Morphological changes, beach inundation and overwash caused by an extreme storm on a low-lying embayed beach bounded by a dune system (NW Mediterranean)

The geomorphological evolution of a low-lying, micro-tidal sandy beach in the western Mediterranean, Pals beach, was characterized using airborne Light Detection and Ranging (LiDAR) data. Data were collected in prior to and six months after the impact of an extreme storm with a return period of approx. 50 years, with the aim of characterizing the beach's response to the storm. The use of repeated high-resolution topographic data to quantify beach geomorphic changes has allowed assessment of the accuracy of different proxies for estimating beach volume changes. Results revealed that changes in the shoreline position cannot accurately reproduce beach volume changes on low-lying beaches where overwash processes are significant. Observations also suggested that volume estimations from beach profiles do not accurately represent subaerial volume changes at large profile distances on beaches with significant alongshore geomorphological variability. Accordingly, the segmentation of the beach into regularly spaced bins is proposed to assess alongshore variations in the beach volume with the accuracy of the topographic data. The morphological evolution of Pals beach during the study period showed a net shoreline retreat (- 4 m) and a significant sediment gain on the subaerial beach (+ 7.5 m3/m). The net gain of sediment is mostly due to the impact of the extreme storm, driving significant overwash processes that transport sediment landwards, increasing volume on the backshore and dunes. The increase of volume on the foreshore and the presence of cuspate morphologies along the shoreline also evidence post-storm beach recovery. Observed morphological changes exhibit a high variability along the beach related to variations in beach morphology. Changes in the morphology and migration of megacusps result in a high variability in the shoreline position and foreshore volume changes. On the other hand, larger morphological changes on the backshore and larger inundation distances occur when the beach and the dunes are lower, favouring the dominance of overwash. The observed storm-induced morphological changes differ from predicted beach storm impacts because of spatial and temporal variations in the beach morphology, suggesting that detailed morphological parameters and indicators used for predicting beach vulnerability to storms should be regularly updated in order to represent the pre-storm beach conditions. Finally, observed morphological changes in Pals Bay evidenced a different behaviour between natural and urban areas, with better post-storm beach recovery on natural areas where the beach is not artificially narrowed.Peer ReviewedPostprint (author's final draft

Airborne LiDAR for DEM generation: some critical issues

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented

Comparative analysis of the differences between using LiDAR and contour-based DEMs for hydrological modeling of runoff generating debris flows in the Dolomites

Present work aims to explore the differences in hydrological modeling when using digital elevation models (DEMs) generated by points from LiDAR surveys and those digitized on the contour lines of the regional technical map (RTM) and their relevance for the simulation of debris flow triggering. Hydrological models for mountainous areas are usually based on digital elevation models (DEMs). DEMs are used to determine the flow path from each pixel, by which the basin is discretized, to the outlet. Hydrological simulations of runoff that triggered debris flows occurred in two rocky headwater basins of Dolomites, Fiames Dimai (area approximately 0.03 km2) and Cancia (area approximately 0.7 km2) are carried out using a DEM-based model designed for simulating runoff that descends from headwater areas. For each basin, the runoff is simulated using DEMs that are generated using points from LiDAR, and those digitized on the contour lines of the regional technical map, respectively. The results show that the peak discharge values corresponding to the simulations carried out using the LiDAR-based DEMs are higher than those corresponding to the simulations carried out using the RTM-based DEMs. Larger differences are observed for the Dimai basin, where the area corresponding to the RTM-based DEM is markedly smaller than the area corresponding to LiDAR-based DEM, whereas for the Cancia basin, the two areas are similar. Both the differences in the peak discharge and the basin area are due to the poor accuracy of the contour-based DEM (i.e., elevation accuracy), that is, a poor representation of the morphological features that leads to errors on the watershed divide and simplifications of the flow paths from each cell to the outlet. This result is highly relevant for estimating the triggering conditions of runoff generated debris flows. An incorrect simulated value of peak discharge can lead to errors both in planning countermeasures against debris flows and in predicting their occurrence

Predicting growing stock volume of Eucalyptus plantations using 3-D point clouds derived from UAV imagery and ALS data

Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired fromUnmannedAerialVehicles(UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model E ciency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant di erence was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantationsinfo:eu-repo/semantics/publishedVersio

