Search

Detailed maps of the seabed and knowledge of its habitats are critical for a wide range of tasks, such as sustainable development, and environmental protection. Boulders on the seabed form an important environment for ecosystems, but the detection of them is challenging. In this study, we aim to improve the understanding of boulder predictors and to determine connections between predictors and boulder environments on different spatial scales. The Relief-F filter feature selection algorithm was used on four 30 m x 30 m areas in Rodsand lagoon, containing one boulder each, to determine the most relevant predictors. The predictors could be divided into four groups detecting different boulder characteristics: colour contrast, height, boulder boundaries, and spherical geometry. Twelve different types of boulder environments were evaluated. Bare, spherical boulders on sandy seabeds can be predicted from all four predictor groups. It is not possible to detect non-spherical boulders on seabed covered by vegetation. The best predictors for boulder detection depend on the shape and size of the boulder and the surrounding sediment and vegetation. The predictors were evaluated on a larger 400 x 2500 m area. When up-scaling the boulder detection area, larger seabed structures may affect the results. Therefore, knowledge about these structures can be used to remove errors and uncertainties from machine learning input data.

The transition zone between land and water is difficult to map with conventional geophysical systems due to shallow water depth and often challenging environmental conditions. The emerging technology of airborne topobathymetric light detection and ranging (lidar) is capable of providing both topographic and bathymetric elevation information, using only a single green laser, resulting in a seamless coverage of the land-water transition zone. However, there is no transparent and reproducible method for processing green topobathymetric lidar data into a digital elevation model (DEM). The general processing steps involve data filtering, water surface detection and refraction correction. Specifically, the procedure of water surface detection and modelling, solely using green laser lidar data, has not previously been described in detail for tidal environments. The aim of this study was to fill this gap of knowledge by developing a step-by-step procedure for making a digital water surface model (DWSM) using the green laser lidar data. The detailed description of the processing procedure augments its reliability, makes it user-friendly and repeatable. A DEM was obtained from the processed topobathymetric lidar data collected in spring 2014 from the Knudedyb tidal inlet system in the Danish Wadden Sea. The vertical accuracy of the lidar data is determined to ±8 cm at a 95 % confidence level, and the horizontal accuracy is determined as the mean error to ±10 cm. The lidar technique is found capable of detecting features with a size of less than 1 m2. The derived high-resolution DEM was applied for detection and classification of geomorphometric and morphological features within the natural environment of the study area. Initially, the bathymetric position index (BPI) and the slope of the DEM were used to make a continuous classification of the geomorphometry. Subsequently, stage (or elevation in relation to tidal range) and a combination of statistical neighbourhood analys

Grøn laser kan gennemtrænge vandsøjlen og blive reflekteret fra havbunden. Ved hjælp af flybåren grøn laserscanning kan overgangszonen mellem land og vand samt lavvandede områder i kystzonen opmåles med fuld dækning og med høj detaljeringsgrad. Rumlig og detaljeret kortlægning af land–vand-overgangszonen giver mulighed for at generere ny viden om de naturlige processer, som foregår på tværs af kysten. Dette kan bidrage til optimeret forvaltning af kystzonen med bedre integration af naturlige processer, lovgivning og administration på tværs af kysten.

Coastal and tidal environments are valuable ecosystems, which, however, are under pressure in many areas around the world due to globalisation and/or climate change. Detailed mapping of these environments is required in order to manage the coastal zone in a sustainable way. However, historically these transition zones between land and water are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. The new generation of airborne topobathymetric light detection and ranging (LiDAR) potentially enables full-coverage and high-resolution mapping of these land-water transition zones. We have carried out topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the LiDAR point cloud with a mean point density in the order of 20 points/m2. The DEM was analysed morphometrically using a modification of the tool Benthic Terrain Modeler (BTM) developed by Wright et al. (2005). Initially, stage (the elevation in relation to tidal range) was used to divide the area of investigation into the different tidal zones, i.e. subtidal, intertidal and supratidal. Subsequently, morphometric units were identified and characterised by a combination of statistical neighbourhood analysis with varying window sizes (using the Bathymetric Positioning Index (BPI) from the BTM, moving average and standard deviation), slope parameters and area/perimeter ratios. Finally, these morphometric units were classified into six different types of landforms based on their stage and morphometric characteristics, i.e. either subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar or beach dune. We hereby demonstrate the potential of using airborne topobathymetric LiDAR for seamless

Shallow water environments in the land-sea transition zone are challenging to map in high spatial resolution at large spatial scales. Historically this has led to gaps (white ribbons) between terrestrial and marine surveys. Topobathymetric LiDAR (Light Detection And Ranging), also referred to as green LiDAR which is able to penetrate through water, holds the potential to close this gap. However, water column turbidity poses limitations to the penetration of the green laser beam, and water column refraction of the laser beam poses limitations to the scale of features which can be resolved at the seabed. The aim of this study is to investigate the performance of topobathymetric LiDAR in shallow water environments in relation to resolving small-scale morphological features at landscape scale. More specifically, the objectives are: 1) to determine the spatial resolution as well as the horizontal and vertical precision of green LiDAR based on object detection; and 2) to assess the potential of topobathymetric LiDAR as a tool to combine and integrate terrestrial and marine mapping and related investigations in the land-sea transition zone. Topobathymetric LiDAR surveys were carried out in spring 2014 on an app. 7 km reach of the Ribe Vesterå river and in a 5 km x 10 km section of the Knudedyb tidal inlet in the Danish Wadden Sea using the airborne hydrographic laser scanner RIEGL® VQR-820-G. Prior to the surveys three geometrically defined objects (steel frames with dimensions of 0.8 m x 0.8 m x 0.25 m) were placed within the survey area in the river section, and in a back-barrier tidal channel and on a back-barrier salt marsh in the tidal inlet system, respectively. The exact locations of the three objects were determined by a Trimble® R8 GNSS Receiver. The preliminary results show that the topobathymetric LiDAR system can detect the three objects. However, the sharp corners and edges of the objects are not perfectly resolved due to a combination of point den