Wykorzystanie danych NMT na potrzeby opracowania bilansu mas ziemnych

Distributed testing of a system of systems such is critical to successful development and fielding. Developmental and operational test planning, mission rehearsal, and modeling and simulation of distributed test events requires rapid generation of high-fidelity synthetic environments and geospatial databases that allow efficient transmission and portrayal over network-centric architectures and low-bandwidth communications networks. This paper describes an initiative lead by the U.S. Army Developmental Test Center to rapidly construct digital terrain and surface models using remote sensing data. The authors present methods and techniques used to generate Digital Terrain Elevation Data (DTED) Level 5 or better digital terrain models, surface object databases using Three-Dimensional (3-D) data from airborne Light Detection and Ranging (LIDAR) sensors, and mathematical operations to describe complex geospatial data objects and 3-D topology in highly-compact manners. Currently, units-of-action undergo testing within a defined Common Operating Area (COA) at a training range or proving ground. In coming years, distributed testing, with simulated scenes added to the participating systems, will occur at multiple COAs located at different test facilities. Consistent construction is required for these synthetic environments or scenes for the different facilities. The authors will present trade study results with recommendations for a uniform set of data collection requirements.

Digital Terrain Model (Digital Terrain Model acronym DTM) is arbitrary use of a large number of coordinates in three-dimensional x, y, z coordinates of the point on the ground for a form of Statistics said that the terrain surface morphology is the number of attribute information is a space location characteristics and attributes of the terrain described the figures, initially for the automatic design of highway proposed. With the world of computer technology and the rapid development of 3-D visualization technology into the traditional static two-dimensional map of the three-dimensional terrain modeling makes a Geographic Information System (GIS) and digital mapping, a new field of study. DTM is the basis of geographic information system data, mainly used to describe the ground state of ups and downs, the terrain can be used to extract various parameters such as slope, aspect, roughness, and Visibility analysis, watershed generation applications such as structural analysis. Therefore, the DTM in land use analysis, and rational planning, forecasting flood danger, as well as military navigation and missile guidance systems, and combat electronic sand table, and other fields are widely used. Digital Terrain Elevation Model mainly contains the attributes of surface morphology, as well as other attributes, such as slope, aspect and so on. Terrain Elevation attribute is the basis of the model attributes, other elements of the terrain elevation attributes can be directly or indirectly receive, digital elevation model (Digital Elevation Model, acronym DEM) acts as a digital terrain on the main study. DEM is that the number of regional terrain, elevation Z coordinates on the plane X, Y, the two variables of continuous function of a limited discrete said, a series of ground from the X, Y location and elevation linked by some Organization structure with the actual terrain features that the spatial distribution model, it is a spatial information system an important component part.

The digitalization of urban mechanisms relies on the integration of digital terrain and 3D city models. However, a systematic examination of this topic within the context of integrated smart cities or digital twins has been lacking, hindering reproducibility and interpretation of results. To address this gap, this study conducts a systematic literature review to explore the role of digital terrain and 3D city models in supporting urban decision-making for integrated smart cities or digital twins. By following a review protocol, research questions were formulated, and systematic search strategies were implemented involving reputable databases such as Scopus, Web of Science, Science Direct, Emerald, Taylor Francis, Springer Link, and Sage Journals. The review process included identification, screening, eligibility assessment, quality appraisal, data extraction, and thematic analysis. The thematic analysis identified eight main themes and 22 sub-themes, shedding light on various aspects of digital terrain and 3D city models in urban decision-making, including (1) data integration and interoperability, (2) integrated visualization; (3) environmental simulation; (4) digital twins application; (5) smart cities application; (6) semantic enrichment; (7) applied planning; and (8) urban planning. This systematic review identifies gaps in the field and provides directions for future studies.