Evaluation of high quality topographic data for geomorphological and flood impact studies in upland area: North York Moors, UK

A flash flood on 19th June 2005 caused more than one hundred landslides in the North-western North York Moors uplands, UK. This project aims to 1) assess digital elevation models (DEMs) in terms of statistical terrain analysis and 2) explore the sensitivity of a 2D FLOWMAP model response to DEMs input data. A variety of topographic data were acquired, generated and processed. These included high-resolution aerial photographs, Ordnance Survey (OS) DEMs, topographic maps, InSAR DEMs, LiDAR data and ground survey data. These DEMs of different horizontal and vertical resolutions were analysed through key topographic parameters calculated using three different software packages. Key topographic attributes such as slope, aspect, profile curvature and the Topographic Wetness Index (TWI) were studied. Results demonstrate that DEMs from different sources or at different resolutions provide different representations of topographic parameters especially in areas where large topographic changes take place. Algorithms used in different packages also had an effect. Degradation in the representation of topographic information is larger between 10 m and 50 m DEMs than between 5 m and 10 m DEMs. Finer resolution and smaller filter size have the same type of impact on slope and aspect. In addition, DEMs at finer horizontal resolutions have smaller minimum profile curvatures and larger maximum values and standard deviations in profile curvature. The TWI is more sensitive to the horizontal resolution than DEM data source and finer DEMs calculate smaller minimum and mean TWI and larger maximum TWI and standard deviations. Modelled hydrological responses are sensitive to both DEM resolution and its data source. Model showed different results when using 5 m LİDAR DEM and 5 m InSAR DEM of the same area, which meant DEM source had impacts on modelling These differences reduced with a larger magnitude flooding. Producing a better representative surface model from the LİDAR data has much larger impact on model response than adjusting a constant roughness coefficient

ESA's Ice Sheets CCI: validation and inter-comparison of surface elevation changes derived from laser and radar altimetry over Jakobshavn Isbræ, Greenland – Round Robin results

In order to increase the understanding of the changing climate, the European Space Agency has launched the Climate Change Initiative (ESA CCI), a program which joins scientists and space agencies into 13 projects either affecting or affected by the concurrent changes. This work is part of the Ice Sheets CCI and four parameters are to be determined for the Greenland Ice Sheet (GrIS), each resulting in a dataset made available to the public: Surface Elevation Changes (SEC), surface velocities, grounding line locations, and calving front locations. All CCI projects have completed a so-called Round Robin exercise in which the scientific community was asked to provide their best estimate of the sought parameters as well as a feedback sheet describing their work. By inter-comparing and validating the results, obtained from research institutions world-wide, it is possible to develop the most optimal method for determining each parameter. This work describes the SEC Round Robin and the subsequent conclusions leading to the creation of a method for determining GrIS SEC values. The participants used either Envisat radar or ICESat laser altimetry over Jakobshavn Isbræ drainage basin, and the submissions led to inter-comparisons of radar vs. altimetry as well as cross-over vs. repeat-track analyses. Due to the high accuracy of the former and the high spatial resolution of the latter, a method, which combines the two techniques will provide the most accurate SEC estimates. The data supporting the final GrIS analysis stem from the radar altimeters on-board Envisat, ERS-1 and ERS-2. The accuracy of laser data exceeds that of radar altimetry; the Round Robin analysis has, however, proven the latter equally capable of dealing with surface topography thereby making such data applicable in SEC analyses extending all the way from the interior ice sheet to margin regions. This shows good potential for a~future inclusion of ESA CryoSat-2 and Sentinel-3 radar data in the analysis, and thus for obtaining reliable SEC estimates throughout the entire GrIS

Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues

This paper reviews LiDAR ground filtering algorithms used in the process of creating Digital Elevation Models. We discuss critical issues for the development and application of LiDAR ground filtering algorithms, including filtering procedures for different feature types, and criteria for study site selection, accuracy assessment, and algorithm classification. This review highlights three feature types for which current ground filtering algorithms are suboptimal, and which can be improved upon in future studies: surfaces with rough terrain or discontinuous slope, dense forest areas that laser beams cannot penetrate, and regions with low vegetation that is often ignored by ground filters