Identification Method of Topographic Surfaces Models

Abstract. Digital Terrain Models (DTMs) are still one of the most emerging products derived from remote sensing technologies such as LiDAR. A DTM usually is defined as the current digital representation of the earth´s surface. However, due to natural events and human influences the earth's surface is constantly changing. Therefore, the ability to analyse DTM data over time allows to understand and quantify changes, which are crucial for environmental monitoring, disaster management and urban planning. In this paper we introduce a GeoDBMS-based approach to manage, sustainably provide, analyse and visualize spatio-temporal DTM data. First, we review current approaches for the management and temporal modelling of DTM data. Then we present an event-based time-stamping spatio-temporal data model that meets special requirements for the management and analysis of DTMs to monitor spatial changes within the DTM in time. Based on this model, we present methods for the management and analysis of spatio-temporal DTMs. Thereby the model is extended by an appropriate server-infrastructure and a graphical user interface that enables to query, analyze, visualize and export time series of DTMs. Data consistency and accuracy for DTMs are also considered. A use case is conducted based on spatio-temporal DTM datasets of South-West Germany, demonstrating the suitability of the approach. Furthermore, geodetic applications and new DTM research directions are shown. Finally, conclusions are drawn from the paper and an outlook is presented describing our future research based on new use cases, including the analysis of DTMs and Digital Surface Models (DSMs) in the United Arab Emirates.

This article presents a review of the combined analysis of digital terrain models (DTMs) and remotely sensed data in landscape investigations. The utilization of remotely sensed data with DTMs has become an important trend in geomatics in the past two decades. Models of more than ten quantitative topographic variables are employed as ancillary data in the treatment of images. The article reviews the methods for DTM derivation and the basic problems of DTM operation that are important for handling DTMs with imagery, namely: 1) the choice of a DTM network type; 2) DTM resolution; 3) DTM accuracy; and 4) the precise superimposition of DTMs and images. The processing of remotely sensed data and DTMs in combination is used in the following procedures: 1) the image correction of the topographic effect; 2) the correction of geometric image distortion; 3) image classification; 4) statistical and comparative analyses of landscape data; and 5) three-dimensional landscape modelling. These procedures are applied to solve a wide range of problems in geobotany, geochemistry, soil science, geology, glaciology and other sciences. The joint use of imagery and DTMs can increase the total amount of information extracted from both types of data. The trend has been towards the incorporation of the combined analysis of remotely sensed data and DTMs into mixed environmental models. The following potential applications of the treatment of imagery in association with DTMs are identified: 1) the prediction of the migration and accumulation zones of water, mineral and organic substances moved by gravity along the land surface and in the soil; 2) the investigation of the relationships between topographically expressed geological structures and landscape properties; 3) the improvement of geological engineering in industrial planning (e.g., the construction of nuclear power stations, oil and gas pipelines and canals); and 4) the monitoring of existing industries. Digital models of plan, profile, mean and total accumulation curvatures, and nonlocal and combined topographic attributes should be included in data processing both to solve the problems indicated and to improve the outcome of some regular tasks (for example, the prediction of soil moisture distribution and fault recognition).

