WorldView-2 bathymetric capabilities

Miecznik, Grzegorz; Grabowska, Dorota

doi:10.1117/12.919342

Cited by 7 publications

(11 citation statements)

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“…The RGB DEM outperforms the Coastal Blue DEM not only in completeness but also in height precision, indicated by the higher amount of red pixels in the height precision maps. The superiority can also be seen from the histograms This clearly shows that the Coastal Blue band does provide bathymetric capabilities, not only in the coastal domain (Miecznik and Grabowska, 2012) but also for inland water bodies. But it is also evident that especially the green band performs better from a photogrammetric point of view.…”

Section: Preliminary Results and Discussionmentioning

confidence: 69%

“…Whereas blue (λ=450-500 nm) and green (λ=490-570 nm) are standard bands of an RGB image, modern multispectral satellite sensors like Landsat 8 (Operational Land Imager, OLI) or WorldView-2 provide a so-called Coastal Blue band (WorldView-2: λ=396-458 nm). On the one hand, signal attenuation in clear water is theoretically least for this wavelength which makes it most suitable for mapping shallow clear water bathymetry (Miecznik and Grabowska, 2012). On the other hand, it is absorbed by chlorophyll in healthy plants and, therefore, aids in conducting vegetative analysis but it is also influenced by atmospheric scattering (Anderson and Marchisio, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Investigating the Use of Coastal Blue Imagery for Bathymetric Mapping of Inland Water Bodies

Mandlburger

Kremer²,

Steinbacher³

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In this contribution, we report on an experimental airborne data acquisition with two medium format cameras (Coastal Blue, RGB) and a topo-bathymetric laser scanner for capturing the bathymetry of a dozen of groundwater supplied lakes located near Augsburg, Germany. The specific research question was to investigate whether the use of high-resolution Coastal Blue imagery (&lambda;=400&ndash;460nm) provides added value for mapping bathymetry and characterization of water bottom features. While data processing is still in progress, preliminary results indicate that the blue (&lambda;=420&ndash;500nm) and green (&lambda;=490&ndash;570nm) color channels of the RGB camera are better suited for estimating bathymetry, but the Coastal Blue channel adds an additional water penetrating band increasing the number of useful band combinations with a positive effect on the water bottom classification capabilities. Whereas Coastal Blue channels are rather used from satellite platforms (Landsat 8, WorldView-2) with spatial resolutions in the meter range, our experiment aims at using higher resolution Coastal Blue imagery with a ground sampling distance of around 5cm enabling not only spectrally based shallow water depth mapping but also the application of multi-media photogrammetry in high spatial resolution. To the best of our knowledge the use of high-resolution Coastal Blue captured from airborne platforms is novel in the context of mapping shallow water bathymetry.

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Section: Preliminary Results and Discussionmentioning

confidence: 69%

Section: Introductionmentioning

confidence: 99%

Investigating the Use of Coastal Blue Imagery for Bathymetric Mapping of Inland Water Bodies

Mandlburger

Kremer²,

Steinbacher³

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Sensor SNR also contributed to the observed patterns in the NE∆rsE. For example, the green band (510-580 nm) has the highest observed SNR in shallow waters (z < 5 m) [2], which can explain the lower NE∆rsE observed in this band (Figure 4).…”

Section: Discussionmentioning

confidence: 81%

“…Atmospheric effects, such as Rayleigh scattering, also affected noise observed in the images, particularly in the coastal band (400-450 nm), as this band is the most sensitive to Rayleigh scattering [2,32]. Sensor SNR also contributed to the observed patterns in the NE∆rsE.…”

Section: Discussionmentioning

confidence: 92%

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Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

2016

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Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF). Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

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Mapping and estimating harvest potential of seaweed culture using Worldview-2 Satellite images: a case study in Nusa Lembongan, Bali − Indonesia

Pratama

Albasri

2021

Aquat. Living Resour.

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Unreliable information on harvest potential is a persistent challenge for the Indonesian government and industry alike to manage an efficient supply chain of seaweed raw material. The use of remote sensing technology to assess seaweed harvest potential has been scarcely available in the literature. This current research aimed at estimating the harvest potential of seaweed Kappaphycus alvarezii through remote sensing using supervised classification with maximum likelihood (MLC) and contextual editing (CE) methods. This research evaluated the capabilities of different band combinations along with depth invariant index (DII) to enhance the remote sensing accuracy in estimating seaweed harvest potential. The seaweed classification using Worldview-2 imagery was compared with the in-situ references (ground-truthing). The potential data bias resulted from different imagery acquisition timestamps with the in-situ measurement was kept minimal as both data time stamps were ten days apart and within the same seaweed culture cycle. The average dry weight of all seaweed samples collected during the research was 924 ± 278.91 g/m2 with culture ages between 1 and 40 days. The classification results based on MLC+CE with a 5-band combination method without DII showed a better correlation and closer fit with the in-situ references compared to the other methods, with an overall accuracy of 79.05% and Tau coefficient value of 0.75. The estimated total harvest potential based on the combined seaweed classes was 531.26 ± 250.29 tons dry weight.

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WorldView-2 bathymetric capabilities

Cited by 7 publications

References 0 publications

Investigating the Use of Coastal Blue Imagery for Bathymetric Mapping of Inland Water Bodies

Investigating the Use of Coastal Blue Imagery for Bathymetric Mapping of Inland Water Bodies

Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

Mapping and estimating harvest potential of seaweed culture using Worldview-2 Satellite images: a case study in Nusa Lembongan, Bali − Indonesia

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