A New Adaptive Image Interpolation Method to Define the Shoreline at Sub-Pixel Level

[EN] This paper presents a new methodological process for detecting the instantaneous land-water border at sub-pixel level from mid-resolution satellite images (30 m/pixel) that are freely available worldwide. The new method is based on using an iterative procedure to compute Laplacian roots of a po...

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Detalles Bibliográficos
Autores: Sánchez-García, Elena, Almonacid-Caballer, Jaime, Balaguer-Beser, Ángel|||0000-0003-0039-2641, Pardo Pascual, Josep Eliseu|||0000-0003-0471-9795
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/168877
Acceso en línea:https://riunet.upv.es/handle/10251/168877
Access Level:acceso abierto
Palabra clave:Shoreline sub-pixel detection
Satellite images
Adaptive interpolation
Coastal management
INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA
MATEMATICA APLICADA
Descripción
Sumario:[EN] This paper presents a new methodological process for detecting the instantaneous land-water border at sub-pixel level from mid-resolution satellite images (30 m/pixel) that are freely available worldwide. The new method is based on using an iterative procedure to compute Laplacian roots of a polynomial surface that represents the radiometric response of a set of pixels. The method uses a first approximation of the shoreline at pixel level (initial pixels) and selects a set of neighbouring pixels to be part of the analysis window. This adaptive window collects those stencils in which the maximum radiometric variations are found by using the information given by divided differences. Therefore, the land-water surface is computed by a piecewise interpolating polynomial that models the strong radiometric changes between both interfaces. The assessment is tested on two coastal areas to analyse how their inherent differences may affect the method. A total of 17 Landsat 7 and 8 images (L7 and L8) were used to extract the shorelines and compare them against other highly accurate lines that act as references. Accurate quantitative coastal data from the satellite images is obtained with a mean horizontal error of 4.38 +/- 5.66 m and 1.79 +/- 2.78 m, respectively, for L7 and L8. Prior methodologies to reach the sub-pixel shoreline are analysed and the results verify the solvency of the one proposed.