Terrain Visualization Research Articles

Adaptive Color Transfer From Images to Terrain Visualizations.

Terrain mapping is not only dedicated to communicating how high or steep a landscape is but can also help to indicate how we feel about a place. However, crafting effective and expressive elevation colors is challenging for both nonexperts and experts. In this article, we present a two-step image-to-terrain color transfer method that can transfer color from arbitrary images to diverse terrain models. First, we present a new image color organization method that organizes discrete, irregular image colors into a continuous, regular color grid that facilitates a series of color operations, such as local and global searching, categorical color selection and sequential color interpolation. Second, we quantify a series of cartographic concerns about elevation color crafting, such as the "lower, higher" principle, color conventions, and aerial perspectives. We also define color similarity between images and terrain visualizations with aesthetic quality. We then mathematically formulate image-to-terrain color transfer as a dual-objective optimization problem and offer a heuristic searching method to solve the problem. Finally, we compare elevation colors from our method with a standard color scheme and a representative color scale generation tool based on four test terrains. The evaluations show that the elevation colors from the proposed method are most effective and that our results are visually favorable. We also showcase that our method can transfer emotion from images to terrain visualizations.

Edge-protected IDW-based DEM detail enhancement and 3D terrain visualization

Terrain visualization plays an important role in Digital Twin, geology, environmental science, and exploration. Generating 3D visualization results by the Digital Elevation Model (DEM) is an effective method. However, existing DEM 3D visualization methods generally lack sufficient detail to obtain good visual effects. Therefore, we propose a novel DEM detail enhancement and 3D terrain visualization method. Our method is based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm and the edge-protected Inverse Distance Weighted (IDW) algorithm, and achieves 3D visualization of DEM data through a workflow of converting the raw DEM data into an image, followed by enhancement and detail optimization of the image, and finally converting the image into triangular meshes. The edge-protected IDW algorithm performs IDW interpolation optimization based on the Canny edge detector combined with the Otsu threshold optimization method to detect edge areas, achieving smooth transitions in the edge areas. Experiments show that our method generates detail-rich 3D visualization results after enhancing original DEM data. We also conducted an ablation study to provide a side-by-side comparison of each step. Our method can be further applied to many tasks, such as virtual reality, GIS, and geological exploration.

Large-Scale 3D Terrain Reconstruction Using 3D Gaussian Splatting for Visualization and Simulation

Abstract. The fusion of low-cost unmanned aerial systems (UAS) with advanced photogrammetric techniques has revolutionized 3D terrain reconstruction, enabling the automated creation of detailed models. Concurrently, the advent of 3D Gaussian Splatting has introduced a paradigm shift in 3D data representation, offering visually realistic renditions distinct from traditional polygon-based models. Our research builds upon this foundation, aiming to integrate Gaussian Splatting into interactive simulations for immersive virtual environments. We address challenges such as collision detection by adopting a hybrid approach, combining Gaussian Splatting with photogrammetry-derived meshes. Through comprehensive experimentation covering varying terrain sizes and Gaussian densities, we evaluate scalability, performance, and limitations. Our findings contribute to advancing the use of advanced computer graphics techniques for enhanced 3D terrain visualization and simulation.

An efficient method for modeling and evaluating the bench terrain of open-pit mines

In order to quantitatively analyze the roughness of the bench floor during open-pit mine blasting, this study proposes a real-time measuring method for the three-dimensional terrain of the bench floor during the excavation process. Real-time monitoring is conducted at the boundary and discrete internal points of the workbench floor during electric shovel operation, utilizing real-time kinematic global navigation satellite system (RTK-GNSS) positioning technology. An improved convex hull algorithm is introduced to automatically extract the optimal boundary of discrete point clouds based on their spatial distribution characteristics. This study establishes a digital elevation model (DEM) using five interpolation algorithms for 3D terrain visualization simulation. Through cross-validation, a comparative analysis of the DEM accuracy, the simulation results of the ordinary kriging interpolation algorithm were found to be optimized. The optimized interpolation algorithm is applied to simulate the 3D terrain in the Dexing open-pit copper mine, and the relevant terrain parameters were calculated. This dataset can serve as a precise foundation for the real-time path planning of elevation blasting design and ground leveling operations.

