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A Review of Advancements and Applications of Satellite-Derived Bathymetry
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SATELLITE-DERIVED BATHYMETRY ONLINE
International Hydrographic Review, 2022Satellite-Derived Bathymetry (SDB) methods have found their way into the hydrographers’ toolbox and are part of integrated survey concepts, nautical charts and support global and European programs such as Seabed2030 or EMODnet Bathymetry. The concept of the ‘physics-based’ SDB describes the calculation of bathymetry by modelling the sunlight path from ...
Hartmann, Knut +5 more
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Satellite derived photogrammetric bathymetry
ISPRS Journal of Photogrammetry and Remote Sensing, 2018Abstract Satellite Derived Bathymetry (SDB) is being adopted as a cheaper and more spatially extensive method for bathymetric mapping than traditional acoustic surveys, with research being conducted by the Canadian Hydrographic Service under a Government Related Initiatives Program (GRIP) of the Canadian Space Agency.
Matúš Hodúl +3 more
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Hydrographische Nachrichten, 2022
In dieser Arbeit konnte gezeigt werden, dass auf Grundlage der satellitengestützten Bathymetrie (SDB) eine anlassbezogene Seevermessung, bei der Gebiete je nach Dynamik unterschiedlich intensiv vermessen werden, prinzipiell möglich ist. Die Grundlage für die SDB bilden Sentinel-2-Daten und daraus abgeleitete Bandkombinationen.
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In dieser Arbeit konnte gezeigt werden, dass auf Grundlage der satellitengestützten Bathymetrie (SDB) eine anlassbezogene Seevermessung, bei der Gebiete je nach Dynamik unterschiedlich intensiv vermessen werden, prinzipiell möglich ist. Die Grundlage für die SDB bilden Sentinel-2-Daten und daraus abgeleitete Bandkombinationen.
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Satellite derived Bathymetry and Digital Elevation Models (DEM)
International Petroleum Technology Conference, 2014Abstract In 2010, Qatar Shell Upstream International B.V. (QSUI) re-entered Exploration in Qatar focusing on the relatively deep conventional Pre-Khuff gas plays with a view to discover additional hydrocarbons in the State of Qatar.
J. Siermann +3 more
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Satellite-Derived Bathymetry Using Deep Convolutional Neural Network
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020Our goal is to develop technique for assessing bathymetry maps, which show the topography of the floors of water-bodies, using satellite or aerial imagery. The advent of deep neural networks has enabled the use of new techniques in analysing and creating depth maps from high resolution satellite images.
Bibin Wilson +3 more
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Satellite-derived bathymetry in practice
Hydrographische Nachrichten, 2020Multibeam bathymetry surveying is a well-established method but limited to water depths accessible by vessels or small boats. Airborne LiDAR bathymetry (ALB) systems can cover this gap by surveying both the coastal topography and the shallower water regions.
Niederjasper, Marina, Lehmann, Frank
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Satellite-derived bathymetry integrating spatial and spectral information of multispectral images
Applied Optics, 2023As a significant and cost-effective method of obtaining shallow seabed topography, satellite derived bathymetry (SDB) can acquire a wide range of shallow sea depth by integrating a small quantity ofin-situwater depth data. This method is a beneficial addition to traditional bathymetric topography.
Ningning Li +5 more
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Mapping Multidecadal Morphological Variability Via Satellite Derived Bathymetries
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018This paper outlines a novel approach to calibrating satellite derived relative depth surfaces generated using the ratio transform algorithm first proposed by Stumpf et al. The method utilizes raster image equal interval classification to generate depth classes and to identify both the upper and lower limits of sensitivity to the depth signal within the
Annette Burke +2 more
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Satellite-Derived Bathymetry using Adaptive Geographically Weighted Regression Model
Marine Geodesy, 2016ABSTRACTThe common practice adopted in previous attempts on Satellite-Derived Bathymetry (SDB) has been to calibrate a single set of coefficients using global regression model. In this study we propose an Adaptive-Geographically Weighted Regression (A-GWR) model that takes into account local factors in determining the regression coefficients.
Poliyapram Vinayaraj +2 more
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