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Open-source Raster Processing Toolbox for the Investigation of Coastal Intertidal Bar Displacement (PROTECT)

Authors: Moelans, Robrecht; Montreuil, Anne-Lise; Chen, Margaret;

Open-source Raster Processing Toolbox for the Investigation of Coastal Intertidal Bar Displacement (PROTECT)

Abstract

PROTECT is an open-source raster processing toolbox developed in Python to investigate coastal intertidal bar displacement. It is developed on both airborne LiDAR data as well as UAV data acquired at two locations at the Belgian coast: Groenendijk and De Haan. In order to validate the toolbox, it is applied to two coastal sites outside Belgium: Mablethorpe (UK) and Dunkirk (France). PROTECT has not the intention of being a black-box that fits all possible circumstances of intertidal bars along macrotidal beaches. Often, the user needs to get familiar with the input parameters, and eventually he/she will need to add or tune the code in order to achieve the best possible results adapted to the respective study site. For this purpose, the values of the parameters in use are included with the results in the report. The PROTECT toolbox has three main modules: (i) a pre-processing module; (ii) a module to detect and characterise intertidal bars; and (iii) a module to detect drainage channels. The pre-processing module prepares the topographic raster dataset to achieve better results in (ii) and (iii) and includes cropping, filtering and smoothing the raster. The procedure to detect feature points for intertidal bars is composed of two steps. The first one is to find relevant feature points on 2D cross-sections followed by a processing of these points on the raster level. The ���end product��� is the automated clustering of feature points belonging to the same set of intertidal bars. This allows comparing the displacement of these points with time to investigate for example bar migration. The clustering step makes use of the DBSCAN-algorithm (unsupervised machine learning technique) implemented and made available in scikit-learn. For drainage channels, a similar procedure is available. The toolbox is developed under the Stereo III project SR/03/204, funded by Belgian Science Policy Office (Belspo). The authors welcome your feedback on the applicability of your experience in using this toolbox. Whenever this PROTECT toolbox or the uploaded UAV data are used in research, applications, services, and publications, the name of the toolbox should be mentioned together with a reference to the current report. This applies also to the case when the toolbox is modified and/or used in other software or related context. Authors: Robrecht Moelans, Anne-Lise Montreuil, Margaret Chen

PROTECT is developed under STEREO III project SR/03/204, funded by Belgian Science Policy Office.

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Keywords

python, raster analysis, machine learning, UAV, three-dimensional topography, airborne LiDAR, bar morphology, automatic detection

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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