Delaunay Triangulation in the Big Data Landscape: A Parallel Optimization Approach

Abstract In the era of big data, from digital cities to digital earth, the exponential growth of spatial information due to the development of diverse data collection technologies has been a significant concern. Delaunay triangulation has garnered widespread attention and application in geomorphological analysis, topographic simulation, and cartographic synthesis due to its minimal data redundancy and excellent stability. However, as the application fields of Delaunay triangular mesh models continue to expand and application requirements deepen, especially with the urgent need to address real-time large-scale scene rendering and terrain visualization, the efficiency, accuracy, and stability of Delaunay triangulation meshes are increasingly demanded. This paper proposes a parallel optimization algorithm based on the insertion point method, following an analysis of the traditional insertion point method, and demonstrates its effectiveness through a series of experiments.

Exploring the Influence of Input Feature Space on CNN‐Based Geomorphic Feature Extraction From Digital Terrain Data

AbstractMany studies of Earth surface processes and landscape evolution rely on having accurate and extensive data sets of surficial geologic units and landforms. Automated extraction of geomorphic features using deep learning provides an objective way to consistently map landforms over large spatial extents. However, there is no consensus on the optimal input feature space for such analyses. We explore the impact of input feature space for extracting geomorphic features from land surface parameters (LSPs) derived from digital terrain models (DTMs) using convolutional neural network (CNN)‐based semantic segmentation deep learning. We compare four input feature space configurations: (a) a three‐layer composite consisting of a topographic position index (TPI) calculated using a 50 m radius circular window, square root of topographic slope, and TPI calculated using an annulus with a 2 m inner radius and 10 m outer radius, (b) a single illuminating position hillshade, (c) a multidirectional hillshade, and (d) a slopeshade. We test each feature space input using three deep learning algorithms and four use cases: two with natural features and two with anthropogenic features. The three‐layer composite generally provided lower overall losses for the training samples, a higher F1‐score for the withheld validation data, and better performance for generalizing to withheld testing data from a new geographic extent. Results suggest that CNN‐based deep learning for mapping geomorphic features or landforms from LSPs is sensitive to input feature space. Given the large number of LSPs that can be derived from DTM data and the variety of geomorphic mapping tasks that can be undertaken using CNN‐based methods, we argue that additional research focused on feature space considerations is needed and suggest future research directions. We also suggest that the three‐layer composite implemented here can offer better performance in comparison to using hillshades or other common terrain visualization surfaces and is, thus, worth considering for different mapping and feature extraction tasks.

Construction of 3D Design Model of Urban Public Space Based on ArcGIS Water System Terrain Visualization Data

On the premise of being familiar with ArcGIS Server technology, we build the architecture of the entire platform, including the basic support layer, data layer, service platform layer, and application layer, and build the entire environment of the platform. We make electronic maps through Arc Map, and collect, organize, and improve spatial data and attribute data, so as to achieve satisfactory accuracy and visual comfort. This study implements various map services under the Dojo framework, including basic map operations, information display and query, marker points, eagle eye diagrams, measurement, printing, and other functions, and uses JavaScript technology to improve user experience. We publish various services through ArcGIS Server, and realize fast and error-free invocation of each service. Based on the theory of runoff and runoff, ArcGIS software was used to study the hydrological information of the watershed, and to determine the catchment area threshold and hydrological response unit. Combined with the GIS spatial analysis method, the numerical simulation of rainfall and runoff in the study case area was carried out, and the variation of the annual rainfall-runoff coefficient was obtained. This study selects an area where stock planning was first proposed as the object of this research. Briefly, we introduce the construction of three-dimensional public space in a certain area, select thirteen typical three-dimensional public spaces as representatives for public evaluation, and explore their existing problems, mainly including the lack of adaptability of space functions and the lack of diversity in space design, privatization of operation management, low level of public perception, etc. Since then, in response to the public problems of the three-dimensional public space in a certain area, a targeted three-dimensional public space optimization strategy is proposed from the four levels of planning policy, urban design, management subject, and user subject.

A Method for Digital Terrain Reconstruction Using Longitudinal Control Lines and Sparse Measured Cross Sections

Using longitudinal control lines and sparse measured cross sections with large spaces, a new method for quickly reconstructing digital terrains in natural riverways is presented. The longitudinal control lines in a natural riverway, mainly including the river boundaries, the thalweg, the dividing lines of floodplains and main channel, and the water edges, can be obtained by interpreting satellite images, remote sensing images or site surveys. Then, the longitudinal control lines are introduced into quadrilateral grid generation as auxiliary lines that can control longitudinal riverway trends and reflect transverse terrain changes. Then, by the equal cross-sectional area principle at the same water level, all measured cross sections are reasonably fitted. On the above basis, by virtue of the fitted cross-sectional data and the weighted distance method, the terrain interpolations along the longitudinal grid lines are conducted to obtain the elevation data of all grid nodes. Finally, according to the readable text formats of MIKE21 and SMS, the gridded digital terrain and connection information are output by computer programming to achieve good construction of the data exchange channels and fully exploit the special advantages of various software programs for digital terrain visualization and further utilization.

