern Iceland, region of Reykjavik. Iceland is one of the most special Arctic regions with unique flora and landscapes. Its environment is presented by vulnerable ecosystems of highlands where vegetation is affected by climate, human or geologic factors: overgrazing, volcanism, annual temperature change. Therefore, mapping land cover types in Iceland contribute to the nature conservation, sustainable development and environmental monitoring purposes. This paper starts by review of the current trends in remote sensing, the importance of Landsat TM imagery for environmental mapping in general and Iceland in particular, and the requirements of GIS specifically for satellite image analysis. This is followed by the extended methodological workflow supported by illustrative print screens and technical description of data processing in ArcGIS. The data used in this research include Landsat TM image which was captured using GloVis and processed in ArcGIS. The methodology includes a workflow involving several technical steps of raster da ta processing in ArcGIS: 1) coordinate projecting, 2) panchromatic sharpening, 3) inspection of raster statistics, 4) spectral bands combination, 5) calculations, 6) unsupervised classification, 7) mapping. The classification was done by clustering technique using ISO Cluster algorithm and Maximum Likelihood Classification. This paper finally presents the results of the ISO Cluster application for Landsat TM image processing and concludes final remarks on the perspectives of environmental mapping based on Landsat TM image processing in ArcGIS.The results of the classification present landscapes divided into eight distinct land cover classes: 1) bare soils; 2) shrubs and smaller trees in the river valleys, urban areas including green spaces; 3) water areas; 4) forests including the Reykjanesfólkvangur National reserve; 5) ice-covered areas, glaciers and ... Article in Journal/Newspaper Iceland Reykjavík Reykjavík ice covered areas Zenodo Frontiers in Marine Science 10 |
institution |
Open Polar |
collection |
Zenodo |
op_collection_id |
ftzenodo |
language |
English |
topic |
Machine learning Landsat TM ArcGIS Cartography |
spellingShingle |
Machine learning Landsat TM ArcGIS Cartography Lemenkova, Polina ISO Cluster Classifier by ArcGIS for Unsupervised Classification of the Landsat TM Image of Reykjavík |
topic_facet |
Machine learning Landsat TM ArcGIS Cartography |
description |
The paper presents the use of the Landsat TM image processed by the ArcGIS Spatial Analyst Tool for environmental mapping of southwestern Iceland, region of Reykjavik. Iceland is one of the most special Arctic regions with unique flora and landscapes. Its environment is presented by vulnerable ecosystems of highlands where vegetation is affected by climate, human or geologic factors: overgrazing, volcanism, annual temperature change. Therefore, mapping land cover types in Iceland contribute to the nature conservation, sustainable development and environmental monitoring purposes. This paper starts by review of the current trends in remote sensing, the importance of Landsat TM imagery for environmental mapping in general and Iceland in particular, and the requirements of GIS specifically for satellite image analysis. This is followed by the extended methodological workflow supported by illustrative print screens and technical description of data processing in ArcGIS. The data used in this research include Landsat TM image which was captured using GloVis and processed in ArcGIS. The methodology includes a workflow involving several technical steps of raster da ta processing in ArcGIS: 1) coordinate projecting, 2) panchromatic sharpening, 3) inspection of raster statistics, 4) spectral bands combination, 5) calculations, 6) unsupervised classification, 7) mapping. The classification was done by clustering technique using ISO Cluster algorithm and Maximum Likelihood Classification. This paper finally presents the results of the ISO Cluster application for Landsat TM image processing and concludes final remarks on the perspectives of environmental mapping based on Landsat TM image processing in ArcGIS.The results of the classification present landscapes divided into eight distinct land cover classes: 1) bare soils; 2) shrubs and smaller trees in the river valleys, urban areas including green spaces; 3) water areas; 4) forests including the Reykjanesfólkvangur National reserve; 5) ice-covered areas, glaciers and ... |
format |
Article in Journal/Newspaper |
author |
Lemenkova, Polina |
author_facet |
Lemenkova, Polina |
author_sort |
Lemenkova, Polina |
title |
ISO Cluster Classifier by ArcGIS for Unsupervised Classification of the Landsat TM Image of Reykjavík |
title_short |
ISO Cluster Classifier by ArcGIS for Unsupervised Classification of the Landsat TM Image of Reykjavík |
title_full |
ISO Cluster Classifier by ArcGIS for Unsupervised Classification of the Landsat TM Image of Reykjavík |
title_fullStr |
ISO Cluster Classifier by ArcGIS for Unsupervised Classification of the Landsat TM Image of Reykjavík |
title_full_unstemmed |
ISO Cluster Classifier by ArcGIS for Unsupervised Classification of the Landsat TM Image of Reykjavík |
title_sort |
iso cluster classifier by arcgis for unsupervised classification of the landsat tm image of reykjavík |
publisher |
Zenodo |
publishDate |
2021 |
url |
https://doi.org/10.5281/zenodo.5068505 |
genre |
Iceland Reykjavík Reykjavík ice covered areas |
genre_facet |
Iceland Reykjavík Reykjavík ice covered areas |
op_source |
Bulletin of Natural Sciences Research, 11(1), 29-37, (2021-07-04) |
op_relation |
https://doi.org/10.5937/bnsr11-30488 https://doi.org/10.5281/zenodo.5068504 https://doi.org/10.5281/zenodo.5068505 oai:zenodo.org:5068505 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.506850510.5937/bnsr11-3048810.5281/zenodo.5068504 |
container_title |
Frontiers in Marine Science |
container_volume |
10 |
_version_ |
1810451027878477824 |