Land Use Cover Mapping of Water Melon and Cereals in Southern Italy
The new high-resolution images from the satellites as IKONOS, SPOT5, Quickbird2 give us the opportunity to map ground features, which were not detectable in the past, by using medium resolution remote sensed data (LANDSAT). More accurate and reliable maps of land cover can then be produced. However,...
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| Format: | Article |
| Language: | English |
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Elsevier
2010-06-01
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| Series: | Italian Journal of Agronomy |
| Online Access: | https://www.agronomy.it/index.php/agro/article/view/108 |
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| author | Costanza Fiorentino Domenico Ventrella Luisa Giglio Enza Di Giacomo Raffaele Lopez |
| author_facet | Costanza Fiorentino Domenico Ventrella Luisa Giglio Enza Di Giacomo Raffaele Lopez |
| author_sort | Costanza Fiorentino |
| collection | DOAJ |
| description | The new high-resolution images from the satellites as IKONOS, SPOT5, Quickbird2 give us the opportunity to map ground features, which were not detectable in the past, by using medium resolution remote sensed data (LANDSAT). More accurate and reliable maps of land cover can then be produced. However, classification procedure with these images is more complex than with the medium resolution remote sensing data for two main reasons: firstly, because of their exiguous number of spectral bands, secondly, owing to high spatial resolution, the assumption of pixel independence does not generally hold. It is then necessary to have a multi-temporal series of images or to use classifiers taking into account also proximal information. The data in this study were (i) a remote sensing image taken by SPOT5 satellite in July 2007 and used to discriminate the water melon cover class and, (ii) three multi-temporal remote sensing images taken by SPOT5 satellite in May, June and July 2008 used to discriminate water melon and cereal crop cover classes. For water melon recognition, providing a single image in 2007, an object-oriented technique was applied instead of a traditional, per pixel technique obtaining an increase of overall accuracy of 15%. In 2008, since it was available a multi-temporal data set, a traditional ‘Maximum Likelihood’ technique was applied for both water melon and cereal crop cover class. The overall accuracy is greater than 95%. |
| format | Article |
| id | doaj-art-0f13a43da08c445f85c8da8bd309ceec |
| institution | OA Journals |
| issn | 1125-4718 2039-6805 |
| language | English |
| publishDate | 2010-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Italian Journal of Agronomy |
| spelling | doaj-art-0f13a43da08c445f85c8da8bd309ceec2025-08-20T01:55:02ZengElsevierItalian Journal of Agronomy1125-47182039-68052010-06-015210.4081/ija.2010.18571Land Use Cover Mapping of Water Melon and Cereals in Southern ItalyCostanza FiorentinoDomenico VentrellaLuisa GiglioEnza Di GiacomoRaffaele LopezThe new high-resolution images from the satellites as IKONOS, SPOT5, Quickbird2 give us the opportunity to map ground features, which were not detectable in the past, by using medium resolution remote sensed data (LANDSAT). More accurate and reliable maps of land cover can then be produced. However, classification procedure with these images is more complex than with the medium resolution remote sensing data for two main reasons: firstly, because of their exiguous number of spectral bands, secondly, owing to high spatial resolution, the assumption of pixel independence does not generally hold. It is then necessary to have a multi-temporal series of images or to use classifiers taking into account also proximal information. The data in this study were (i) a remote sensing image taken by SPOT5 satellite in July 2007 and used to discriminate the water melon cover class and, (ii) three multi-temporal remote sensing images taken by SPOT5 satellite in May, June and July 2008 used to discriminate water melon and cereal crop cover classes. For water melon recognition, providing a single image in 2007, an object-oriented technique was applied instead of a traditional, per pixel technique obtaining an increase of overall accuracy of 15%. In 2008, since it was available a multi-temporal data set, a traditional ‘Maximum Likelihood’ technique was applied for both water melon and cereal crop cover class. The overall accuracy is greater than 95%.https://www.agronomy.it/index.php/agro/article/view/108 |
| spellingShingle | Costanza Fiorentino Domenico Ventrella Luisa Giglio Enza Di Giacomo Raffaele Lopez Land Use Cover Mapping of Water Melon and Cereals in Southern Italy Italian Journal of Agronomy |
| title | Land Use Cover Mapping of Water Melon and Cereals in Southern Italy |
| title_full | Land Use Cover Mapping of Water Melon and Cereals in Southern Italy |
| title_fullStr | Land Use Cover Mapping of Water Melon and Cereals in Southern Italy |
| title_full_unstemmed | Land Use Cover Mapping of Water Melon and Cereals in Southern Italy |
| title_short | Land Use Cover Mapping of Water Melon and Cereals in Southern Italy |
| title_sort | land use cover mapping of water melon and cereals in southern italy |
| url | https://www.agronomy.it/index.php/agro/article/view/108 |
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