Depth from Satellite Images: Depth Retrieval Using a Stereo and Radiative Transfer-Based Hybrid Method

Collings, Simon; Botha, Elizabeth C.; Anstee, Janet; Campbell, N. A.

doi:10.3390/rs10081247

Cited by 13 publications

(8 citation statements)

References 41 publications

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“…In particular, multispectral satellite images are able to provide bathymetry information in shallow waters [15], aiding in the improvement of the monitoring of shoreline variability [16]. In addition, studies conducted using stereo images [17][18][19] have demonstrated a great potential for shallow water bathymetry mapping using data from remote sensing.…”

Section: Introductionmentioning

confidence: 99%

The Contribution of Multispectral Satellite Image to Shallow Water Bathymetry Mapping on the Coast of Misano Adriatico, Italy

Muzirafuti

Barreca

Crupi

et al. 2020

JMSE

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The results of absolute satellite-derived bathymetry (SDB) are presented in the current study. A comparative analysis was conducted on empirical methods in order to explore the potential of SDB in shallow water on the coast of Misano, Italy. Operations were carried out by relying on limited in situ water depth data to extract and calibrate bathymetry from a QuickBird satellite image acquired on a highly dynamic coastal environment. The image was processed using the log-band ratio and optimal band ratio analysis (OBRA) methods. Preprocessing steps included the conversion of the raw satellite image into top of atmosphere reflectance, spatial filtering, land and water classification, the determination of the optimal OBRA spectral band pairs, and the estimation of relative SDB. Furthermore, calibration and vertical referencing were performed via in situ bathymetry acquired in November 2007. The relative bathymetry obtained from different band ratios were vertically referenced to the local datum using in situ water depth in order to obtain absolute SDB. The coefficient of determination (R2) and vertical root mean square error (RMSE) were computed for each method. A strong correlation with in situ field bathymetry was observed for both methods, with R2 = 0.8682 and RMSE = 0.518 m for the log-band ratio method and R2 = 0.8927–0.9108 and RMSE = 0.35 m for the OBRA method. This indicated a high degree of confidence of the SDB results obtained for the study area, with a high performance of the OBRA method for SDB mapping in turbid water.

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Section: Introductionmentioning

confidence: 99%

The Contribution of Multispectral Satellite Image to Shallow Water Bathymetry Mapping on the Coast of Misano Adriatico, Italy

Muzirafuti

Barreca

Crupi

et al. 2020

JMSE

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“…However, spectral characteristics data from field measurements and satellite imagery showed that the blue (band 2) and green (band 3) bands have higher spectral values compared to coastal (band 1). Several other studies observed the dwindling capabilities and poor results of the coastal band in water penetration due to atmospheric and surface noises generated from high scattering and absorption in short wavelengths such as in Manessa et al (2016a,b), Collings et al (2018), andCross et al (2018). A study by Miecznik and Grabowska (2012) revealed that the coastal band only penetrates deepest in pure water.…”

Section: Discussionmentioning

confidence: 95%

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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“…Stumpf extended the approach of Lyzenga, proposing an empirical method for estimating SDB known as the ratio transform algorithm, which contends that the ratio for two bands at a constant depth will be the same, independently from the substrate of the seabed [24]. Additionally, significant potentials of estimating bathymetry were presented by researchers with stereo techniques [25,26] and more recently with machine learning approaches [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Satellite-Derived Bathymetry from High and Medium-Resolution Sensors Using Empirical Methods

et al. 2022

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This study evaluates the accuracy of bathymetric maps generated from multispectral satellite datasets acquired from different multispectral sensors, namely the Worldview 2, PlanetScope, and the Sentinel 2, in the bay of Elounda in Crete. Image pre-processing steps were implemented before the use of the three empirical methods for estimating bathymetry. A dedicated correction and median filter have been applied to minimize noise from the sun glint and the sea waves. Due to the spectral complexity of the selected study area, statistical correlation with different numbers of bands was applied. The analysis indicated that blue and green bands obtained the best results with higher accuracy. Then, three empirical models, namely the Single Band Linear Algorithm, the Multiband Linear Algorithm, and the Ratio Transform Algorithm, were applied to the three multispectral images. Bathymetric and error distribution maps were created and used for the error assessment of results. The accuracy of the bathymetric maps estimated from different empirical models is compared with on-site Single beam Echo Sounder measurements. The most accurate bathymetric maps were obtained using the WorldView 2 and the empirical model of the Ratio Transform algorithm, with the RMSE reaching 1.01 m.

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Depth from Satellite Images: Depth Retrieval Using a Stereo and Radiative Transfer-Based Hybrid Method

Cited by 13 publications

References 41 publications

The Contribution of Multispectral Satellite Image to Shallow Water Bathymetry Mapping on the Coast of Misano Adriatico, Italy

The Contribution of Multispectral Satellite Image to Shallow Water Bathymetry Mapping on the Coast of Misano Adriatico, Italy

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

Evaluation of Satellite-Derived Bathymetry from High and Medium-Resolution Sensors Using Empirical Methods

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