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This research conducts a comparative analysis of the vertical accuracies of satellite-derived Digital Elevation Models (DEMs) in the Akure South Local Government Area, Ondo State, Nigeria. The DEMs assessed were obtained from three open-source satellite missions: Sentinel-1A, ALOS PALSAR, and TanDEM-X. The reference Ground Control Points (GCPs) used in the evaluations comprised 133 GCPs of 2nd and 3rd-order accuracy acquired from the Office of the Surveyor General, Ondo State, and through field surveys using the South Galaxy-1 Differential GPS. These obtained GCPs provided extensive coverage of the study area. The evaluation was undertaken based on the land cover, which was established by dividing the study area into open (built-up and bare land) and vegetation-covered (agricultural and forested) areas. The vertical accuracies of the satellite-based DEM collected within the study area were then compared and analyzed. The results revealed that Sentinel-1A and TanDEM-X were the most suitable in both open and vegetation-covered parts of the study area, with Sentinel-1A exhibiting the best performance. The effect of vegetation cover was mostly felt by ALOS PALSAR. Sentinel-1A and TanDEMX displayed commendable vertical accuracies, deemed highly suitable for applications in topographic mapping, as shown by an RMS of less than 2m. This research recommends the open-source satellite DEMs Sentinel-1A and TanDEM-X for planning and engineering applications because they offer the highest accuracy among their counterparts within Akure and its environs. [ABSTRACT FROM AUTHOR]

Image collection strategies and ground control points (GCPs) are of particular importance for uncrewed aerial vehicle combined with Structure‐from‐Motion (UAV–SfM) photogrammetry, and the generalization of their effects has proved elusive. This study designed various photogrammetric scenarios to investigate the effects of image collection strategies, ground control quantity, and their interaction on digital elevation model (DEM) errors and their spatial structure in high‐relief terrain. The results of 1.77 × 105 UAV–SfM scenarios provide insights for improving UAV–SfM practices. A high image capture angle (20–40°) enhances camera calibration quality decreasing the magnitude and spatial correlation of errors. High camera inclination reduces the sensitivity of mean and standard deviation of error to flying height but not the spatial correlation of error. Including additional data (e.g. supplemented convergent images; images captured at multiple flying heights) has only a minor effect if imagery is highly inclined. GCPs provide more effective constraints than image collection strategies. The mean error and standard error decline quickly with a small number of GCPs and then become stable in all scenarios, but the spatial correlation of error can be further improved with increasing GCPs. However, the effects of GCP quantity do interact with image collection strategies. High camera inclination reduces requirements for GCPs, whilst strategies combining different flying heights and image orientations have little effect on necessary GCP quantity. The distribution of GCPs still affects the errors, but the effect of GCP distribution becomes less important with an increase in the number of GCPs. Finally, we show that UAV–SfM photogrammetric quality assessment should routinely assess the spatial dependence of error using a statistic like Moran's I. [ABSTRACT FROM AUTHOR]

Geospatial data obtained using Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs) are increasingly used to model the terrain in the coastal zone, in particular in shallow waterbodies (with a depth of up to 1 m). In order to generate a terrain relief, it is important to choose a method for modelling that will allow it to be accurately projected. Therefore, the aim of this article is to present a method for accuracy assessment of topo-bathymetric surface models based on geospatial data recorded by UAV and USV vehicles. Bathymetric and photogrammetric measurements were carried out on the waterbody adjacent to the public beach in Gdynia (Poland) in 2022 using a DJI Phantom 4 RTK UAV and an AutoDron USV. The geospatial data integration process was performed in the Surfer software. As a result, Digital Terrain Models (DTMs) in the coastal zone were developed using the following terrain modelling methods: Inverse Distance to a Power (IDP), Inverse Distance Weighted (IDW), kriging, the Modified Shepard's Method (MSM) and Natural Neighbour Interpolation (NNI). The conducted study does not clearly indicate any of the methods, as the selection of the method is also affected by the visualization of the generated model. However, having compared the accuracy measures of the charts and models obtained, it was concluded that for this type of data, the kriging (linear model) method was the best. Very good results were also obtained for the NNI method. The lowest value of the Root Mean Square Error (RMSE) (0.030 m) and the lowest value of the Mean Absolute Error (MAE) (0.011 m) were noted for the GRID model interpolated with the kriging (linear model) method. Moreover, the NNI and kriging (linear model) methods obtained the highest coefficient of determination value (0.999). The NNI method has the lowest value of the R68 measure (0.009 m), while the lowest value of the R95 measure (0.033 m) was noted for the kriging (linear model) method. [ABSTRACT FROM AUTHOR]

