The Impact of Acoustic Imaging Geometry on the Fidelity of Seabed Bathymetric Models

Attributes derived from digital bathymetric models (DBM) are a powerful means of analyzing seabed characteristics. Those models however are inherently constrained by the method of seabed sampling. Most bathymetric models are derived by collating a number of discrete corridors of multibeam sonar data. Within each corridor the data are collected over a wide range of distances, azimuths and elevation angles and thus the quality varies significantly. That variability therefore becomes imprinted into the DBM. Subsequent users of the DBM, unfamiliar with the original acquisition geometry, may potentially misinterpret such variability as attributes of the seabed. This paper examines the impact on accuracy and resolution of the resultant derived model as a function of the imaging geometry. This can be broken down into the range, angle, azimuth, density and overlap attributes. These attributes in turn are impacted by the sonar configuration including beam widths, beam spacing, bottom detection algorithms, stabilization strategies, platform speed and stability. Superimposed over the imaging geometry are residual effects due to imperfect integration of ancillary sensors. As the platform (normally a surface vessel), is moving with characteristic motions resulting from the ocean wave spectrum, periodic residuals in the seafloor can become imprinted that may again be misinterpreted as geomorphological information

semi automatic derivation of channel network from a high resolution dtm the example of an italian alpine region

AbstractHigh-resolution digital terrain models (HR-DTMs) of regional coverage open interesting scenarios for the analysis of landscape, including derivation and analysis of channel network. In this study, we present the derivation of the channel network from a HR-DTM for the Autonomous Province of Trento. A preliminary automatic extraction of the raw channel network was conducted using a curvature-based algorithm applied to a 4 m resolution DTM derived from an airborne LiDAR survey carried out in 2006. The raw channel network automatically extracted from the HR-DTM underwent a supervised control to check the spatial pattern of the hydrographic network. The supervised control was carried out by means of different informative layers (i.e. geomorphometric indexes, orthophoto imagery and technical cartography) resulting in an accurate and fine-scale channel network

Geomorphometric Characteristics of Landslides in the Tinalah Watershed, Menoreh Mountains, Yogyakarta, Indonesia

AbstractA landslide is one of natural hazards that affect humans and their livelihood especially in the mountainous area. The increasing landslide risk due to global climate change and demographic pressure demands integration between disaster risk reduction and sustainability management, for instance, the recently increasing people's awareness of the landslide and its impacts. Landslides occur in particular location regarding both physical and non-physical features of an area, comprising geomorphology, geology, geomorphometry, human activities, earthquake probability, rainfall occurrence, and etc. This research aims to understand the characteristics of the specific land surface that bears susceptibility to landslides using a geomorphometric approach and to analyze the relationship between geomorphometric characteristics and landslide events. The Tinalah watershed is located in Menoreh Mountains, one of mountainous areas in Java where highly frequent landslides occur. Geomorphometric characteristics, derived from DEMs with 2x2-m2 grid resolution, consist of elevation, slope gradient, aspect, profile curvature, plan curvature, and general curvature. The inventory of landslide events, consisting of the location, time, area, perimeter, typology, and activity, is derived from the field maps, local government's report analysis, and interviews with local people. In this research, landslide distribution is mapped using the multi-temporal records of landslide events during 2006-2010. A raster-based spatial analysis reveals the relationship between landslide events and geomorphometric characteristics. Each variable shows the quantitative information of landslide distribution in the Tinalah watershed. As a result, geomorphometric characteristics have the most significant relationship with the landslide distribution in this study area

Scaling gridded river networks for macroscale hydrology: Development, analysis, and control of error

A simple and robust river network scaling algorithm (NSA) is presented to rescale fine‐resolution networks to any coarser resolution. The algorithm was tested over the Danube River basin and the European continent. Coarse‐resolution networks, at 2.5, 5, 10, and 30 min resolutions, were derived from higher‐resolution gridded networks using NSA and geomorphometric attributes, such as river order, shape index, and width function. These parameters were calculated and compared at each resolution. Simple scaling relationships were found to predict decreasing river lengths with coarser‐resolution data. This relationship can be used to correct river length as a function of grid resolution. The length‐corrected width functions of the major river basins in Europe were compared at different resolutions to assess river network performance. The discretization error in representing basin area and river lengths at coarser resolutions were analyzed, and simple relationships were found to calculate the minimum number of grid cells needed to maintain the catchment area and length within a desired level of accuracy. This relationship among geomorphological characteristics, such as shape index and width function (derived from gridded networks at different resolutions), suggests that a minimum of 200–300 grid cells is necessary to maintain the geomorphological characteristics of the river networks with sufficient accuracy

