Abstract
Boulders on the seabed in coastal marine environments provide key geo- and ecosystem functions and services. They serve as natural coastal protection by dissipating wave energy, and they form an important hard substrate for macroalgae, and hence for coastal marine reefs that serve as important habitats for fish. The aim of this study was to investigate the possibility of developing an automated method to classify boulders from topo-bathymetric LiDAR data in coastal marine environments. The Rødsand lagoon in Denmark was used as study area. A 100 m × 100 m test site was divided into a training and a test set. The classification was performed using the random forest machine learning algorithm. Different tuning parameters were tested. The study resulted in the development of a nearly automated method to classify boulders from topo-bathymetric LiDAR data. Different measure scores were used to evaluate the performance. For the best parameter combination, the recall of the boulders was 57%, precision was 27%, and F-score 37%, while the accuracy of the points was 99%. The most important tuning parameters for boulder classification were the subsampling level, the choice of the neighborhood radius, and the features. Automatic boulder detection will enable transparent, reproducible, and fast detection and mapping of boulders.
Highlights
The seabed surface in the Danish waters is diverse regarding abiotic as well as biotic features and functions (e.g., [1,2,3])
Stone reefs and boulders act as natural coastal protection, e.g., by dissipating wave energy [6], whereby they provide valuable geosystem services in relation to reducing coastal erosion and coastal hazard risk
We aim to develop an automated approach to directly map stand-alone boulders from point clouds derived from topo-bathymetric LiDAR data
Summary
The seabed surface in the Danish waters is diverse regarding abiotic as well as biotic features and functions (e.g., [1,2,3]). The seabed surface geodiversity, i.e., the variety in seabed surface geology, geomorphology, and substrate, is relatively high in Danish waters as a result of the composition of the seabed surface being a combination of a drowned glacial landscape with subsequent and ongoing marine and coastal processes. Seabed substrate displays a broad spectrum of soft and hard substrates, including areas designated as stone reefs [4,5]. The seabed surface in the Danish waters displays a high biotic diversity in terms of flora and fauna. Hide, and feed in areas with algae and seaweed growing on hard substrates
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