Terrain analysis is the quantitative analysis of topographic surfaces. The purpose of a digital terrain system is to provide the digital representation of terrain so that environmental problem like soil erosion may be approached accurately and efficiently through automated means. Traditionally this was (and still is!) being done manually by using topographic/contour maps. With the availability of Digital Elevation Models (DEM) and GIS tools, watershed properties can be extracted by using automated procedures. Remote Sensing and Digital elevation models (DEMs) are known to be very useful data sources for the automated delineation of flow paths, sub watersheds and flow networks for hydrologic modelling and watershed characterization. The digital terrain model was extracted from a 90m resolution Shuttle Radar Topographic Mission (SRTM) of the study area. The SRTM data was corrected by removing voids, striping, tree offsets and random noise. The SRTM DEM data was projected from geographic coordinate WGS 84 to UTM zone 32 of the study area. The 3-D analysis tool of the ArcGIS 10.1 was used for this process. The DEM was processed to obtain the Slope, Contour, Flow direction, Flow accumulation, Flow length, Stream power Index of the study area. The study proved that SRTM elevation dataset has the ability to obviate the lack of terrain data for hydrologic modelling using ArcGIS where appropriate data for terrain modelling and simulation of hydrological processes is unavailable.

Problem. Fast and high-quality development of project solutions for transport infrastructure objects and other linear artificial structures is based on the application of automated design systems. Modern automated design systems use digital 2D and 3D terrain models as input data. The development of digital terrain modeling is motivated by both the development of automated design systems and the development of specialized geodesic equipment. Functional capabilities of modern geodetic equipment in combination with systems for automated processing of geodetic measurement results make it possible to significantly reduce the time of measurement and processing of results and significantly improve the quality of the obtained results. Goal. The goal is to analyze the features of building a digital 3D model of the terrain of linear structures based on the results of measurements by a mobile laser scanner. Methodology. The technical parameters and functional capabilities of the Trimble MX2 mobile laser 3D scanner were analyzed. The Trimble MX2 mobile laser scanner is a high-speed and productive scanning system designed for installation in a vehicle. Results. The Trimble MX2 mobile laser 3D scanner allows you to perform laser scanning of the road surface and the surrounding area and create output data for building a digital terrain model. A digital terrain model using this technology can be created without stopping traffic flow. The Trimble MX2 mobile laser 3D scanner is mounted on the base of a passenger car and requires the involvement of one driver and one surveyor operator. The main elements of the system – an inertial sensor, GNSS receivers and scanning heads allow obtaining a cloud of points with high positioning accuracy. The system is managed through the operator's console in the car interior. With the help of systems for automated processing of measurement results, the cloud of points is transformed into a geospatial model of the area, which allows you to obtain a digital model of the area many times faster than using traditional measurement methods. Originality. Thanks to the available Trimble MX2 GNSS receivers in the scanning system and with the help of the Trident Imaging Hub software complex, the obtained measurement results are linked to the desired coordinate system and the scanning system route is visualized, which enables to link all the obtained results with absolutely clear positioning on the terrain. Practical value. With the use of the Trimble MX2 scanning system, road surveys of Ukraine are already being carried out, which allows to quickly and qualitatively develop capital repair and reconstruction projects and to determine the necessary measures for the proper operational maintenance of road sections.

LiDAR data have become indispensable for research in archaeology and a variety of other topographic applications. To derive products (e.g. digital terrain or feature models, individual trees, buildings), the 3D LiDAR points representing the desired objects of interest within the acquired and georeferenced point cloud need to be identified. This process is known as classification, where each individual point is assigned to an object class. In archaeological prospection, classification focuses on identifying the object class ‘ground points’. These are used to interpolate digital terrain models exposing the microtopography of a terrain to be able to identify and map archaeological and palaeoenvironmental features. Setting up such classification workflows can be time‐consuming and prone to information loss, especially in geographically heterogeneous landscapes. In such landscapes, one classification setting can lead to qualitatively very different results, depending on varying terrain parameters such as steepness or vegetation density. In this paper, we are focussing on a special workflow for optimal classification results in these heterogeneous environments, which integrates expert knowledge. We present a novel Python‐based open‐source software solution, which helps to optimize this process and creates a single digital terrain model by an adaptive classification based on spatial segments. The advantage of this approach for archaeology is to produce coherent digital terrain models even in geomorphologically heterogenous areas or areas with patchy vegetation. The software is also useful to study the effects of different algorithm and parameter combinations on digital terrain modelling with a focus on a practical and time‐saving implementation. As the developed pipelines and all meta‐information are made available with the resulting data set, classification is white boxed and consequently scientifically comprehensible and repeatable. Together with the software's ability to simplify classification workflows significantly, it will be of interest for many applications also beyond the examples shown from archaeology.