The ASTER DEM generation for geomorphometric analysis of the Central Alborz mountains, Iran

This research focuses on the ASTER DEM generation for visual and mathematical analysis of topography, landscapes and landforms, as well as modeling of surface processes of Central Alborz, Iran. ASTER DEM 15 m generated using tie points over the Central Alborz and Damavand volcano with 5671 m height from ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) satellite data using PCI Geomatica 9.1. Geomorphic parameters are useful to identify and describe geomorphologic forms and processes, which were extracted from ASTER DEM in GIS environment such as elevation, aspect, slope angle, vertical curvature, and tangential curvature. Although the elevation values are slightly low in altitudes above 5500 m asl., the ASTER DEM is useful in interpretation of the macro- and meso-relief, and provides the opportunity for mapping especially at medium scales (1:100,000 and 1:50,000). ASTER DEM has potential to be a best tool to study 3D model for to geomorphologic mapping and processes of glacial and per glacial forms above 4300 m asl

Physical geomorphometry for elementary land surface segmentation and digital geomorphological mapping

By interpretations related to energy, elementary land surface segmentation can be treated as a physical problem. Many pieces of such a view found in the literature can be combined into a synthetic comprehensive physical approach. The segmentation has to be preceded by defining the character and size of searched units to result from the segmentation. A high-resolution digital elevation model (DEM) is the key input for this task; it should be generalized to the resolution best expressing information about the searched units. Elementary land surface units can be characterized by various parts of potential gravitational energy associated with a set of basic geomorphometric variables. Elevation above sea level (z) represents Global Geomorphic Energy (GGE). Regional and Local Geomorphic Energy (RGE and LGE) are parts of GGE, represented respectively by relative elevation above the local base level (zrel) and local relief (elevation differential in a moving window Δz). Derivation (change) of elevation defines the slope inclination (S), determining the local Potential Energy of Surface (PES) applicable to mass flow. Normal slope line (profile) curvature (kn)s and normal contour (tangential) curvature (kn)c express change in the PES value (ΔPES(kn )s, ΔPES(kn )c), responsible for acceleration/deceleration and convergence/ divergence of flow. Mean curvature (kmean) determines the Potential Energy of Surface applicable to Diffusion (PESD). Energetic interpretation of basic geomorphometric variables enables their direct comparison and systematic evaluation. Consequently, the homogeneity of basic geomorphometric variables defines a hierarchy of states of local geomorphic equilibria: static equilibrium, steady state, and non-steady state dynamic equilibrium. They are local attractors of landform development reflected in the geomorphometric tendency to symmetry (horizontality, various types of linearity, and curvature isotropy, together expressed by gravity concordance). Nonequilibrium and transitional states can be characterized by the PES excess (PESe) determined by difference curvature (kd), by gravity discordant change of the PES characterized by twisting curvature (τg)c, and by Integral Potential Energy of Surface Curvature (IPESC) expressed by Casorati curvature (kC) (general curvedness). Excluding zrel and Δz, all these energy-related geomorphometric variables are local point-based. Local area-based and regional variables such as Glock’s Available Relief, Melton Ruggedness Number, Stream Power Index, Openness, Topographic Position Index, Topographic Wetness Index, and Index of Connectivity also have energetic interpretations although their definition is more complex. Therefore we suggest exclusive use of the local point-based variables in designs of elementary land surface segmentation. The segmentation should take notice of natural interconnections, the hierarchy of geomorphometric variables, elements of Local Geomorphic Energy, and (dis)equilibria states, so that elementary segments are clearly interpretable geomorphologically. This is exemplified by Geographic Object-Based Image Analysis (GEOBIA) segmentation of Sandberg, a territory on the boundary of the Carpathians and Vienna Basin with a complex geomorphic history and marked morphodynamics. Compared with expert-driven field geomorphological mapping, the automatic physically-based segmentation resulted in a more specific delineation and composition of landforms. Physical-geomorphometric characteristics of the elementary forms enabled the formulation of their system and subsequent improvement of the expert-based qualitative genetic analysis, with interpretation leading to a deeper understanding of the development and recent dynamics of the landscape