Terrain visualization information integration in agent-based military industrial logistics simulation

Agent-based simulation has become a useful tool in describing military industrial logistics organization behavior to implement military industrial information integration. Considering the specific demands of virtual engagement terrain design, this study present a framework for terrain visualization information integration in agent-based military industrial logistics simulation, which consists of perception access layer, data layer, service layer, and application layer. Focusing on its data source and the data analysis, processing, use, and validation, we propose a novel design approach on an engagement terrain database system for agent-based military industrial logistics simulation, and provide resolutions to actual problems, such as real-time efficient accession of the agent-based simulation system to high-resolution terrain data, management and maintenance of large-scale terrain data, and integrated visual simulation of terrain data. Such an initiative is achieved by presenting specific methods on the data and model designs for terrain relation, terrain analysis application, and terrain texture in terrain visualization application. A case study of the agent-based military industrial logistics simulation verifies the feasibility and effectiveness of the approach.

Risk Management of Community Sports Based on AI Technology

With the progress of the times, China’s economy, politics and culture are developing rapidly. Today’s sports life is rich and colorful. People gradually realize that sports activities play a positive role in people’s health. Therefore, with the development of mass sports healthy lifestyle and AI technology, sports community risk management has become increasingly important. The purpose of this paper is to study the risk management of sports community based on AI technology. This paper uses the related technologies of emergency virtual scene construction, including three-dimensional terrain visualization technology based on terra Vista and global mapper software, and static object simulation modeling technology based on creator software. This paper puts forward the method of list sort, risk matrix, Pareto analysis and mathematical statistics. This paper discusses and deeply analyzes the related concepts of risk management in sports community and puts forward solutions. Finally, it adopts a variety of forms of expression, and presents its trend chart intuitively to users. The experimental study shows that human and site factors account for about 20% of the risk factors, and social factors account for the least, accounting for 6.56%. The severity index of self action completion and management efficiency reached 4.62 and 4.84 respectively. The maximum probability index of the impact of management efficiency on the occurrence of accidents reached 4.57.

Combined Detection and Segmentation of Archeological Structures from LiDAR Data Using a Deep Learning Approach

Until recently, archeological prospection using LiDAR data was based mainly on expert-based and time-consuming visual analyses. Currently, deep learning convolutional neural networks (deep CNN) are showing potential for automatic detection of objects in many fields of application, including cultural heritage. However, these computer-vision based algorithms remain strongly restricted by the large number of samples required to train models and the need to define target classes before using the models. Moreover, the methods used to date for archaeological prospection are limited to detecting objects and cannot (semi-)automatically characterize the structures of interest. In this study, we assess the contribution of deep learning methods for detecting and characterizing archeological structures by performing object segmentation using a deep CNN approach with transfer learning. The approach was applied to a terrain visualization image derived from airborne LiDAR data within a 200 km² area in Brittany, France. Our study reveals that the approach can accurately (semi-)automatically detect, delineate, and characterize topographic anomalies, and thus provides an effective tool to inventory many archaeological structures. These results provide new perspectives for large-scale archaeological mapping.

Elevation models for reproducible evaluation of terrain representation

ABSTRACT This paper proposes elevation models to promote, evaluate, and compare various terrain representation techniques. Our goal is to increase the reproducibility of terrain rendering algorithms and techniques across different scales and landscapes. We introduce elevation models of varying terrain types, available to the user at no cost, with minimal common data imperfections such as missing data values, resampling artifacts, and seams. Three multiscale elevation models are available, each consisting of a set of elevation grids, centered on the same geographic location, with increasing cell sizes and spatial extents. We also propose a collection of single-scale elevation models of archetypal landforms including folded ridges, a braided riverbed, active and stabilized sand dunes, and a volcanic caldera. An inventory of 78 publications with a total of 155 renderings illustrating terrain visualization techniques guided the selection of landform types in the elevation models. The benefits of using the proposed elevation models include straightforward comparison of terrain representation methods across different publications and better documentation of the source data, which increases the reproducibility of terrain representations.

