Shoreline extraction methods from Sentinel-2 and PlanetScope images

This work aims to compare and assess the performance of certain methodologies for shoreline mapping based on the use of medium (10 m) and high resolution (3 m) multi-spectral imagery, provided by Sentinel-2 (S2) and PlanetScope (PS), respectively. Being Sentinel-2 part of the Copernicus missions, it...

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Detalhes bibliográficos
Autores: Angelini, Riccardo, Angelats, Eduard, Luzi, Guido, Ribas Prats, Francesca|||0000-0003-4701-5982, Masiero, Andrea, Mugnai, Francesco
Tipo de documento: artigo
Data de publicação:2024
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2117/417493
Acesso em linha:https://hdl.handle.net/2117/417493
https://dx.doi.org/10.5194/isprs-archives-XLVIII-1-2024-1-2024
Access Level:Acceso aberto
Palavra-chave:Shoreline extraction
Satellite
Unsupervised classification
Multi-spectral images
PlanetScope
Sentinel-2.
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços
Descrição
Resumo:This work aims to compare and assess the performance of certain methodologies for shoreline mapping based on the use of medium (10 m) and high resolution (3 m) multi-spectral imagery, provided by Sentinel-2 (S2) and PlanetScope (PS), respectively. Being Sentinel-2 part of the Copernicus missions, its data are freely available. PS imagery are also freely available for scientific research, upon approval by the European Space Agency of a related project proposal. Several spectral indices, including Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Automated Water Extraction Index (AWEI), and Water Index (WI), were used for shoreline detection. In particular, two unsupervised classification techniques, the Gaussian Mixture Model (GMM) and K-means clustering were deployed as shoreline extraction methods. The outcomes of such approaches were validated using reference shorelines derived from aerial orthomosaics, generated from images acquired as close as possible to the satellite imagery dates, and the ”baseline and transect” approach for accuracy verification. Three tide-less Mediterranean beaches were used as study cases for comparison: the beach between Castelldefels and Gava in Spain, Feniglia and Marina di Grosseto in Italy. The results demonstrated sub-pixel accuracy in shoreline extraction, with Mean Absolute Distances ranging from 2 m to 5 m for S2 data and 1.5 m to 2 m for PS data. These findings highlight the potential of freely available satellite data for semi-automatic shoreline detection. Results obtained by using the combination of different indices and methodologies show that the best option may change depending on the considered context, hence future investigations should be dedicated to the development of a procedure for automatically determining the context-based (close to) optimal index-classifier combination.