This work presents the results of an intensive examination of two competing digital terrain models: regular gridded digital elevation models (DEMs) and triangulated irregular networks (TINs). The importance of representing a surface as accurately as possible in a given amount of space or time is presented. The backgrounds of the DEM and TIN models are reviewed, including their origins, constructions, advantages and disadvantages. Some of the numerous possible applications of digital terrain models are described. A study to compare the two models over a wide variety of terrains is presented and described in detail. Twenty-five 7.5- minute study areas are carefully selected to be representative of the terrains found in the United Slates. Eight different terrain models — two DEMs and six TINs — are constructed: all are based, directly or indirectly, on the digitized contours found in the USGS DLC files. The gridded models are created with the latest USGS procedure, CTOG, which interpolates a grid from digitized contours. The TINs are created either from subsets of the grids or from samples of the contour vertices. The sizes of the TIN models arc constrained to one-tenth the number of points in the gridded models to permit an assessment of efficiency. The eight models are compared by assessing how accurately they estimate the elevations at three different sets of test points. Mean, maximum, RMSE, and 90th percentiles of error are computed and compared. Of the two gridded models, which differ only in their interpolant, simple linear interpolation proves to be more accurate than an inverse-distance weighting of the nine nearest neighbours. Neither of two procedures for selecting TIN vertices from a DEM yields models that are more accurate than the full DEM. Of three procedures for selecting TIN vertices from contours, preliminary Douglas line simplification can yield improved surface fits. The most significant conclusion is that none of the TINs produced represent the surface more accurately than a comparably-sized DEM. The per-point overhead associated with the irregular TIN structure appears to outweigh the advantage of variable resolution. Directions for further research are suggested. Ce travail présente les résultats d'un examen en profondeur de deux modèles numériques de terrain en compétition : les modèles numériques d'élévation (MNE) en quadrillage régulier et les réseaux de triangles irréguliers (RTI). On y décrit l'importance de représenter une surface aussi précisément que possible selon une quantité donnée d'espace et de temps. On revoit les donnees qui se rapportent aux MNE et RTI, entre autres, leurs origines, leurs modes de construction, leurs avantages et leurs désavantages. On décrit également quelques-unes des nombreuses applications des modèles numériques de terrain. On présente tout d'abord la description détaillée d'une étude comparative de deux modèles portant sur une grande variété de terrains. Vint-cinq zones d'étude, mesurant 7,5 minutes, ont été choisies soigneusement pour représenter les divers types de terrain que l'on retrouve aux États-Unis. On construit par la suite huit différents modèles de terrain, deux MNE et six RTI; ils sont tous basés, directement ou indirectement, sur la numérisation des courbes de niveau que l'on trouve dans les fichiers DLG produits par les Levés géologiques des États-Unis (USGS), Les modèles quadrillés sont construits a l'aide de la plus récente procédure de USGS, soit le programme CTOG, qui interpole un quadrillage à partir des courbes de niveau. Les RTI sont ainsi créés soit à partir de sous-ensembles des quadrillages, soit à partir d'échantillons des points d'inflexion des courbes de niveau. Pour permettre une évaluation de l'efficacité, on restreint les dimensions des modèles RTI a un dixième du nombre rie points des modeles quadrilles. Les huit modèles sont donc comparés en évaluant la précision avec laquelle ils estiment les élévations de trois différents jeux de points tests. On calcule puis on compare la moyenne, le maximum, l'erreur moyenne quadratique le les 90e centiles d'erreur. Des deux modèles quadrillés, qui différent seulement par leur valeur d'interpolation, il semble que l'interpolation linéaire simple est plus précise qu'une pondération inverse des neuf plus proches voisins. Aucune des deux procédures pour choisir des sommets de RTI à partir de MNE ne donne des modèles plus précis que le MNE complet. Des trois procédures pour choisir des sommets de RTI à partir de courbes de niveau, la généralisation préliminaire de courbe de Douglas-Plücker peut améliorer les jonctions de surface. La conclusion la plus significative est qu'aucun des RTI produits dans cette expérience ne représente la surface plus précisément qu'un MNE de dimensions comparables. Le fardeau que représente le nombre de points associés à la structure irrégulière d'un RTI semble peser plus que l'avantage d'une résolution variable. On suggère enfin des directions en vue de recherches ultérieures.

<p>Gully erosion is regarded as one of the worst land degradation processes in the world. Rapid identification of the location of gully features is urgently required, to aid in recognizing regions where gully erosion is prominent. Manual digitizing of gully features is both time consuming and prone to bias. Generating semi-automated or automated workflows to detect gully erosion allows quick and unbiased mapping of gully features over large extents.</p><p>In the Sandspruit catchment, South Africa, contour banks with a combined length of approximately 25000km have been constructed to mitigate soil erosion. Gullies are now mostly confined to narrow slivers in the natural vegetation, fynbos and Renosterveld, between agricultural fields. The morphological similarity and proximity of contour banks and gullies in this region provides a good test site to evaluate whether a semi-automated detection workflow could map gullies in complex, rough agricultural terrain.</p><p>Here, a Digital Surface Model (DSM) with a spatial resolution of 2m was used to test a semi-automated detection workflow in a Geographical Information System (GIS) environment. Two main building blocks were generated from the DSM: 1) a normalized DSM, created by subtracting a convolved mean DSM with a designated filter size from the original DSM, and 2) local slope generated from the normalized DSM. Subsequently, using expert knowledge, mapped gully polygons were refined and smoothed, by threshold determination, masking features not related to drainage, and pixel-based growing and shrinking. The semi-automated workflow was completed for two different spatial resolutions: 1) the native 2m-resolution and 2) a 0.5m-resolution DSM, upsampled without producing artificial values from interpolation methods. A GeoEye-1 image with a spatial resolution of 0.5m was included at the backend of the workflow as an additional step, to test whether gully mapping from using terrain attributes only, could be improved upon.     </p><p>Gully detection from terrain attributes only, achieved an overall accuracy of 0.68 (0.5m DSM) and 0.74 (2m DSM) with kappa values ranging from 0.36 (0.5m DSM) and 0.35 (2m DSM). The upsampled 0.5m DSM performed worse than the native 2m DSM due to increased noise detection. Although reasonable performance was obtained from the 2m DSM, issues encountered include: 1) vegetation that caused some inaccuracies in gully boundary delineation and discontinuities along gully channels and 2) false positive detection of contour banks. The addition of the GeoEye-1 image increased overall accuracy to 0.79 and kappa value to 0.5, mostly because of the elimination of false positives in agricultural fields.</p><p>The accuracy statistics indicate that the semi-automated detection workflow developed here shows promise as a tool to detect gully erosion on a catchment scale. Furthermore, due to the workflow being built upon the distinct morphology of gully features, it could be transferable to other regions that are dissimilar to the Sandspruit catchment. The transferability of the workflow should be tested in future, in addition to how accuracy would be affected if the DSM were substituted with a Digital Terrain Model (DTM) of similar spatial resolution.</p>