Terrain surfaces conserve human activities in terms of textures and structures. With reference to archaeological questions, the geological archive is investigated by means of models regarding anthropogenic traces. In doing so, the high-resolution digital terrain model is of inestimable value for the decoding of the archive. The evaluation of these terrain models and the reconstruction of historical surfaces is still a challenging issue. Due to the data collection by means of LiDAR systems (light detection and ranging) and despite their subsequent pre-processing and filtering, recently anthropogenic artefacts are still present in the digital terrain model. Analysis have shown that elements, such as contour lines and channels, can well be extracted from a high-resolution digital terrain model. This way, channels in settlement areas show a clear anthropogenic character. This fact can also be observed for contour lines. Some contour lines representing a possibly natural ground surface and avoid anthropogenic artefacts. Comparable to channels, noticeable patterns of contour lines become visible in areas with anthropogenic artefacts. The presented workflow uses functionalities of ArcGIS and the programming language R.1 The method starts with the extraction of contour lines from the digital terrain model. Through macroscopic analyses based on geomorphological expert knowledge, contour lines are selected representing the natural geomorphological character of the surface. In a first step, points are determined along each contour line in regular intervals. This points and the corresponding height information which is taken from an original digital terrain model is saved as a point cloud. Using the programme library gstat, a variographic analysis and the use of a Kriging-procedure based on this follow.2-4 The result is a digital terrain model filtered considering geomorphological expert knowledge showing no human degradation in terms of artefacts, preserving the landscape-genetic character and can be called a prehistoric terrain model.

Impacts of random attitude measurement errors (RAME) made by the global positioning system (GPS)/inertial measurement unit (IMU) integrated system on elevation accuracy of a digital surface model (DSM) reconstructed from an airborne laser scanning (ALS) system were evaluated. By numerical simulation, three common terrain models, i.e., a planar, a rectangular, and a hemispheric terrain model, were established, and the scanning processes of the ALS system for the three terrain models were simulated to analyze the effects of RAME on reconstructed DSMs. Furthermore, a semi-physical simulation experimental setup was constructed to verify the results obtained from the numerical simulation. A physical terrain model was scanned to quantitatively evaluate the impacts of RAME on positioning accuracy of a laser point cloud and elevation accuracy of a reconstructed DSM. Experimental results show that under the condition of experimental “flight” height of 1310 mm and affected by two kinds of RAME with different standard deviations, i.e., 0.01° and 0.1°, the RMS values of elevation error of reconstructed DSMs increase 0.04 and 1.56 mm, respectively, corresponding to 0.015 and 0.595 m at actual flight height of 500 m. Therefore, if the elevation error of a reconstructed DSM caused by RAME is requested to be lower than 1 cm under the condition of flight height of 500 m, the random attitude measurement accuracy of the GPS/IMU integrated system should be higher than 0.01° (1σ) at least.

