6533b86dfe1ef96bd12caa65

RESEARCH PRODUCT

Comparison of Bathymetric estimation using different satellite images in coastal sea waters

Pierre GoutonA. GoreacSandrine MathieuM. SpigaiAudrey Minghelli-roman

subject

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciencesPixelAerial survey[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMultispectral image0211 other engineering and technologies02 engineering and technologySpectral bands01 natural sciencesMultispectral pattern recognition[SPI]Engineering Sciences [physics][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer Science::Computer Vision and Pattern RecognitionGeneral Earth and Planetary SciencesBathymetry14. Life underwaterQuantization (image processing)Image resolution[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingGeologyComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing

description

Bathymetric estimation can be obtained from multispectral satellite images for shallow waters. The method is based on the rotation of a pair of spectral bands. One of the resulting images is depth-dependent. Therefore several pixels corresponding to different depths are required to numerically evaluate the linear relation between the pixel values and the real depth for a training area. The aim of this study is to compare, for one bathymetric estimation method and one mesotrophic site, the results of depth estimation with a large panel of satellite and aerial images: CASI, QUICKBIRD, CHRIS PROBA, ETM, HYPERION and MeRIS. For each image the pair of spectral bands chosen to compute the bathymetry has been optimized. Error on depth estimation has been computed on two regions of the image: the training area and a validation area. This comparison is discussed to identify the influence of image parameters (spectral bands, S/N ratio, spatial resolution, and quantization) on the bathymetric results and to propose the most adapted image parameters for bathymetric estimation. For validation purposes, we compared the results obtained with a CASI image matching the optimized parameters in an oligotrophic site in the Red Sea.

https://hal-amu.archives-ouvertes.fr/hal-01479822