Slope angle and aspect as influencing factors on the accuracy of the SRTM and the ASTER GDEM databases

The article discusses the various types of surveyed digital terrain models the points of which are assumed to describe a surface approximating the true earth surface; these models being differentiated by the surveying process only. The suitability of the various model types as an input for computer assisted cartographic utilisation is discussed and judged from the point of view of a relief cartographer with a geodetic, photogrammetric and geomorphological background. The pure mathematical analysis of digital terrain models is rejected in principle and a spatially-geometrical approach recommended. The necessity for mathematical interpolation of secondary DTMs based on surveyed values as input for computer assisted cartographic products is doubted and the opinion is expressed that cartographic and/or cartometric evaluation should be based directly on the approximation surface described by the surveyed values irrespective of the geometric disposition.

Detailed analysis of Digital Terrain Models (DTMs), digital imagery, and a discussion of their various applications and derived geothematic products are presented for study areas in two different geological and geomorphological contexts of North West (NW) of Italy. In both cases it has been proposed an integrated approach for geomorphological analysis that put in evidence many advantages of using these new geomatics tools.In the first context, digital geomorphological mapping of high altitude areas of the Aosta Valley (Gran Paradiso and Gran San Bernardo) have been carried out by using photogrammetry and remote sensing on airborne laser scanner data (LiDAR derived DTM) and orthophotos. Suitable results have been obtained for areas of difficult accessibility, with reduced costs and work time compared to traditional field techniques.In the second geomorphological context, high-resolution images of the present topography of the high Piedmont plain (Turin, Asti and Cuneo Provinces) have been used to perform GIS mapping and analysis. Evidences of Quaternary modifications in the hydrographic network have been enhanced, suggesting new geomorphological elements for the reconstruction of the recent geodynamic history of the area.

This study focuses on using techniques such as digital terrain model (DTM), geographic information system (GIS), and decision support system (DSS) for forestland ecosystem classification and suitability analysis of the Liukuei Experimental Forest of Taiwan Forestry Research Institute. The content includes the delineation of ecosystem units using DTM, the development of a hierarchical ecosystem classification system using GIS and multivariate statistical analysis, and the establishment of a forestland classification DSS with an application on site selection of a Taiwanese native species-Taiwania (Taiwania cryptomerioides). The results indicate that DTM is a fast, easy, feasible, and automatic approach for delineating ecosystem units of different spatial scales. The developed hierarchical ecosystem classification is a satisfactory scheme for Liukuei's forestland classification because the developed scheme coincides with the terrain characteristics along a continuum. The established DSS can effectively and feasibly analyze forestland classification under different spatial scales. Meanwhile, the system can easily perform site selection for Taiwania. From the results, it is concluded that techniques such as DTM, GIS, and DSS are useful for forest managers in the reasonable planning of forestland classification and management practice. In addition, the ecosystem approaches obtained from the Experimental Forest can be extended to island-wide forestland classification in Taiwan.

The grain‐scale topography of a sediment surface is a key component of a fluvial system, affecting aspects including sediment transport, flow resistance and ecology. However, its effect is hard to quantify because of the need for grain‐scale elevation data from in situ fluvial gravel surfaces which are difficult to collect. The sediment surface properties are, therefore, commonly estimated as a function of the sediment grain‐size distribution; however, because of additional factors, such as grain packing and shape, there is not necessarily a unique relationship between the two. A new methodology has been developed that uses terrestrial laser scanning to collect grain‐scale topographic data from in situ fluvial gravel surfaces, from which digital terrain models are created. This paper investigates methods of analysing such digital terrain models, and possible sedimentological interpretations that can be drawn from the analysis. Eleven digital terrain models from exposed gravel surfaces in two contrasting rivers (the River Feshie and Bury Green Brook) were analysed by calculating: the distribution of surface elevations, semivariograms, surface inclinations, surface slopes and aspects and grain orientation. The distribution of surface elevations and surface slope and aspect analysis were found to be most informative. In the River Feshie, grain‐size was interpreted as being a dominant control on sediment surface structure and gravel imbrication was identified. In Bury Green Brook, the location of the digital terrain models within the riffle–pool sequence was the dominant control on surface structure and grain orientation. Such digital terrain models therefore provide a new approach to measuring and quantifying the topography of fluvial sediment surfaces.

