Principal component analysis applied to remote sensing
<p>The main objective of this article was to show an application of principal component analysis (PCA) which is used in two science degrees. Particularly, PCA analysis was used to obtain information of the land cover from satellite images. Three Landsat images were selected from two areas whic...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitat Politècnica de València
2013-06-01
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| Series: | Modelling in Science Education and Learning |
| Subjects: | |
| Online Access: | http://polipapers.upv.es/index.php/MSEL/article/view/1905 |
| _version_ | 1828288458448175104 |
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| author | Javier Estornell Jesus M. Martí-Gavliá M. Teresa Sebastiá Jesus Mengual |
| author_facet | Javier Estornell Jesus M. Martí-Gavliá M. Teresa Sebastiá Jesus Mengual |
| author_sort | Javier Estornell |
| collection | DOAJ |
| description | <p>The main objective of this article was to show an application of principal component analysis (PCA) which is used in two science degrees. Particularly, PCA analysis was used to obtain information of the land cover from satellite images. Three Landsat images were selected from two areas which were located in the municipalities of Gandia and Vallat, both in the Valencia province (Spain). In the first study area, just one Landsat image of the 2005 year was used. In the second study area, two Landsat images were used taken in the 1994 and 2000 years to analyse the most significant changes in the land cover. According to the results, the second principal component of the Gandia area image allowed detecting the presence of vegetation. The same component in the Vallat area allowed detecting a forestry area affected by a forest fire. Consequently in this study we confirmed the feasibility of using PCA in remote sensing to extract land use information.</p> |
| first_indexed | 2024-04-13T10:05:58Z |
| format | Article |
| id | doaj.art-1b7e43669c2e465cbd115d6a66484e04 |
| institution | Directory Open Access Journal |
| issn | 1988-3145 |
| language | English |
| last_indexed | 2024-04-13T10:05:58Z |
| publishDate | 2013-06-01 |
| publisher | Universitat Politècnica de València |
| record_format | Article |
| series | Modelling in Science Education and Learning |
| spelling | doaj.art-1b7e43669c2e465cbd115d6a66484e042022-12-22T02:51:06ZengUniversitat Politècnica de ValènciaModelling in Science Education and Learning1988-31452013-06-0160838910.4995/msel.2013.19051538Principal component analysis applied to remote sensingJavier Estornell0Jesus M. Martí-Gavliá1M. Teresa Sebastiá2Jesus Mengual3Universitat Politècnica de ValènciaUniversitat Politècnica de ValènciaUniversitat Politècnica de ValènciaUniversitat Politècnica de València<p>The main objective of this article was to show an application of principal component analysis (PCA) which is used in two science degrees. Particularly, PCA analysis was used to obtain information of the land cover from satellite images. Three Landsat images were selected from two areas which were located in the municipalities of Gandia and Vallat, both in the Valencia province (Spain). In the first study area, just one Landsat image of the 2005 year was used. In the second study area, two Landsat images were used taken in the 1994 and 2000 years to analyse the most significant changes in the land cover. According to the results, the second principal component of the Gandia area image allowed detecting the presence of vegetation. The same component in the Vallat area allowed detecting a forestry area affected by a forest fire. Consequently in this study we confirmed the feasibility of using PCA in remote sensing to extract land use information.</p>http://polipapers.upv.es/index.php/MSEL/article/view/1905PCALand useRemote sensingLandsat |
| spellingShingle | Javier Estornell Jesus M. Martí-Gavliá M. Teresa Sebastiá Jesus Mengual Principal component analysis applied to remote sensing Modelling in Science Education and Learning PCA Land use Remote sensing Landsat |
| title | Principal component analysis applied to remote sensing |
| title_full | Principal component analysis applied to remote sensing |
| title_fullStr | Principal component analysis applied to remote sensing |
| title_full_unstemmed | Principal component analysis applied to remote sensing |
| title_short | Principal component analysis applied to remote sensing |
| title_sort | principal component analysis applied to remote sensing |
| topic | PCA Land use Remote sensing Landsat |
| url | http://polipapers.upv.es/index.php/MSEL/article/view/1905 |
| work_keys_str_mv | AT javierestornell principalcomponentanalysisappliedtoremotesensing AT jesusmmartigavlia principalcomponentanalysisappliedtoremotesensing AT mteresasebastia principalcomponentanalysisappliedtoremotesensing AT jesusmengual principalcomponentanalysisappliedtoremotesensing |