Three-Dimensional Geographically Weighted Inverse Regression (3GWR) Model for Satellite Derived Bathymetry Using Sentinel-2 Observations

Chybicki, Andrzej

doi:10.1080/01490419.2017.1373173

Cited by 19 publications

(17 citation statements)

References 55 publications

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“…However, in recent years, new studies have focused on enhancing empirical model performance, for example, through spatial rather than standard, non-spatial modelling (e.g. Su et al, 2015; Monteys et al, 2015; Chybicki, 2018). Following this trend, this study assessed an empirical modelling framework through the incorporation of spatial autocorrelation effects.…”

Section: Discussionmentioning

confidence: 99%

A comparison of Landsat 8, RapidEye and Pleiades products for improving empirical predictions of satellite-derived bathymetry

Cahalane

Magee

Monteys

et al. 2019

Remote Sensing of Environment

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Satellite derived bathymetry (SDB) enables rapid mapping of large coastal areas through measurement of optical penetration of the water column. The resolution of bathymetric mapping and achievable horizontal and vertical accuracies vary but generally, all SDB outputs are constrained by sensor type, water quality and other environmental conditions. Efforts to improve accuracy include physics-based methods (similar to radiative transfer models e.g. for atmospheric/vegetation studies) or detailed in-situ sampling of the seabed and water column, but the spatial component of SDB measurements is often under-utilised in SDB workflows despite promising results suggesting potential to improve accuracy significantly. In this study, a selection of satellite datasets (Landsat 8, RapidEye and Pleiades) at different spatial and spectral resolutions were tested using a log ratio transform to derive bathymetry in an Atlantic coastal embayment. A series of non-spatial and spatial linear analyses were then conducted and their influence on SDB prediction accuracy was assessed in addition to the significance of each model's parameters. Landsat 8 (30 m pixel size) performed relatively weak with the non-spatial model, but showed the best results with the spatial model. However, the highest spatial resolution imagery used – Pleiades (2 m pixel size) showed good results across both non-spatial and spatial models which suggests a suitability for SDB prediction at a higher spatial resolution than the others. In all cases, the spatial models were able to constrain the prediction differences at increased water depths.

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Section: Discussionmentioning

confidence: 99%

A comparison of Landsat 8, RapidEye and Pleiades products for improving empirical predictions of satellite-derived bathymetry

Cahalane

Magee

Monteys

et al. 2019

Remote Sensing of Environment

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“…Hence, the area between the coastline and the 30/40 cm isobath should be measured by the geodetic method [20] or photogrammetric method with unmanned [65] or manned aircraft [66,67]. Moreover, alternatively, the coastal water depths can be determined by analyzing high-resolution satellite images [68][69][70][71].…”

Section: Discussionmentioning

confidence: 99%

Determining the Variability of the Territorial Sea Baseline on the Example of Waterbody Adjacent to the Municipal Beach in Gdynia

Specht

Wąż

et al. 2019

Applied Sciences

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The purpose of this publication is to analyze the spatial and temporal variability of the territorial sea baseline in sand bottom waterbodies, which were determined twice, in 2016 and 2018, by the Real Time Kinematic (RTK) method. This involves direct measurement of sea bottom coordinates on planned hydrographic sounding profiles using a Global Navigation Satellite System (GNSS) receiver mounted on a pole. The data were the basis for creating Digital Terrain Models (DTM), which were then used to determine the baseline for both measurement campaigns. Subsequently, terrain surface models were compared to determine bathymetry changes in the area under analysis, and an assessment was made of the baseline spatial position change over the previous two years. The measurements have shown considerable spatial and temporal variability of the baseline course along a short section of sandy beach. The territorial sea baseline was very unstable; in some places, it moved by even 20–25 m, landwards and seawards. Therefore, one can suppose that these changes are periodic, and one can conclude that the reliability of the baseline measurements can decrease quite quickly.

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“…Considering our constraints, we aimed for deriving Satellite-Derived Bathymetry (SDB) using preferentially the free wide-swath Sentinel-2 multispectral images. With a five-day revisit time, a 10 m medium-scale native resolution and its suitable spectral resolution, the European Space Agency sensor have high potential for marine and coastal applications [30][31][32][33][34], and its use for bathymetry retrievals is increasing [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Shallow Water Bathymetry Retrieval Using a Band-Optimization Iterative Approach: Application to New Caledonia Coral Reef Lagoons Using Sentinel-2 Data

et al. 2021

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To achieve high accuracy bathymetry retrieval using remote sensing images with robust performance in a 0 to 25 m-deep lagoon with sharp bottom depth variations, a new Iterative Multiple Band Ratio (IMBR) algorithm is tested against known Multiple Band Ratio (MBR) and Single Band Ratio (SBR) algorithms. The test was conducted using the five multispectral bands, at 10 to 60 m resolution, of a Sentinel-2 image of the 25 km2 Poe lagoon, a UNESCO World Heritage Area. The IMBR approach requires training datasets for the definitions of depth threshold at which optimal band ratios vary. IMBR achieved accuracy, quantified with an original block cross-validation procedure across the entire depth range reached a mean absolute error of 46.0 cm. It compares very favorably against MBR (78.3 cm) and the various SBR results (188–254 cm). The method is suitable for generalization to other sites pending a minimal ground-truth dataset crossing all the depth range being available. We stress that different users may need different precisions and can use MBR or SBR algorithms for their applications. For the hydrodynamic modelling applications that are developing in New Caledonia, the IMBR solutions applied to Sentinel imagery are optimal.

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Three-Dimensional Geographically Weighted Inverse Regression (3GWR) Model for Satellite Derived Bathymetry Using Sentinel-2 Observations

Cited by 19 publications

References 55 publications

A comparison of Landsat 8, RapidEye and Pleiades products for improving empirical predictions of satellite-derived bathymetry

A comparison of Landsat 8, RapidEye and Pleiades products for improving empirical predictions of satellite-derived bathymetry

Determining the Variability of the Territorial Sea Baseline on the Example of Waterbody Adjacent to the Municipal Beach in Gdynia

Shallow Water Bathymetry Retrieval Using a Band-Optimization Iterative Approach: Application to New Caledonia Coral Reef Lagoons Using Sentinel-2 Data

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