Utilizing multispectral satellite data and digital elevation models (DEMs) has emerged as the primary approach for cartographically representing landforms. By using high-resolution satellite photos that capture spatial, temporal, spectral, and radiometric data, one may get a fresh comprehension of the geomorphology of a particular area by recognizing its landforms. In addition, a synergistic method is used by using data produced from digital elevation models (DEMs) such as Slope, Aspect, Hillshade, Curvature, Contour Patterns, and 3-D Flythrough Visuals. The increasing use of UAV (drone) technology for obtaining high-resolution digital images and elevation models has become an essential element in developing complete topographic models in landslide scars that are very unstable and prone to erosion. Comparison (differences in values) of seven (7) different DEMs between two algorithms used, i.e., QGIS and White Box Tool (WBT), were successfully attempted in the present research. The TLS, UAV and Satellite data of the study area—Kshetrapal Landslide, Chamoli (District), Uttarakhand (State), India was subjected to two different algorithms (QGIS and WBT) to evaluate and differentiate seven different DEMs (CARTOSAT, ASTER, SRTM, Alos 3D, TanDEM, MERIT, and FabDEM/FATHOM) taking into consideration various parameters viz. Aspect, Hillshade, Slope, Mean Curvature, Plan Curvature, Profile Curvature and Total Curvature. The different values of aforesaid parameters of various DEMs evaluated (using algorithms QIGS and WBT) reveal that only three parameters, i.e., Aspect, Hillshade, and Slope, show results. In contrast, the remaining ones do not show any meaningful results, and therefore, the comparison was possible only with regard to these three parameters. The comparison is drawn by comparing minimum, maximum, and elevation values (by subtracting WBT values from QGIS values) regarding Aspect, Hillshade, and Slope, arranging the differences in values as per their importance. (Increasing or decreasing order), assigning merit scores individually, and then cumulatively, and ascertaining the order of application suitability of various Dems, which stand in the order of (CARTOSAT, ASTER, SRTM, Alos 3D, TanDEM, and MERIT, and FabDEM/FATHOM).

Multi‐resolution terrain models are an efficient approach to improve the speed of three‐dimensional (3D) visualizations, especially for terrain visualization in Geographical Information Systems (GIS). As a further development to existing algorithms and models, a new model is proposed for the construction of multi‐resolution terrain models in a 3D GIS. The new model represents multi‐resolution terrains using two major methods for terrain representation: Triangulated Irregular Network (TIN) and regular grid (Grid). In this paper, first, the concepts and formal definitions of the new model are presented. Second, the methodology for constructing multi‐resolution terrain models based on the new model is proposed. Third, the error of multi‐resolution terrain models is analysed, and a set of rules is proposed to retain the important features (e.g. boundaries of man‐made objects) within the multi‐resolution terrain models. Finally, several experiments are undertaken to test the performance of the new model. The experimental results demonstrate that the new model can be applied to construct multi‐resolution terrain models with good performance in terms of time cost and maintenance of the important features. Furthermore, a comparison with previous algorithms/models shows that the speed of rendering for 3D walking/flying through has been greatly improved by applying the new model.

The accuracy and efficiency of the simulations in distributed hydrological models must depend on the proper estimation of flow directions and paths. Numerous studies have been carried out to delineate the drainage patterns based on gridded digital elevation models (DEMs). The triangulated irregular network (TIN) has been increasingly applied in hydrological applications due to the advantages of high storage efficiency and multi‐scale adaptive performance. Much of the previous literature focuses mainly on filling the depressions on gridded DEMs rather than treating the special cases in TIN structures, which has hampered its applications to hydrological models. This study proposes a triangulation‐based solution for the removal of flat areas and pits to enhance the simulation of flow routing on triangulated facet networks. Based on the drainage‐constrained TIN generated from only a gridded DEM by the compound point extraction (CPE) method, the inconsistent situations including flat triangles, V‐shape flat edges and sink nodes are respectively identified and rectified. The optimization algorithm is an iterative process of TIN reconstruction, in which the flat areas are generalized into their center points and the pits are rectified by embedding break lines. To verify the proposed algorithm and investigate the potential for flow routing, flow paths of steepest descent are derived by the vector‐based tracking algorithm based on the optimized TIN. A case study of TIN optimization and flow path tracking was performed on a real‐world DEM. The outcomes indicate that the proposed approach can effectively solve the problem of inconsistencies without a significant loss in accuracy of the terrain model.