The Norwegian Water Resources and Energy Administration has photographed glacial areas in Norway for several decades. Detailed maps or digital terrain models have been made for selected glaciers from vertical aerial photographs. Multiple models of seven glaciers have been used here to calculate glacier volume change during the time between mappings using the geodetic method. Analyses and results are presented and compared with traditional mass-balance measurements. We estimated uncertainties of ±1.3–2.7mw.e. for the geodetic method, and ±1.3 –3.5mw.e. for the traditional method. The discrepancies between the methods varied between 0.4 and 4.7 mw.e. All glaciers decreased in volume from the 1960s/70s to the 1990s, except Hardangerjøkulen. This glacier experienced a significant increase in volume: the geodetic and traditional methods showed net balance values of +6.8m and +9.4mw.e., respectively. Trollbergdalsbreen had the largest total volume loss: the geodetic and traditional methods showed net balance values of –12.3 and –16.8mw.e.

Digital aerial photogrammetry (DAP) and unmanned aerial systems (UAS) have emerged as synergistic technologies capable of enhancing forest inventory information. A known limitation of DAP technology is its ability to derive terrain surfaces in areas with moderate to high vegetation coverage. In this study, we sought to investigate the influence of flight acquisition timing on the accuracy and coverage of digital terrain models (DTM) in a low cover forest area in New Brunswick, Canada. To do so, a multi-temporal UAS-acquired DAP data set was used. Acquired imagery was photogrammetrically processed to produce high quality DAP point clouds, from which DTMs were derived. Individual DTMs were evaluated for error using an airborne laser scanning (ALS)-derived DTM as a reference. Unobstructed road areas were used to validate DAP DTM error. Generalized additive mixed models (GAMM) were generated to assess the significance of acquisition timing on mean vegetation cover, DTM error, and proportional DAP coverage. GAMM models for mean vegetation cover and DTM error were found to be significantly influenced by acquisition date. A best available terrain pixel (BATP) compositing exercise was conducted to generate a best possible UAS DAP-derived DTM and outline the importance of flight acquisition timing. The BATP DTM yielded a mean error of −0.01 m. This study helps to show that the timing of DAP acquisitions can influence the accuracy and coverage of DTMs in low cover vegetation areas. These findings provide insight to improve future data set quality and provide a means for managers to cost-effectively derive high accuracy terrain models post-management activity.

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.

Digital terrain modelling and industrial surface metrology — converging crafts

The article presents a comprehensive analysis of modern approaches to digital terrain modeling based on intel ligent geographic information systems and advanced information technologies. It highlights the evolution of terrain modeling methods — from traditional GIS technologies to the integration of artificial intelligence ap proaches (the GeoAI concept). The purpose of the study is to generalize the capabilities and advantages of ap plying artificial intelligence (machine learning, deep learning, and computer vision) to digital terrain modeling tasks and to identify prospects for the development of such intelligent systems. The study explores the application potential of supervised machine learning algorithms (decision trees, Random Forest, SVM) for landform classification and remote sensing data processing, as well as deep learning methods (CNN) for automatic pattern recognition and semantic terrain segmentation. Examples of intelligent GIS solu tions are provided in various applied fields: slope stability monitoring systems with landslide forecasting, flood risk assessment models, and military terrain planning systems with drone route optimization. The main results demonstrate that the implementation of AI technologies enables unprecedented detail and automation in terrain analysis. Modern geospatial intelligent systems are capable of integrating heterogeneous data sources (LiDAR scans, satellite imagery, drone data, ground sensors) and updating digital terrain models in real time, thereby supporting decision-making in land management and emergency response. The future development of GeoAI is defined by the continued integration of diverse data sources, the transition from static 3D models to dynamic 4D terrain representations, semantic enrichment of digital models (land scape ontologies, object detection), and their integration into the concept of territorial digital twins. It is con cluded that the synergy of traditional GIS tools with state-of-the-art artificial intelligence technologies is transforming the field of digital terrain modeling, opening new horizons for scientific research and practical applications.

