Shoreline Change from Optical and Sar Satellite Imagery at Macro-Tidal Estuarine, Cliffed Open-Coast and Gravel Pocket-Beach Environments

Coasts are continually changing and remote sensing from satellite has the potential to both map andmonitor coastal change at multiple scales. This study aims to assess the application of shorelines extracted from Multi-Spectral Imagery (MSI) and Synthetic Aperture Radar (SAR) from publicly available...

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Detalhes bibliográficos
Autores: Paz Delgado, María Victoria, Payo, Andrés, Gómez Pazo, Alejandro, Beck, Anne-Laure, Savastano, Salvatore
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Recursos:Universidad de León
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/21363
Acesso em linha:https://portalcientifico.unileon.es/documentos/628976c4ffc02649ba308547
https://hdl.handle.net/10612/21363
Access Level:acceso abierto
Palavra-chave:Geografía
Erosion
Monitoring
Earth observation
England
PCA
Coastal change
2505.07 Geografía Física
Descrição
Resumo:Coasts are continually changing and remote sensing from satellite has the potential to both map andmonitor coastal change at multiple scales. This study aims to assess the application of shorelines extracted from Multi-Spectral Imagery (MSI) and Synthetic Aperture Radar (SAR) from publicly available satellite imagery to map and capture sub-annual to inter-annual shoreline variability. This is assessed at three macro-tidal study sites along the coastline of England, United Kingdom (UK): estuarine, soft cliff environment, and gravel pocket-beach. We have assessed the accuracy of MSI-derived lines against ground truth datum tideline data and found that the satellite derived lines have the tendency to be lower (seaward) on the Digital Elevation Model than the datum-tideline. We have also compared the metric of change derived from SAR lines differentiating between ascending and descending orbits. The spatial and temporal characteristics extracted from SARlines via Principal Component Analysis suggested that beach rotation is captured within the SARdataset for descending orbits but not for the ascending ones in our study area. The present study contributes to our understanding of a poorly known aspect of using coastlines derived from publicly available MSI and SAR satellite missions. It outlines a quantitative approach to assess their mapping accuracy with a new non-foreshore method. This allows the assessment of variability on the metrics of change using the Open Digital Shoreline Analysis System (ODSAS) method and to extract complex spatial and temporal information using Principal Component Analysis (PCA) that is transferable to coastline evolution assessments worldwide.