Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29142
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Retrieval of nearshore bathymetry from Landsat 8 images: A tool for coastal monitoring in shallow waters
Author(s): Pacheco, André
Horta, João
Loureiro, Carlos
Ferreira, Óscar
Contact Email: carlos.loureiro@stir.ac.uk
Keywords: satellite-derived bathymetry
Landsat
LiDAR
linear transform algorithm
coastal monitoring
Ria Formosa
Issue Date: 15-Mar-2015
Date Deposited: 1-Mar-2019
Citation: Pacheco A, Horta J, Loureiro C & Ferreira Ó (2015) Retrieval of nearshore bathymetry from Landsat 8 images: A tool for coastal monitoring in shallow waters. Remote Sensing of Environment, 159, pp. 102-116. https://doi.org/10.1016/j.rse.2014.12.004
Abstract: Nearshore bathymetry is likely to be the coastal variable that most limits the investigation of coastal processes and the accuracy of numerical models in coastal areas, as acquiring medium spatial resolution data in the near- shore is highly demanding and costly. As such, the ability to derive bathymetry using remote sensing techniques is a topic of increasing interest in coastal monitoring and research. This contribution focuses on the application of the linear transform algorithm to obtain satellite-derived bathymetry (SDB) maps of the nearshore, at medium resolution (30 m), from freely available and easily accessible Landsat 8 imagery. The algorithm was tuned with available bathymetric Light Detection and Ranging (LiDAR) data for a 60-km-long nearshore stretch of a highly complex coastal system that includes barrier islands, exposed sandy beaches, and tidal inlets (Ria Formosa, Portugal). A comparison of the retrieved depths is presented, enabling the configuration of nearshore profiles and extracted isobaths to be explored and compared with traditional topographic/bathymetric techniques (e.g., high- and medium-resolution LiDAR data and survey-grade echo-sounding combined with high-precision positioning systems). The results demonstrate that the linear algorithm is efficient for retrieving bathymetry from multi-spectral satellite data for shallow water depths (0 to 12 m), showing a mean bias of − 0.2 m, a median difference of −0.1 m, and a root mean square error of 0.89 m. Accuracy is shown to be depth dependent, an inherent limitation of passive optical detection systems. Accuracy further decreases in areas where turbidity is likely to be higher, such as locations adjacent to tidal inlets. The SDB maps provide reliable estimations of the shoreline position and of nearshore isobaths for different cases along the complex coastline analysed. The use of freely available satellite imagery proved to be a quick and reliable method for acquiring updated medium- resolution, high-frequency (days and weeks), low-cost bathymetric information for large areas and depths of up to 12 m in clear waters without wave breaking, allowing almost constant monitoring of the submerged beach and the shoreface.
DOI Link: 10.1016/j.rse.2014.12.004
Rights: [Pacheco_etal_2015_PublishedVersion.pdf] The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
[Pacheco_etal_2015_AcceptedManuscript.pdf] Accepted refereed manuscript of: Pacheco A, Horta J, Loureiro C & Ferreira Ó (2015) Retrieval of nearshore bathymetry from Landsat 8 images: A tool for coastal monitoring in shallow waters. Remote Sensing of Environment, 159, pp. 102-116. DOI: https://doi.org/10.1016/j.rse.2014.12.004 © 2014, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Licence URL(s): http://creativecommons.org/licenses/by-nc-nd/4.0/

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