Terrain models are widely used to depict the shape of the Earth's surface. With the development of photogrammetric methods, point cloud data have become one of the most popular data sources for terrain modelling. However, the obtained point clouds are of high density, which often increases redundancy rather than improving accuracy. Therefore, point cloud simplification should be a core component of terrain modelling. This paper proposes a point cloud simplification method by integrating topographic knowledge into terrain modelling (TKPCS). The method contains two steps: (1) topographic knowledge recognition and construction and (2) point cloud simplification using this topographic knowledge for terrain modelling. The proposed approach is benchmarked against improved versions of existing methods to validate its capability and accuracy in digital elevation model construction and terrain derivative extraction. The results show that the simplified points of the TKPCS method can generate finer resolution terrain models with higher accuracy and greater information entropy. The good performance of the TKPCS method is also stable at different scales. This work endeavours to transform perceptive topographic knowledge into a process of point cloud simplification and can benefit future research related to terrain modelling. [ABSTRACT FROM AUTHOR]

Geospatial data are increasingly used to model the terrain in the coastal zone, in particular in shallow waterbodies (with a depth of up to 1 m). In order to generate a terrain relief, it is important to choose a method for its modelling that will allow it to be accurately projected. Therefore, the aim of this publication is to analyze the terrain modelling methods in the coastal zone. For the purposes of the research, five most popular methods for terrain modelling were described: Inverse Distance Weighted (IDW), Modified Shepard's Method (MSM), Natural Neighbor Interpolation (NNI), kriging and spline. Each of the methods has been described in a uniform way in terms of: the essence of its operation, mathematical expression and application examples. The advantages and disadvantages of each of the methods for terrain modelling are also discussed. It should be stated that the choice of the method for the terrain modelling of a shallow waterbody is not unambiguous, as it depends on the type of data recorded during bathymetric and photogrammetric measurements. [ABSTRACT FROM AUTHOR]

Point clouds are widely used in Earth surface research but usually exhibit gaps of missing data. Previous point cloud restoration methods used in terrain modelling have not fully considered complex terrain characteristics, which can be summarised as the controlling role of topographic features in shaping terrain surfaces and the inherent similarities observed among these surfaces. This work introduces a novel method that integrates Topographic Features and Patch Matching (TFPM) into point cloud restoration processes for terrain modelling. The method mainly contains three steps. First, identifying gap boundary points. Second, topographic feature points are extracted and subsequently interpolated into the identified gaps. Third, searching other parts of the raw point cloud for patches resembling the gaps, and the identified patches are used as templates to restore the point cloud. The proposed method is benchmarked against three state-of-the-art point cloud restoration methods. The experimental results demonstrate that the TFPM method consistently exhibits superior accuracy in terrain modelling and analysis, as evidenced by low values of the root mean square error, average elevation difference, and average slope difference. This work endeavours to incorporate topographic features into point cloud restoration processes and can benefit future research related to terrain modelling and analysis. [ABSTRACT FROM AUTHOR]

Terrain is an essential part of any outdoor environment and, consequently, many techniques have appeared that deal with the problem of its automatic generation, such as procedural modeling. One form to create terrains is using noise functions because its low computational cost and its random result. However, the randomness of these functions also makes it difficult to have any control over the result obtained. In order to solve the problem of lack of control, this paper presents a new method noise-based that allows procedural terrains creation with elevation constraints (GPS routes, points of interest and areas of interest). For this, the method establishes the restrictions as fixed values in the heightmap function and creates a system of equations to obtain all points that they depend this restrictions. In this way, the terrain obtained maintains the random noise, but including the desired restrictions. The paper also includes how we apply this method on large terrain models without losing resolution or increasing the computational cost excessively. The results show that our method makes it possible to integrate this kind of constraints with high accuracy and realism while preserving the natural appearance of the procedural generation. [ABSTRACT FROM AUTHOR]

Featured Application: The presented approach can be implemented as an interactive tool for creating mesa and butte terrain features in modelling applications and game engines. Natural terrains created by long-term erosion processes can sometimes have spectacular forms and shapes. The visible form depends often upon internal geological structure and materials. One of the unique terrain artefacts occur in the form of table mountains and can be observed in the Monument Valley (Colorado Plateau, USA). In the following article a procedural method is considered for terrain modelling of structures, geometrically similar to the mesas and buttes hills. This method is not intended to simulate physically inspired erosion processes, but targets directly the generation of eroded forms. The results can be used as assets by artists and designers. The proposed terrain model is based on a height-field representation extended by materials and its hardness information. The starting point of the technique is the Poisson Faulting algorithm that was originally used to obtain fractional Brownian surfaces. In the modification, the step function as the fault line generator was replaced with a circular one. The obtained geometry was used for materials' classification and the hardness part of the modelled terrain. The final model was achieved by the erosive modification of geometry according to the materials and its hardness data. The results are similar to the structures observed in nature and are achieved within an acceptable time for real-time interactions. [ABSTRACT FROM AUTHOR]

In recent decades, terrain modelling and reconstruction techniques have increased research interest in precise short and long distance autonomous navigation, localisation and mapping within field robotics. One of the most challenging applications is in relation to autonomous planetary exploration using mobile robots. Rovers deployed to explore extraterrestrial surfaces are required to perceive and model the environment with little or no intervention from the ground station. Up to date, stereopsis represents the state-of-the art method and can achieve short-distance planetary surface modelling. However, future space missions will require scene reconstruction at greater distance, fidelity and feature complexity, potentially using other sensors like Light Detection And Ranging (LIDAR). LIDAR has been extensively exploited for target detection, identification, and depth estimation in terrestrial robotics, but is still under development to become a viable technology for space robotics. This paper will first review current methods for scene reconstruction and terrain modelling using cameras in planetary robotics and LIDARs in terrestrial robotics; then we will propose camera-LIDAR fusion as a feasible technique to overcome the limitations of either of these individual sensors for planetary exploration. A comprehensive analysis will be presented to demonstrate the advantages of camera-LIDAR fusion in terms of range, fidelity, accuracy and computation. [ABSTRACT FROM AUTHOR]