A scale-adaptive digital elevation model (S-DEM) method is proposed for multi-scale terrain analysis using a single high-resolution digital elevation model (DEM) database. The motivation is to construct a DEM that is self-adaptive to a given scale of an application, rather than letting the application fit into the built-in scale of the DEM. The method is based on an adaptive compound point extraction (CPE) algorithm that extracts surface ‘significant points’ from a high-resolution DEM according to their degree of importance (DOI) to the scale of an application. A data structure can be established to match the demand from an application at a coarser scale. Based on the data structure, a triangulated irregular network (TIN) model can be generated to support the terrain analysis at the desired scale. The aim of the S-DEM is to support multi-scale applications in three aspects, namely, ‘one database for all scales and scale-adaptive’ (i.e. matching any application scale using a single high-resolution DEM), ‘consistent measurement’ (i.e. delivering more constant measurements of terrain parameters with changing scales), and ‘skeleton preservation’ (i.e. preserving basic streamlines with changing scales). Compared with the raster resampling algorithm and the maximum z-tolerance algorithm, we find that the proposed method offers better performance, providing values that meet the accuracy requirements set by DEM data standards for different scales, and producing analytical derivatives that retain terrain features with consistent measurements of terrain parameters.

There is no doubt that the tremendous development of information technology was one of the driving factors behind the great growth of surveying and geodesy science. This has spawned modern geospatial techniques for data capturing, acquisition, and visualization tools. Digital elevation model (DEM) is the 3D depiction of continuous elevation data over the Earth’s surface that is produced through many procedures such as remote sensing, photogrammetry, and land surveying. DEMs are essential for various surveying and civil engineering applications to generate topographic maps for construction projects at a scale that varies from 1:500 to 1:2,000. GIS offers a powerful tool to create a DEM with high resolution from accurate land survey measurements using interpolation methods. The aim of this research is to investigate the impact of estimation techniques on generating a reliable and accurate DEM suitable for large-scale mapping. As a part of this study, the deterministic interpolation algorithms such as ANUDEM (Topo to Raster), inverse distance weighted (IDW), and triangulated irregular network (TIN) were tested using the ArcGIS desktop for elevation data obtained from real total station readings, with different landforms to show the effect of terrain roughness, data density, and interpolation process on DEM accuracy. Furthermore, comparison and validation of each interpolator were carried out through the cross-validation method and numerous graphical representations of the DEM. Finally, the results of the investigations showed that ANUDEM and TIN models are similar and significantly better than those attained from IDW.

The correct representation of the topography of terrain is an important requirement to generate photogrammetric products such as orthoimages and maps from high-resolution (HR) or very high-resolution (VHR) satellite datasets. The refining of the digital elevation model (DEM) for the generation of an orthoimage is a vital step with a direct effect on the final accuracy achieved in the orthoimages. The refined DEM has potential applications in various domains of earth sciences such as geomorphological analysis, flood inundation mapping, hydrological analysis, large-scale mapping in an urban environment, etc., impacting the resulting output accuracy. Manual editing is done in the presented study for the automatically generated DEM from IKONOS data consequent to the satellite triangulation with a root mean square error (RMSE) of 0.46, using the rational function model (RFM) and an optimal number of ground control points (GCPs). The RFM includes the rational polynomial coefficients (RPCs) to build the relation between image space and ground space. The automatically generated DEM initially represents the digital surface model (DSM), which is used to generate a digital terrain model (DTM) in this study for improving orthoimages for an area of approximately 100 km2. DSM frequently has errors due to mass points in hanging (floating) or digging, which need correction while generating DTM. The DTM assists in the removal of the geometric effects (errors) of ground relief present in the DEM (i.e., DSM here) while generating the orthoimages and thus improves the quality of orthoimages, especially in areas such as Dehradun that have highly undulating terrain with a large number of natural drainages. The difference image of reference, i.e., edited IKONOS DEM (now representing DTM) and automatically generated IKONOS DEM, i.e., DSM, has a mean difference of 1.421 m. The difference DEM (dDEM) for the reference IKONOS DEM and generated Cartosat-1 DEM at a 10 m posting interval (referred to as Carto10 DEM) results in a mean difference of 8.74 m.