Digital Terrain Modeling

Florinsky, Igor V.

doi:10.1016/b978-0-12-804632-6.00001-8

Cited by 68 publications

(68 citation statements)

References 40 publications

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“…Currently, geomorphometric methods are widely used to solve various multiscale problems of geomorphology, hydrology, remote sensing, soil science, geology, geophysics, geobotany, glaciology, oceanology, climatology, planetology and other disciplines; see reviews (Clarke and Romero, 2017; Deng, 2007; Florinsky, 1998b; Jordan, 2007; Lecours et al, 2016; Minár et al, 2016; Moore et al, 1991; Pike, 2000; Wasklewicz et al, 2013; Wilson, 2012) and books (Florinsky, 2016; Hengl and Reuter, 2009; Li et al, 2005; Wilson and Gallant, 2000).…”

Section: Introductionmentioning

confidence: 99%

An illustrated introduction to general geomorphometry

Florinsky

2017

Progress in Physical Geography: Earth and Environment

102

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Geomorphometry is widely used to solve various multiscale geoscientific problems. For the successful application of geomorphometric methods, a researcher should know the basic mathematical concepts of geomorphometry and be aware of the system of morphometric variables, as well as understand their physical, mathematical and geographical meanings. This paper reviews the basic mathematical concepts of general geomorphometry. First, we discuss the notion of the topographic surface and its limitations. Second, we present definitions, formulae and meanings for four main groups of morphometric variables, such as local, non-local, two-field specific and combined topographic attributes, and we review the following 29 fundamental morphometric variables: slope, aspect, northwardness, eastwardness, plan curvature, horizontal curvature, vertical curvature, difference curvature, horizontal excess curvature, vertical excess curvature, accumulation curvature, ring curvature, minimal curvature, maximal curvature, mean curvature, Gaussian curvature, unsphericity curvature, rotor, Laplacian, shape index, curvedness, horizontal curvature deflection, vertical curvature deflection, catchment area, dispersive area, reflectance, insolation, topographic index and stream power index. For illustrations, we use a digital elevation model (DEM) of Mount Ararat, extracted from the Shuttle Radar Topography Mission (SRTM) 1-arc-second DEM. The DEM was treated by a spectral analytical method. Finally, we briefly discuss the main paradox of general geomorphometry associated with the smoothness of the topographic surface and the non-smoothness of the real topography; application of morphometric variables; statistical aspects of geomorphometric modelling, including relationships between morphometric variables and roughness indices; and some pending problems of general geomorphometry (i.e. analysis of inner surfaces of caves, analytical description of non-local attributes and structural lines, as well as modelling on a triaxial ellipsoid). The paper can be used as a reference guide on general geomorphometry.

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Section: Introductionmentioning

confidence: 99%

An illustrated introduction to general geomorphometry

Florinsky

2017

Progress in Physical Geography: Earth and Environment

102

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“…Here, the meso-tidal range (~2.8 m) made moving the local shoreline on a wide cross-shore span of about 400 m over the observed time. Alternative remote-sensing sources for retrieving GCPs elevation are the aerial LiDAR (e.g., [88][89][90]), satellite altimetry data (e.g., [91]) or unmanned aerial vehicle (UAV) (e.g., [92]). However, these types of data are not always available and/or do not have the adequate resolution, and/or require intensive computational effort which would make more difficult the methodology.…”

Section: Discussionmentioning

confidence: 99%

Operational Use of Surfcam Online Streaming Images for Coastal Morphodynamic Studies

2019

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Coastal video monitoring has been proven to be a valuable shore-based remote-sensing technique to study coastal processes, as it offers the possibility of high-frequency, continuous and autonomous observations of the coastal area. However, the installation of a video systems infrastructure requires economical and technical efforts, along with being often limited by logistical constraints. This study presents methodological approaches to exploit “surfcam” internet streamed images for quantitative scientific studies. Two different methodologies to collect the required ground control points (GCPs), both during fieldwork and using web tools freely available are presented, in order to establish a rigorous geometric connection between terrestrial and image spaces. The application of an image projector tool allowed the estimation of the unknown camera parameters necessary to georectify the online streamed images. Three photogrammetric procedures are shown, distinct both in the design of the computational steps and in number of GCPs available to solve the spatial resection system. Results showed the feasibility of the methodologies to generate accurate rectified planar images, with the best horizontal projection accuracy of 1.3 m compatible with that required for a quantitative analysis of coastal processes. The presented methodologies can turn “surfcam” infrastructures and any online streaming beach cam, into fully remote shore-based observational systems, fostering the use of these freely available images for the study of nearshore morphodynamics.

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“…Further research and improvement of the approach will be conducted with regard to two aspects: (1) in the course of the analysis, it became apparent that a more sophisticated investigation of the spatial distribution of ground points with point pattern analysis (e.g., average nearest neighbours (ANN), Ripley's K) could complement the proposed RUI. Hence, an additional uncertainty indication could be provided.…”

Section: Discussionmentioning

confidence: 99%

“…Very high spatial resolution (VHSR) stereo-imagery from airborne (resolution of a few centimeters) and space-borne (resolution of a few meters to sub-meter) sensor systems enable the generation of digital surface models (DSM) using digital photogrammetric approaches [1][2][3]. For some applications and for further analysis steps, an additional DSM-derived digital elevation model (DEM) and a subsequently generated normalized DSM (nDSM; related to ground level) are desirable.…”

Section: Introductionmentioning

confidence: 99%

Terrain Extraction in Built-Up Areas from Satellite Stereo-Imagery-Derived Surface Models: A Stratified Object-Based Approach

Luethje

Tiede

Eisank

2017

IJGI

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Very high spatial resolution (VHSR) stereo-imagery-derived digital surface models (DSM) can be used to generate digital elevation models (DEM). Filtering algorithms and triangular irregular network (TIN) densification are the most common approaches. Most filter-based techniques focus on image-smoothing. We propose a new approach which makes use of integrated object-based image analysis (OBIA) techniques. An initial land cover classification is followed by stratified land cover ground point sample detection, using object-specific features to enhance the sampling quality. The detected ground point samples serve as the basis for the interpolation of the DEM. A regional uncertainty index (RUI) is calculated to express the quality of the generated DEM in regard to the DSM, based on the number of samples per land cover object. The results of our approach are compared to a high resolution Light Detection and Ranging (LiDAR)-DEM, and a high level of agreement is observed-especially for non-vegetated and scarcely-vegetated areas. Results show that the accuracy of the DEM is highly dependent on the quality of the initial DSM and-in accordance with the RUI-differs between the different land cover classes.

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Digital Terrain Modeling

Cited by 68 publications

References 40 publications

An illustrated introduction to general geomorphometry

An illustrated introduction to general geomorphometry

Operational Use of Surfcam Online Streaming Images for Coastal Morphodynamic Studies

Terrain Extraction in Built-Up Areas from Satellite Stereo-Imagery-Derived Surface Models: A Stratified Object-Based Approach

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