COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INFESTATIONS IN CROATIA
This paper presents different approaches to map bark beetle infested forests in Croatia. Bark beetle infestation presents threat to forest ecosystems. Due to large unapproachable area, it also presents difficulties in mapping infested areas. This paper analyses available machine learning options in...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-4-W7-2023/83/2023/isprs-archives-XLVIII-4-W7-2023-83-2023.pdf |
| _version_ | 1797797567075975168 |
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| author | N. Kranjčić V. Cetl H. Matijević D. Markovinović |
| author_facet | N. Kranjčić V. Cetl H. Matijević D. Markovinović |
| author_sort | N. Kranjčić |
| collection | DOAJ |
| description | This paper presents different approaches to map bark beetle infested forests in Croatia. Bark beetle infestation presents threat to forest ecosystems. Due to large unapproachable area, it also presents difficulties in mapping infested areas. This paper analyses available machine learning options in open-source software QGIS and SAGA GIS. All options are performed on Copernicus data, Sentinel 2 satellite imagery. Machine learning and classification options are maximum likelihood classifier, minimum distance, artificial neural network, decision tree, K Nearest Neighbor, random forest, support vector machine, spectral angle mapper and Normal Bayes. Kappa values respectively are: 0.71; 0.72; 0.81; 0.68; 0.69; 0.75; 0.26; 0.60; 0.41 which shows highest classification accuracy for artificial neural networks method and lowest for support vector machine accuracy. |
| first_indexed | 2024-03-13T03:50:17Z |
| format | Article |
| id | doaj.art-deb248d148fd4cfea4729c579bd780d5 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-03-13T03:50:17Z |
| publishDate | 2023-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-deb248d148fd4cfea4729c579bd780d52023-06-22T16:21:24ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342023-06-01XLVIII-4-W7-2023838810.5194/isprs-archives-XLVIII-4-W7-2023-83-2023COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INFESTATIONS IN CROATIAN. Kranjčić0V. Cetl1H. Matijević2D. Markovinović3Faculty of Geotechnical Engineering, University of Zagreb, Varaždin, CroatiaDepartment for Geodesy and Geomatics, University North, Varaždin, CroatiaDepartment for Geodesy and Geomatics, University North, Varaždin, CroatiaDepartment for Geodesy and Geomatics, University North, Varaždin, CroatiaThis paper presents different approaches to map bark beetle infested forests in Croatia. Bark beetle infestation presents threat to forest ecosystems. Due to large unapproachable area, it also presents difficulties in mapping infested areas. This paper analyses available machine learning options in open-source software QGIS and SAGA GIS. All options are performed on Copernicus data, Sentinel 2 satellite imagery. Machine learning and classification options are maximum likelihood classifier, minimum distance, artificial neural network, decision tree, K Nearest Neighbor, random forest, support vector machine, spectral angle mapper and Normal Bayes. Kappa values respectively are: 0.71; 0.72; 0.81; 0.68; 0.69; 0.75; 0.26; 0.60; 0.41 which shows highest classification accuracy for artificial neural networks method and lowest for support vector machine accuracy.https://isprs-archives.copernicus.org/articles/XLVIII-4-W7-2023/83/2023/isprs-archives-XLVIII-4-W7-2023-83-2023.pdf |
| spellingShingle | N. Kranjčić V. Cetl H. Matijević D. Markovinović COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INFESTATIONS IN CROATIA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INFESTATIONS IN CROATIA |
| title_full | COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INFESTATIONS IN CROATIA |
| title_fullStr | COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INFESTATIONS IN CROATIA |
| title_full_unstemmed | COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INFESTATIONS IN CROATIA |
| title_short | COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INFESTATIONS IN CROATIA |
| title_sort | comparing different machine learning options to map bark beetle infestations in croatia |
| url | https://isprs-archives.copernicus.org/articles/XLVIII-4-W7-2023/83/2023/isprs-archives-XLVIII-4-W7-2023-83-2023.pdf |
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