Contributions of multispectral images to the study of land cover in wet depressions of eastern Tunisia
Eastern Tunisia is dotted with varied wetlands such as lagoons, sabkhas, garaas… These wetlands, at the interface between land and water, are rich, diverse and dynamic environments. Remote sensing shows potential and efficiency in the detection and characterization of these environments, although th...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-12-01
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| Series: | Egyptian Journal of Remote Sensing and Space Sciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110982320303380 |
| _version_ | 1818934928955408384 |
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| author | Walid Chouari |
| author_facet | Walid Chouari |
| author_sort | Walid Chouari |
| collection | DOAJ |
| description | Eastern Tunisia is dotted with varied wetlands such as lagoons, sabkhas, garaas… These wetlands, at the interface between land and water, are rich, diverse and dynamic environments. Remote sensing shows potential and efficiency in the detection and characterization of these environments, although these humid depressions are difficult to define. The implementation of new optical satellite sensors characterized by High and Very High Spatial Resolution (HSR and VHSR) and by a high temporal repetitiveness, completes the field data and allows to envisage a delineation of the wet depression and a detailed detection of its land use. The purpose of this article is to determine whether the VHSR image, with its very rich spatial resolution, offers an added value for the detection of these diversified depressions, in comparison with the HSR image with richer spectral resolution. The results of the analysis show that the Ikonos image at VHSR compensates for the spectral richness of Sentinel-2 images at HSR. The “object-oriented” classification method, widely used today in image processing for various applications, appears to be more suitable than the “pixel-based” method in VHSR image classification. The Normalized Difference Water Index (NDWI) and the Transformed Soil Adjusted Vegetation Index (TSAVI) have multiple interests in wetland detection, although moisture masks show some inefficiency in improving the quality of classifications. |
| first_indexed | 2024-12-20T05:12:04Z |
| format | Article |
| id | doaj.art-b3e31b178f504c80937c36a15ba161d5 |
| institution | Directory Open Access Journal |
| issn | 1110-9823 |
| language | English |
| last_indexed | 2024-12-20T05:12:04Z |
| publishDate | 2021-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Egyptian Journal of Remote Sensing and Space Sciences |
| spelling | doaj.art-b3e31b178f504c80937c36a15ba161d52022-12-21T19:52:15ZengElsevierEgyptian Journal of Remote Sensing and Space Sciences1110-98232021-12-01243443451Contributions of multispectral images to the study of land cover in wet depressions of eastern TunisiaWalid Chouari0Address: Sfax University, FLSH, SYFACTE Laboratory, (Tunisia).; King Faisal University (KSA), SYFACTE Laboratory, TunisiaEastern Tunisia is dotted with varied wetlands such as lagoons, sabkhas, garaas… These wetlands, at the interface between land and water, are rich, diverse and dynamic environments. Remote sensing shows potential and efficiency in the detection and characterization of these environments, although these humid depressions are difficult to define. The implementation of new optical satellite sensors characterized by High and Very High Spatial Resolution (HSR and VHSR) and by a high temporal repetitiveness, completes the field data and allows to envisage a delineation of the wet depression and a detailed detection of its land use. The purpose of this article is to determine whether the VHSR image, with its very rich spatial resolution, offers an added value for the detection of these diversified depressions, in comparison with the HSR image with richer spectral resolution. The results of the analysis show that the Ikonos image at VHSR compensates for the spectral richness of Sentinel-2 images at HSR. The “object-oriented” classification method, widely used today in image processing for various applications, appears to be more suitable than the “pixel-based” method in VHSR image classification. The Normalized Difference Water Index (NDWI) and the Transformed Soil Adjusted Vegetation Index (TSAVI) have multiple interests in wetland detection, although moisture masks show some inefficiency in improving the quality of classifications.http://www.sciencedirect.com/science/article/pii/S1110982320303380Eastern TunisiaWet depressionsClassification methodsMoisture index |
| spellingShingle | Walid Chouari Contributions of multispectral images to the study of land cover in wet depressions of eastern Tunisia Egyptian Journal of Remote Sensing and Space Sciences Eastern Tunisia Wet depressions Classification methods Moisture index |
| title | Contributions of multispectral images to the study of land cover in wet depressions of eastern Tunisia |
| title_full | Contributions of multispectral images to the study of land cover in wet depressions of eastern Tunisia |
| title_fullStr | Contributions of multispectral images to the study of land cover in wet depressions of eastern Tunisia |
| title_full_unstemmed | Contributions of multispectral images to the study of land cover in wet depressions of eastern Tunisia |
| title_short | Contributions of multispectral images to the study of land cover in wet depressions of eastern Tunisia |
| title_sort | contributions of multispectral images to the study of land cover in wet depressions of eastern tunisia |
| topic | Eastern Tunisia Wet depressions Classification methods Moisture index |
| url | http://www.sciencedirect.com/science/article/pii/S1110982320303380 |
| work_keys_str_mv | AT walidchouari contributionsofmultispectralimagestothestudyoflandcoverinwetdepressionsofeasterntunisia |