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Abstract: Remote sensing has been used since the 1980s to study parameters in relation with coastal zones. It was not until the beginning of the twenty-first century that it started to acquire imagery with good temporal and spectral resolution. This has encouraged the development of reliable imagery acquisition systems that consider remote sensing as a water management tool. Nevertheless, the spatial resolution that it provides is not adapted to carry out coastal studies. This article introduces a new methodology for estimating the most fundamental physical property of intertidal sediment, the grain size, in coastal zones. The study combines hyperspectral information (CASI-2 flight), robust statistic, and simultaneous field work (chemical and radiometric sampling), performed over Santander Bay, Spain. Field data acquisition was used to build a spectral library in order to study different atmospheric correction algorithms for CASI-2 data and to develop algorithms to estimate grain size in an estuary. Two robust estimation techniques (MVE and MCD multivariate M-estimators of location and scale) were applied to CASI-2 imagery, and the results showed that robust adjustments give acceptable and meaningful algorithms. These adjustments have given the following R2 estimated results: 0.93 in the case of sandy loam contribution, 0.94 for the silty loam, and 0.67 for clay loam. The robust statistic is a powerful tool for large dataset.
Autoría: Castillo E., Pereda R., De Luis J.M., Medina R., Viguri J.,
Fuente: Environmental Monitoring and Assessment, 2011,181, 431-444
Editorial: Springer Netherlands
Año de publicación: 2011
Nº de páginas: 14
Tipo de publicación: Artículo de Revista
DOI: 10.1007/s10661-010-1839-z
ISSN: 1573-2959,0167-6369
Url de la publicación: https://link.springer.com/article/10.1007/s10661-010-1839-z
Leer publicación
ELENA CASTILLO LOPEZ
RAUL PEREDA GARCIA
JULIO MANUEL DE LUIS RUIZ
RAUL MEDINA SANTAMARIA
JAVIER RUFINO VIGURI FUENTE
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