Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering
International audience The paper presents the cartographic processing of the Landsat TM image by the two unsupervised classification methods of SAGA GIS: ISODATA and K-means clustering. The approaches were tested and compared for land cover type mapping. Vegetation areas were detected and separated...
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Online Access: | https://doi.org/10.5937/AASer2152159L https://hal.archives-ouvertes.fr/hal-03504862/file/9.%20AAS%20356-21%20Lemenkova.pdf https://hal.archives-ouvertes.fr/hal-03504862 |
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fttriple:oai:gotriple.eu:10670/1.esan6r 2023-05-15T16:50:03+02:00 Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering Lemenkova, Polina Laboratory of Image Synthesis and Analysis, Ecole Polytechnique de Bruxelles, Université Libre de Bruxelles (ULB), Brussels, Belgium 2021-12-29 https://doi.org/10.5937/AASer2152159L https://hal.archives-ouvertes.fr/hal-03504862/file/9.%20AAS%20356-21%20Lemenkova.pdf https://hal.archives-ouvertes.fr/hal-03504862 en eng HAL CCSD University of Kragujevac - Faculty of Agronomy, Čačak hal-03504862 doi:10.5937/AASer2152159L 10670/1.esan6r https://hal.archives-ouvertes.fr/hal-03504862/file/9.%20AAS%20356-21%20Lemenkova.pdf https://hal.archives-ouvertes.fr/hal-03504862 lic_creative-commons Hyper Article en Ligne - Sciences de l'Homme et de la Société ISSN: 0354-9542 Acta Agriculturae Serbica Acta Agriculturae Serbica, University of Kragujevac - Faculty of Agronomy, Čačak, 2021, 26 (56), pp.159-165. ⟨10.5937/AASer2152159L⟩ SAGA GIS mapping vegetation K-means ISODATA clustering cartography machine learning geo manag Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2021 fttriple https://doi.org/10.5937/AASer2152159L 2023-01-22T17:01:06Z International audience The paper presents the cartographic processing of the Landsat TM image by the two unsupervised classification methods of SAGA GIS: ISODATA and K-means clustering. The approaches were tested and compared for land cover type mapping. Vegetation areas were detected and separated from other land cover types in the study area of southwestern Iceland. The number of clusters was set to ten classes. The processing of the satellite image by SAGA GIS was achieved using Imagery Classification tools in the Geoprocessing menu of SAGA GIS. Unsupervised classification performed effectively in the unlabeled pixels for the land cover types using machine learning in GIS. Following an iterative approach of clustering, the pixels were grouped in each step of the algorithm and the clusters were reassigned as centroids. The paper contributes to the technical development of the application of machine learning in cartography by demonstrating the effectiveness of SAGA GIS in remote sensing data processing applied for vegetation and environmental mapping. Article in Journal/Newspaper Iceland Unknown Acta agriculturae Serbica 26 52 159 165 |
institution |
Open Polar |
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language |
English |
topic |
SAGA GIS mapping vegetation K-means ISODATA clustering cartography machine learning geo manag |
spellingShingle |
SAGA GIS mapping vegetation K-means ISODATA clustering cartography machine learning geo manag Lemenkova, Polina Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering |
topic_facet |
SAGA GIS mapping vegetation K-means ISODATA clustering cartography machine learning geo manag |
description |
International audience The paper presents the cartographic processing of the Landsat TM image by the two unsupervised classification methods of SAGA GIS: ISODATA and K-means clustering. The approaches were tested and compared for land cover type mapping. Vegetation areas were detected and separated from other land cover types in the study area of southwestern Iceland. The number of clusters was set to ten classes. The processing of the satellite image by SAGA GIS was achieved using Imagery Classification tools in the Geoprocessing menu of SAGA GIS. Unsupervised classification performed effectively in the unlabeled pixels for the land cover types using machine learning in GIS. Following an iterative approach of clustering, the pixels were grouped in each step of the algorithm and the clusters were reassigned as centroids. The paper contributes to the technical development of the application of machine learning in cartography by demonstrating the effectiveness of SAGA GIS in remote sensing data processing applied for vegetation and environmental mapping. |
author2 |
Laboratory of Image Synthesis and Analysis, Ecole Polytechnique de Bruxelles, Université Libre de Bruxelles (ULB), Brussels, Belgium |
format |
Article in Journal/Newspaper |
author |
Lemenkova, Polina |
author_facet |
Lemenkova, Polina |
author_sort |
Lemenkova, Polina |
title |
Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering |
title_short |
Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering |
title_full |
Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering |
title_fullStr |
Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering |
title_full_unstemmed |
Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering |
title_sort |
evaluating land cover types from landsat tm using saga gis for vegetation mapping based on isodata and k-means clustering |
publisher |
HAL CCSD |
publishDate |
2021 |
url |
https://doi.org/10.5937/AASer2152159L https://hal.archives-ouvertes.fr/hal-03504862/file/9.%20AAS%20356-21%20Lemenkova.pdf https://hal.archives-ouvertes.fr/hal-03504862 |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Hyper Article en Ligne - Sciences de l'Homme et de la Société ISSN: 0354-9542 Acta Agriculturae Serbica Acta Agriculturae Serbica, University of Kragujevac - Faculty of Agronomy, Čačak, 2021, 26 (56), pp.159-165. ⟨10.5937/AASer2152159L⟩ |
op_relation |
hal-03504862 doi:10.5937/AASer2152159L 10670/1.esan6r https://hal.archives-ouvertes.fr/hal-03504862/file/9.%20AAS%20356-21%20Lemenkova.pdf https://hal.archives-ouvertes.fr/hal-03504862 |
op_rights |
lic_creative-commons |
op_doi |
https://doi.org/10.5937/AASer2152159L |
container_title |
Acta agriculturae Serbica |
container_volume |
26 |
container_issue |
52 |
container_start_page |
159 |
op_container_end_page |
165 |
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1766040242300649472 |