Coastal environments are facing constant changes over time due not only to their dynamic nature but also to geological, geomorphological, hydrodynamic, biological, climatic and anthropogenic factors. Nowadays, erosion phenomena exceed those of accretion. For these reasons, the monitoring of these areas is crucial for the safeguarding of the cultural heritage and the populations living there. Knowledge of shoreline dynamics helps to understand and study a wide range of coastal area studies and, in general, its management and planning. The focus of this research is based on the integration between optical and SAR data for shoreline extraction. High (Sentinel-1 SAR and Sentinel-2 optical) and very high (WorldView-2 optical) resolution satellite images were used. Two coastal sites, Ortona (Chieti, Italy) and Castelldefels (Barcelona, Spain) were detected. After pre-processing, necessary for geometric and radiometric corrections, enhancement techniques were applied in order to increase the readability of the data. Several indices, algorithms and filters were tested. The experimentation critically analysed algorithms already commonly used in literature and led to the study of new algorithms within the world of artificial intelligence. The innovation has conducted to their experimentation on the case studies taken into account in this thesis. These algorithms are the ACM Systems (Active Connection Matrix), which were compared to the common ones considering, as ground truth, once the shoreline manually extracted by visual inspection and once by GPS measurements. The results showed that the ACM Systems, and in particular the Contractive Maps and the J-Net Dynamic, provide a better definition and extraction of the shorelines, which were closer to the reference ones, compared to the most common methodologies. They reached, in most of the tests, a sub-pixel/pixel accuracy. Moreover, one of the aim of this work was to develop a semi-automatic methodology for instantaneous shoreline extraction, mainly using Sentinel images as part of Copernicus programme, which provide full, open and free-of-charge data, in addition to ease of access and use. Through the aforementioned study, it was also demonstrated that the ACM Systems make the best of SAR data, because they were found to be less sensitive to the speckle effect. The new methodology can quickly extract the shorelines of images taken in different time periods and, therefore, evaluate any occurred change. In this way, a concrete possibility of an appropriate intervention plan can be developed by institutions to preserve the environment.

Telerilevamento: integrazione tra immagini ottiche e SAR per l'estrazione della linea di riva / Zollini, Sara. - (2021 May 03).

Telerilevamento: integrazione tra immagini ottiche e SAR per l'estrazione della linea di riva

ZOLLINI, SARA
2021

Abstract

Coastal environments are facing constant changes over time due not only to their dynamic nature but also to geological, geomorphological, hydrodynamic, biological, climatic and anthropogenic factors. Nowadays, erosion phenomena exceed those of accretion. For these reasons, the monitoring of these areas is crucial for the safeguarding of the cultural heritage and the populations living there. Knowledge of shoreline dynamics helps to understand and study a wide range of coastal area studies and, in general, its management and planning. The focus of this research is based on the integration between optical and SAR data for shoreline extraction. High (Sentinel-1 SAR and Sentinel-2 optical) and very high (WorldView-2 optical) resolution satellite images were used. Two coastal sites, Ortona (Chieti, Italy) and Castelldefels (Barcelona, Spain) were detected. After pre-processing, necessary for geometric and radiometric corrections, enhancement techniques were applied in order to increase the readability of the data. Several indices, algorithms and filters were tested. The experimentation critically analysed algorithms already commonly used in literature and led to the study of new algorithms within the world of artificial intelligence. The innovation has conducted to their experimentation on the case studies taken into account in this thesis. These algorithms are the ACM Systems (Active Connection Matrix), which were compared to the common ones considering, as ground truth, once the shoreline manually extracted by visual inspection and once by GPS measurements. The results showed that the ACM Systems, and in particular the Contractive Maps and the J-Net Dynamic, provide a better definition and extraction of the shorelines, which were closer to the reference ones, compared to the most common methodologies. They reached, in most of the tests, a sub-pixel/pixel accuracy. Moreover, one of the aim of this work was to develop a semi-automatic methodology for instantaneous shoreline extraction, mainly using Sentinel images as part of Copernicus programme, which provide full, open and free-of-charge data, in addition to ease of access and use. Through the aforementioned study, it was also demonstrated that the ACM Systems make the best of SAR data, because they were found to be less sensitive to the speckle effect. The new methodology can quickly extract the shorelines of images taken in different time periods and, therefore, evaluate any occurred change. In this way, a concrete possibility of an appropriate intervention plan can be developed by institutions to preserve the environment.
Telerilevamento: integrazione tra immagini ottiche e SAR per l'estrazione della linea di riva / Zollini, Sara. - (2021 May 03).
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Descrizione: Remote sensing: integration between optical and SAR images for shoreline extraction
Tipologia: Tesi di dottorato
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/168318
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