Geomorphometry, the science of digital terrain analysis (DTA), is an important focus of research in both geomorphology and geographical information science (GIS). Given that 70% of China is mountainous, geomorphological research is popular among Chinese scholars, and the development of GIS over the last 30 years has led to significant advances in geomorphometric research. In this paper, we review Chinese progress in geomorphometry based on the published literature. There are three major areas of progress: digital terrain modelling methods, DTA methods, and applications of digital terrain models (DTMs). First, traditional vector- and raster-based terrain modelling methods, including the assessment of uncertainty, have received widespread attention. New terrain modelling methods such as unified raster and vector, high-fidelity, and real-time dynamic geographical scene modelling have also attracted research attention and are now a major focus of digital terrain modelling research. Second, in addition to the popular DTA methods based on topographical derivatives, geomorphological features, and hydrological factors extracted from DTMs, DTA methods have been extended to include analyses of the structure of underlying strata, ocean surface features and even socioeconomic spatial structures. Third, DTMs have been applied to fields including global climate change, analysis of various typical regions, lunar surface and other related fields. Clearly, Chinese scholars have made significant progress in geomorphometry. Chinese scholars have had the greatest international impact in areas including high-fidelity digital terrain modelling and DTM-based regional geomorphological analysis, particularly in the Loess Plateau and the Tibetan Plateau regions.

IntroductionThe conceptual development of a Ceres Sample Return mission has intensified interest in the detailed topographic characterization of Occator Crater, a 92 km-wide impact crater on dwarf planet Ceres. This geologically young [1,2] crater hosts carbon-rich bright deposits [3,4,5] - Cerealia Facula and Vinalia Faculae - that are surface expressions of cryovolcanic processes linked to a ~40–50 km-deep brine reservoir [6,7]. These deposits contain a unique combination of sodium carbonates, ammonium chloride, and other hydrated salts [3,4,5] that were only recently exposed to the surface [2,3,8] and may preserve a record of past subsurface aqueous activity. Several Ceres landing site assessments [9] and mission concepts [10] have already considered Occator, with particular attention on these bright faculae as scientifically compelling targets. The success of such missions will depend on accurate, high-resolution Digital Terrain Models (DTMs) to enable safe landing, mobility, and efficient surface operations.Figure 1. Pan-sharpened RGB orthomisaic of Cerealia Facula [2].BackgroundTo support ongoing and future mission development efforts, we present a new set of high-resolution DTMs of Occator Crater and its interior faculae [11]. These were generated using stereophotogrammetric (SPG) and multi-view shape-from-shading (SfS) techniques applied to Dawn Framing Camera [12] (FC) data from multiple mission phases. The datasets include global coverage from the High and Low Altitude Mapping Orbit (HAMO, LAMO), as well as extremely high-resolution data from the highly elliptical XMO7 orbit acquired during Dawn’s second extended mission (XM2). This multitemporal, multi-geometry coverage forms the basis for precise terrain modeling at multiple spatial scales.MethodologyOur initial DTM products were derived using the USGS ISIS and NASA's ASP [13,14], generating terrain models at Ground Sample Distances (GSDs) of up to 17 m. The workflow incorporated radiometric correction, photometric normalization using Hapke parameters tailored to Ceres’ surface [15], manual tie-point generation for improved co-registration, bundle adjustment [16], and a careful exclusion of over-exposed images covering the faculae. ResultsAn important component of our study involved evaluating published DTMs of Occator Crater, including those produced by DLR [17] and JPL [18]. Our comparison demonstrated significant differences in effective resolution, vertical offsets, and absolute elevation, especially in the complex terrains of Cerealia and Vinalia Faculae. These findings underline the need for further investigation into the sources of these discrepancies, particularly with regard to co-registration accuracy, bundle adjustment stability, and the impact of surface albedo variations on photoclinometry. Our improved terrain models, are suitable for detailed analyses of surface slopes and terrain roughness - key parameters in landing site certification and mobility planning. As illustrated in Figures 2 and 3, Cerealia Facula exhibits highly variable slopes, with regions on and near Cerealia Tholus exceeding 30°, as well as rugged, fractured terrains that pose potential hazards. Only few regions of the surface exhibits slopes