Quality assessment of DEM derived from topographic maps for geomorphometric purposes

Digital elevation models (DEMs) play a significant role in geomorphological research. For geomorphologists reconstructing landform and drainage structure is frequently as important as elevation accuracy. Consequently, large-scale topographic maps (with contours, height points and watercourses) constitute excellent material for creating models (here called Topo-DEM) in fine resolution. The purpose of the conducted analyses was to assess the quality of Topo-DEM against freely-available globalDEMs and then to compare it with a reference model derived from laser scanning (LiDAR-DEM). The analysis also involved derivative maps of geomorphometric parameters (local relief, slope, curvature, aspect) generated on the basis of Topo-DEM and LiDAR-DEM. Moreover, comparative classification of landforms was carried out. It was indicated that Topo-DEM is characterised by good elevation accuracy (RMSE <2 m) and reflects the topography of the analyzed area surprisingly well. Additionally, statistical and percentage metrics confirm that it is possible to generate a DEM with very good quality parameters on the basis of a large-scale topographic map (1:10,000): elevation differences between Topo-DEM and: 1) topographic map amounted from−1.68 to +2.06 m,MAEis 0.10 m, RMSE 0.16 m; 2) LiDAR-DEM (MAE 1.13 m, RMSE 1.69 m, SD 1.83 m); 3) GPS RTK measurements amounted from−3.6 to +3.01 m, MAE is 0.72 m, RMSE 0.97 m, SD 0.97 m. For an area of several dozen km2 Topo-DEM with 10×10 m resolution proved more efficient than detailed (1×1 m) LiDAR-DEM

Integrating a UAV-derived DEM in object-based image analysis increases habitat classification accuracy on coral reefs

Very shallow coral reefs (<5 m deep) are naturally exposed to strong sea surface temperature variations, UV radiation and other stressors exacerbated by climate change, raising great concern over their future. As such, accurate and ecologically informative coral reef maps are fundamental for their management and conservation. Since traditional mapping and monitoring methods fall short in very shallow habitats, shallow reefs are increasingly mapped with Unmanned Aerial Vehicles (UAVs). UAV imagery is commonly processed with Structure-from-Motion (SfM) to create orthomosaics and Digital Elevation Models (DEMs) spanning several hundred metres. Techniques to convert these SfM products into ecologically relevant habitat maps are still relatively underdeveloped. Here, we demonstrate that incorporating geomorphometric variables (derived from the DEM) in addition to spectral information (derived from the orthomosaic) can greatly enhance the accuracy of automatic habitat classification. Therefore, we mapped three very shallow reef areas off KAUST on the Saudi Arabian Red Sea coast with an RTK-ready UAV. Imagery was processed with SfM and classified through object-based image analysis (OBIA). Within our OBIA workflow, we observed overall accuracy increases of up to 11% when training a Random Forest classifier on both spectral and geomorphometric variables as opposed to traditional methods that only use spectral information. Our work highlights the potential of incorporating a UAV’s DEM in OBIA for benthic habitat mapping, a promising but still scarcely exploited asset

Tracing the boundaries of Cenozoic volcanic edifices from Sardinia (Italy): a geomorphometric contribution

Unequivocal delimitation of landforms is an important issue for different purposes, from sciencedriven morphometric analysis to legal issues related to land conservation. This study is aimed at giving a new contribution to the morphometric approach for the delineation of the boundaries of volcanic edifices, applied to 13 monogenetic volcanoes (scoria cones) related to the Pliocene–Pleistocene volcanic cycle in Sardinia (Italy). External boundary delimitation of the edifices is discussed based on an integrated methodology using automatic elaboration of digital elevation models together with geomorphological and geological observations. Different elaborations of surface slope and profile curvature have been proposed and discussed; among them, two algorithms based on simple mathematical functions combining slope and profile curvature well fit the requirements of this study. One of theses algorithms is a modification of a function introduced by Grosse et al. (2011), which better performs for recognizing and tracing the boundary between the volcanic scoria cone and its basement. Although the geological constraints still drive the final decision, the proposed method improves the existing tools for a semi-automatic tracing of the boundaries