We introduce a compact hierarchical procedural model that combines feature-based primitives to describe complex terrains with varying level of detail. Our model is inspired by skeletal implicit surfaces and defines the terrain elevation function by using a construction tree. Leaves represent terrain features and they are generic parametrized skeletal primitives, such as mountains, ridges, valleys, rivers, lakes or roads. Inner nodes combine the leaves and subtrees by carving, blending or warping operators. The elevation of the terrain at a given point is evaluated by traversing the tree and by combining the contributions of the primitives. The definition of the tree leaves and operators guarantees that the resulting elevation function is Lipschitz, which speeds up the sphere tracing used to render the terrain. Our model is compact and allows for the creation of large terrains with a high level o detail using a reduced set of primitives. We show the creation of different kinds of landscapes and demonstrate that our model allows to efficiently control the shape and distribution of landform features. [ABSTRACT FROM AUTHOR]

Underground terrain poses a highly intricate and challenging environment to the propagation of waves carrying information from sensor to the sink nodes. Due to the complexity and level of detail, it is often difficult to realistically model such an environment for conducting tests. However, using numerical methods, the environment characteristics could be translated to a compatible framework, for testing complex networking models such as Wireless Underground Sensor Network (WUSN). Such transformation should lend the necessary clarity and simplicity required for effective problem analysis. In this paper, we demonstrate this possibility using the typical underground terrain environment for nut tree plantations, basing the field data on a full-fledged commercial pecan farm. The results shown are introductory to ongoing research on the effective use of such numerical methods for maximum power efficiency and bit rate for distributed WUSN, and optimum water usage in irrigation control. This paper forms a sequel to previous related research publications. [ABSTRACT FROM AUTHOR]

The article presents laboratory and field experiments that evaluate the sedimentological applications of close-range terrestrial laser scanning (TLS) to formulate protocol for data collection and processing. It reveals the conduct of controlled laboratory experiments to formulate the errors of simple geometrical objects in TLS data and the development of a workflow to generate the digital terrain models (DTMs) of the fluvial gravel surfaces in River Feshie, Scotland. It says that the inherent errors in scanner ad the errors caused by the interaction of laser footprint and surface geometry dominate the fluvial gravel TLS data. It reveals that the method can be use in understanding multiple aspects of fluvial system and other non-fluvial situations that require high-resolution surface data.

In recent years in India, deregulation has opened the telecommunications market up to new arenas putting pressure on existing organizations to become more efficient. New technologies such as fibre optic cables, efficient terrestrial broadcasting and satellites are offering greatly increased bandwidth. However, the ever-increasing demand to provide low-cost and large area coverage with high reception quality has forced these industries to explore advanced optimization strategies for their network planning. The telecommunications companies have begun to recognize that many of their work practices have spatial elements and data can be used more efficiently. In the present study, a planning strategy for establishing a network of towers for the purpose of mobile communications using remote sensing and raster GIS is demonstrated. In particular, this study addresses how to develop a surface model using IRS-1C PAN stereo pair. This information derived from the satellite data was integrated with raster GIS GRID modelling. The study clearly demonstrates that the IRS data could be utilized for planning a suitable network of towers for telecom applications. [ABSTRACT FROM AUTHOR]

The aim of the study was to examine how robust soil-terrain models are to uncertainty in the source elevation data. The study site was a 74 ha agricultural field in Australia. A global positioning system was used to measure elevation and the uncertainty of the measurement, therefore allowing maps of elevation and its uncertainty to be created. Monte-Carlo simulation with a modified version of Latin Hypercube Sampling was used to create 100 realizations of a slope map. Clay content was measured at 111 sites, and kriging with external drift was used to map clay content where each slope realization was used as a secondary information source. Maps of the mean and standard deviation of clay content across all realizations were created. The standard deviations of clay content were generally small ( -1 ) and in most parts of the field less than the analytical accuracy of the hydrometer method which was used to measure soil-clay content in the laboratory. The values in the map of elevation uncertainty were multiplied by 5 and the entire error propagation process was repeated to create a second set of 100 realizations of the clay content. The ratio of the uncertainty in the original DEM was 5:1 when compared with that in the perturbed DEM, i.e. it was multiplied by 5. The ratio between the standard deviation in the two clay-content maps was 3.79:1, which indicates a reduction in uncertainty through the modelling process. The results showed that the soil-terrain model performs well for the study area, and it is not very sensitive to DEM errors. We conclude that input uncertainty tests as shown in this study should accompany soil mapping studies where secondary information is used in the prediction mdoel. [ABSTRACT FROM AUTHOR]