Avalanche hazard mitigation in east Karakoram mountains

Karakoram mountains range in north-western part of Himalayas is about 500 km in length and hosts some of the world’s highest peaks and longest glaciers. It is characterized by steep slopes and polar climate. Snowfall and avalanches are observed almost throughout the year. Many lives have been lost in the past in these mountains due to avalanches. This study focuses on avalanche hazard mitigation work undertaken in eastern part of Karakoram mountains, a complex of glaciers including Siachen and other connected glaciers on the eastern side of Saltoro Ridge. From the forecasting point of view, the snowpack on the slopes of Karakoram mountains almost always has unstable layers and hence continual avalanche threat exists. The structural mitigation measures are infeasible due to steep, unstable and glaciated terrain. The method of slope stabilization by preventive triggering of small avalanches holds promise but necessary infrastructure is difficult to install and maintain. Consequently, the effective avalanche hazard mitigation in the area is a challenging task. The paper describes the general terrain, climatological and avalanche characteristics of the area. Further, it elaborates the infrastructure set up, various tools and products developed to assist the avalanche practitioners in organizing safe camping and movements in the area particularly the snow-meteorological observatory network, weather modelling products, avalanche forecasting models, terrain visualization tools, hazard mapping and risk analysis, and experiences of preventive triggering of avalanches.

An Overview about Research on 3D Visualization Technology of Geographic Information Based on Computer Software Development

Geographic Information System (GIS) is an important system of three-dimensional (3D) real-time interactive visualization platform. 3D visualization technology is to display the information to be expressed by a visual effect. The introduction of 3D visualization technology into GIS is a reform of the form of information expression, which can solve the limitation of using graphic symbols to express the 3D space world on a 2D plane. However, most of the visualizations in GIS focus on the 3D terrain visualization based on the surface model, which does not involve the volume visualization of spatial volume data. An overview about visualization technology for geographic information based on computer software is given here, to encourage further development.

Geospatial Virtual Reality for Cyberlearning in the Field of Topographic Surveying: Moving Towards a Cost-Effective Mobile Solution

In spite of the tremendous success in artificial intelligence technology and a high level of automation in geospatial data obtaining processes, there is still a need for topographical field data collection by professional surveyors. Understanding terrain topology and topography is a cognitive skill set that has to be demonstrated by geospatial Subject Matter Experts (SME) for the productive work in the topographic surveying field. For training of the mentioned above skillset, one has to be exposed to the theory and must also practice with surveying instruments in field conditions. The challenge of any surveying/geospatial engineering workforce training is to expose students to field conditions which might be limited due to equipment expenses and meteorological conditions that prevent good data collection. To meet this challenge, the Integrated Geospatial Technology research group is working on a geospatial virtual reality (VR) project which encompasses the following components: (a) immersive visualization of terrain; (b) virtual total station instrument; (c) virtual surveyor with reflector installed on the virtual rod. The application scenario of the technology we are working with has the following stages: (1) student is installing total station on the optimal location; (2) students move virtual surveyor on the sampling points they consider to be important (3) contours are generated and displayed in 3D being superimposed on 3D terrain; (4) accuracy of terrain modeling is observable and measurable by comparing the sampling model with initial one.

Terrain Analysis in Google Earth Engine: A Method Adapted for High-Performance Global-Scale Analysis

Terrain analysis is an important tool for modeling environmental systems. Aiming to use the cloud-based computing capabilities of Google Earth Engine (GEE), we customized an algorithm for calculating terrain attributes, such as slope, aspect, and curvatures, for different resolution and geographical extents. The calculation method is based on geometry and elevation values estimated within a 3 × 3 spheroidal window, and it does not rely on projected elevation data. Thus, partial derivatives of terrain are calculated considering the great circle distances of reference nodes of the topographic surface. The algorithm was developed using the JavaScript programming interface of the online code editor of GEE and can be loaded as a custom package. The algorithm also provides an additional feature for making the visualization of terrain maps with a dynamic legend scale, which is useful for mapping different extents: from local to global. We compared the consistency of the proposed method with an available but limited terrain analysis tool of GEE, which resulted in a correlation of 0.89 and 0.96 for aspect and slope over a near-global scale, respectively. In addition to this, we compared the slope, aspect, horizontal, and vertical curvature of a reference site (Mount Ararat) to their equivalent attributes estimated on the System for Automated Geospatial Analysis (SAGA), which achieved a correlation between 0.96 and 0.98. The visual correspondence of TAGEE and SAGA confirms its potential for terrain analysis. The proposed algorithm can be useful for making terrain analysis scalable and adapted to customized needs, benefiting from the high-performance interface of GEE.

