Chapter Mapping submerged vegetation and water quality using multi- and hyperspectral imagery of Oristano Gulf (Italy)
Shallow water habitats are among the most important and productive ecosystems on the planet. These ecosystems, which include seagrass meadows, are important biodiversity hotspots. The spread of seagrass can be managed by looking at the seabed cover and how it changes over the year. To this end, sate...
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| Format: | Online |
| Language: | English |
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Firenze University Press
2025
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| Online Access: | ONIX_20250801T173835_9791221505566_269 |
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| author | Mangano, Salvatore Pinardi, Monica Pellegrino, Andrea FABBRETTO, ALICE Giardino, Claudia TARAMELLI, Andrea SATTA, ANDREA Bresciani, Mariano |
| author_browse | Bresciani, Mariano FABBRETTO, ALICE Giardino, Claudia Mangano, Salvatore Pellegrino, Andrea Pinardi, Monica SATTA, ANDREA TARAMELLI, Andrea |
| author_facet | Mangano, Salvatore Pinardi, Monica Pellegrino, Andrea FABBRETTO, ALICE Giardino, Claudia TARAMELLI, Andrea SATTA, ANDREA Bresciani, Mariano |
| author_sort | Mangano, Salvatore |
| collection | Directory of Open Access Books |
| description | Shallow water habitats are among the most important and productive ecosystems on the planet. These ecosystems, which include seagrass meadows, are important biodiversity hotspots. The spread of seagrass can be managed by looking at the seabed cover and how it changes over the year. To this end, satellite-derived products of substrate and vegetation cover at different spatio-temporal resolutions can help water managers and users to better understand and manage seagrass beds in shallow waters (Kutser et al., 2022). The main objective of this study is to test and apply algorithms to obtain bottom substrate, canopy cover together with water quality maps (e.g. SPM, Chl-a) from hyperspectral (e.g. PRISMA) and multispectral (e.g. Sentinel-2) satellite data. The study is developed in the framework of the PRISMA SCIENZA OVERSEE project and focuses on the coastal areas of the Gulf of Oristano (Sardinia, Italy). Changes in substrate cover have been tracked for the period May-October 2022. Spatio-temporal variability of Posidonia oceanica has been studied and discussed in relation to environmental features and human activities. |
| format | Online |
| id | doab-20.500.12854ir-163293 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Firenze University Press |
| publisherStr | Firenze University Press |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1632932025-08-02T05:00:53Z Chapter Mapping submerged vegetation and water quality using multi- and hyperspectral imagery of Oristano Gulf (Italy) Mangano, Salvatore Pinardi, Monica Pellegrino, Andrea FABBRETTO, ALICE Giardino, Claudia TARAMELLI, Andrea SATTA, ANDREA Bresciani, Mariano Seagrass Remote Sensing PRISMA Water Quality Shallow water habitats are among the most important and productive ecosystems on the planet. These ecosystems, which include seagrass meadows, are important biodiversity hotspots. The spread of seagrass can be managed by looking at the seabed cover and how it changes over the year. To this end, satellite-derived products of substrate and vegetation cover at different spatio-temporal resolutions can help water managers and users to better understand and manage seagrass beds in shallow waters (Kutser et al., 2022). The main objective of this study is to test and apply algorithms to obtain bottom substrate, canopy cover together with water quality maps (e.g. SPM, Chl-a) from hyperspectral (e.g. PRISMA) and multispectral (e.g. Sentinel-2) satellite data. The study is developed in the framework of the PRISMA SCIENZA OVERSEE project and focuses on the coastal areas of the Gulf of Oristano (Sardinia, Italy). Changes in substrate cover have been tracked for the period May-October 2022. Spatio-temporal variability of Posidonia oceanica has been studied and discussed in relation to environmental features and human activities. 2025-08-02T05:00:52Z 2025-08-02T05:00:52Z 2025-08-01T15:57:16Z 2024 chapter ONIX_20250801T173835_9791221505566_269 2975-0288 https://library.oapen.org/handle/20.500.12657/104819 9791221505566 https://directory.doabooks.org/handle/20.500.12854/163293 eng Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques open access image/jpeg Attribution-NonCommercial-ShareAlike 4.0 International https://library.oapen.org/bitstream/20.500.12657/104819/1/43669.pdf Firenze University Press 10.36253/979-12-215-0556-6.24 10.36253/979-12-215-0556-6.24 2ec4474d-93b1-4cfa-b313-9c6019b51b1a 9791221505566 8 Florence open access |
| spellingShingle | Seagrass Remote Sensing PRISMA Water Quality Mangano, Salvatore Pinardi, Monica Pellegrino, Andrea FABBRETTO, ALICE Giardino, Claudia TARAMELLI, Andrea SATTA, ANDREA Bresciani, Mariano Chapter Mapping submerged vegetation and water quality using multi- and hyperspectral imagery of Oristano Gulf (Italy) |
| title | Chapter Mapping submerged vegetation and water quality using multi- and hyperspectral imagery of Oristano Gulf (Italy) |
| title_full | Chapter Mapping submerged vegetation and water quality using multi- and hyperspectral imagery of Oristano Gulf (Italy) |
| title_fullStr | Chapter Mapping submerged vegetation and water quality using multi- and hyperspectral imagery of Oristano Gulf (Italy) |
| title_full_unstemmed | Chapter Mapping submerged vegetation and water quality using multi- and hyperspectral imagery of Oristano Gulf (Italy) |
| title_short | Chapter Mapping submerged vegetation and water quality using multi- and hyperspectral imagery of Oristano Gulf (Italy) |
| title_sort | chapter mapping submerged vegetation and water quality using multi and hyperspectral imagery of oristano gulf italy |
| topic | Seagrass Remote Sensing PRISMA Water Quality |
| topic_facet | Seagrass Remote Sensing PRISMA Water Quality |
| url | ONIX_20250801T173835_9791221505566_269 |
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