Continuous-Scale 3D Terrain Visualization Based on a Detail-Increment Model

Triangulated irregular networks (TINs) are widely used in terrain visualization due to their accuracy and efficiency. However, the conventional algorithm for multi-scale terrain rendering, based on TIN, has many problems, such as data redundancy and discontinuities in scale transition. To solve these issues, a method based on a detail-increment model for the construction of a continuous-scale hierarchical terrain model is proposed. First, using the algorithm of edge collapse, based on a quadric error metric (QEM), a complex terrain base model is processed to a most simplified model version. Edge collapse records at different scales are stored as compressed incremental information in order to make the rendering as simple as possible. Then, the detail-increment hierarchical terrain model is built using the incremental information and the most simplified model version. Finally, the square root of the mean minimum quadric error (MMQE), calculated by the points at each scale, is considered the smallest visible object (SVO) threshold that allows for the scale transition with the required scale or the visual range. A point cloud from Yanzhi island is converted into a hierarchical TIN model to verify the effectiveness of the proposed method. The results show that the method has low data redundancy, and no error existed in the topology. It can therefore meet the basic requirements of hierarchical visualization.

A fast quadtree‐based terrain crack locating method that accounts for adjacency relationships

AbstractThe repair of terrain cracks is an important process in multi‐resolution three‐dimensional terrain visualization, and rapid and accurate pinpointing of cracks between terrain blocks is of the utmost importance for this process. The existing quadtree‐based crack locating methods are generally slow and inefficient, as they require the traversal of terrain quadtrees to locate terrain cracks. In this research, we propose a fast quadtree‐based terrain crack locating method that accounts for adjacency information. First, terrain quadtrees are constructed that contain information regarding adjacency relationships. Second, dynamic updating is performed for terrain quadtrees and their adjacency information. Finally, terrain cracks are located by using the adjacencies of the quadtree nodes. This proposed method was experimentally validated via the terrain data of a mountainous region in Sichuan Province. The experimental results indicate that the proposed method can be used to efficiently and accurately locate terrain cracks with a strong performance in practical applications.

Practice of a GIS education program for junior and senior high school students

Abstract. We conducted a GIS (Geographic Information Science) education program for junior and senior high school students in August 2018. This program was designed so that students can learn basic knowledge of GIS and methods of mapping within a day. In this program, we firstly lectured the history of maps and various utilizations using GIS. After the lecture, students exercised mapping and spatial analysis by operating QGIS and free open data. The exercise included spatial analysis using DEMs (Digital Elevation Models) such as terrain visualization based on elevation values, slope calculation, and contour line creation.At the end of the exercise, we conducted a questionnaire survey to understand how the students evaluated the difficulty, understanding and satisfactory levels of the lecture and the exercise, as well as their PC operating skills. They answered each item by selecting one from five levels.The answers of the students show that most of them enjoyed both the lecture and the exercise. They tended to feel some difficulties with the materials, but their understanding and satisfactory levels were relatively high. Almost all students who found high difficulty in the program had low PC operating skills, indicating that the lack of the skills led to limited understanding of technical terms such as the desktop and folders.

Hardware-Based Adaptive Terrain Mesh Using Temporal Coherence for Real-Time Landscape Visualization

In general, changes in society or the environment are expected depending on changes in terrain. The faster and more accurately these terrain changes can be observed, the faster and more accurately predictions can be made. Recently, three-dimensional (3D) terrain visualization programs, such as flight simulation, allow for interaction with various datasets to predict ecosystem influences in real time. Elaborate terrain data require a very large capacity. To render these large terrain data, the computing power of graphics devices cannot always satisfy the real-time conditions. Consequently, a large number of graphics devices in computing systems need to be replaced on a periodic basis. As the industry evolves, the replacement cycle of graphic devices shortens. To solve this problem, we present a novel acceleration approach for generating an adaptive terrain mesh using temporal coherence. By using our method, it is possible to prevent artifacts such as frame drop or screen flickering due to lack of computing power of the GPU in a specific viewing condition. Instead of generating the new terrain mesh on every frame, our method reuses the detail level of terrain mesh that was used in a previous frame. Therefore, it can maintain the frame coherency and improve the rendering speed. This allows the proposed method to more quickly provide more detailed information about the terrain to predict environmental changes more accurately on existing equipment. Thus, the proposed method can reduce the need to frequently replace GPUs. The proposed method can guarantee sufficient performance even with a resilient graphic device and can effectively slow down the replacement period of existing equipment.