Three-dimensional Terrain Research Articles

Path planning of plant protection UAV based on improved A* algorithm under wind conditions

In order to improve safety and reduce energy consumption, a path planning method for the transition of plant protection unmanned aerial vehicles (UAVs) in mountainous and hilly terrain between different plots based on improved A* algorithm was proposed. According to the height of three-dimensional terrain information, a raster voxel map was built. The search space was determined by assigning weights to each grid. The wind cost was introduced into the actual cost function to improve the algorithm. Different weight parameters were set for distance cost and wind cost. Simulation experiments were carried out in the fixed wind field and the variable wind field respectively to obtain the track length and flight time of path planning. The simulation results showed that compared with the classic A* algorithm, the improved A* algorithm could save 9.76%, 7.22% and 11.4% in trajectory, energy and time at the maximum under the condition of fixed wind. Under the condition of variable wind field, the maximum trajectory, energy and time saving percentage was 27.6%, 33.1% and 26.2% respectively compared with the classic A* algorithm. The proposed algorithm could effectively plan a safe and reliable three-dimensional flight path, which provided an effective method for better application of plant protection UAVs in complex hilly terrain. Keywords: A* algorithm; Path-planning; wind vector DOI: 10.33440/j.ijpaa.20200304.125 Citation: Sun G H, Fang X F, Zhu L C, Yuan Y W, Zhao B, Han Z H. Path planning of plant protection UAV based on improved A* algorithm under wind conditions. Int J Precis Agric Aviat, 2020; 3(4): 31–38.

Assessing Different Feature Sets’ Effects on Land Cover Classification in Complex Surface-Mined Landscapes by ZiYuan-3 Satellite Imagery

Land cover classification (LCC) in complex surface-mined landscapes has become very important for understanding the influence of mining activities on the regional geo-environment. There are three characteristics of complex surface-mined areas limiting LCC: significant three-dimensional terrain, strong temporal-spatial variability of surface cover, and spectral-spatial homogeneity. Thus, determining effective feature sets are very important as input dataset to improve detailed extent of classification schemes and classification accuracy. In this study, data such as various feature sets derived from ZiYuan-3 stereo satellite imagery, a feature subset resulting from a feature selection (FS) procedure, training data polygons, and test sample sets were firstly obtained; then, feature sets’ effects on classification accuracy was assessed based on different feature set combination schemes, a FS procedure, and random forest algorithm. The following conclusions were drawn. (1) The importance of feature set could be divided into three grades: the vegetation index (VI), principal component bands (PCs), mean filters (Mean), standard deviation filters (StDev), texture measures (Textures), and topographic variables (TVs) were important; the Gaussian low-pass filters (GLP) was just positive; and none were useless. The descending order of their importance was TVs, StDev, Textures, Mean, PCs, VI, and GLP. (2) TVs and StDev both significantly outperformed VI, PCs, GLP, and Mean; Mean outperformed GLP; all other pairs of feature sets had no difference. In general, the study assessed different feature sets’ effects on LCC in complex surface-mined landscapes.

A Review of Fine-Scale Land Use and Land Cover Classification in Open-Pit Mining Areas by Remote Sensing Techniques

Over recent decades, fine-scale land use and land cover classification in open-pit mine areas (LCCMA) has become very important for understanding the influence of mining activities on the regional geo-environment, and for environmental impact assessment procedure. This research reviews advances in fine-scale LCCMA from the following aspects. Firstly, it analyzes and proposes classification thematic resolution for LCCMA. Secondly, remote sensing data sources, features, feature selection methods, and classification algorithms for LCCMA are summarized. Thirdly, three major factors that affect LCCMA are discussed: significant three-dimensional terrain features, strong LCCMA feature variability, and homogeneity of spectral-spatial features. Correspondingly, three key scientific issues that limit the accuracy of LCCMA are presented. Finally, several future research directions are discussed: (1) unitization of new sensors, particularly those with stereo survey ability; (2) procurement of sensitive features by new sensors and combinations of sensitive features using novel feature selection methods; (3) development of robust and self-adjusted classification algorithms, such as ensemble learning and deep learning for LCCMA; and (4) application of fine-scale mining information for regularity and management of mines.

Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods

Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC) information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of mixed pixels. This study aimed to integrate pixel unmixing and decision tree to improve LULC classification by removing mixed pixel influence. The abundance and minimum noise fraction (MNF) results that were obtained from mixed pixel decomposition were added to decision tree multi-features using a three-dimensional (3D) Terrain model, which was created using an image fusion digital elevation model (DEM), to select training samples (ROIs), and improve ROI separability. A Landsat-8 OLI image of the Yunlong Reservoir Basin in Kunming was used to test this proposed method. Study results showed that the Kappa coefficient and the overall accuracy of integrated pixel unmixing and decision tree method increased by 0.093% and 10%, respectively, as compared with the original decision tree method. This proposed method could effectively eliminate the influence of mixed pixels and improve the accuracy in complex LULC classifications.

A Study on New Virtual Reality System in Maze Terrain

ABSTRACTThis study proposes the maze virtual reality (MVR) system, which is designed to provide new immersive virtual reality (VR) experiences by generating a maze and an event-based maze environment. The MVR system consists of a maze generation technique based on mazemap, which we additionally propose for the automatic generation of diverse maze patterns, event-enhancing immersion, reducing VR sickness, and interactions. First, we present a finite algorithm that automatically generates diverse maze patterns from the user perspective and implements mazemap for automated three-dimensional (3D) terrain generation from a 2D maze pattern. Then, we present optimized events for the maze environment by providing users with deeper immersion and minimized VR sickness. The design procedure is divided into two elements: an automatic structure for arranging predefined events based on maze pattern analysis and a manual operation module. In addition, a Leap Motion-based interactive scheme is implemented for deeper immersion when the user moves in a limited space, while improving object control. Finally, experiments were conducted to analyze user satisfaction with the MVR system, the psychological impact of the continuous mazemap input, and the effects of the event-based environment on immersion enhancement and VR sickness reduction.

Three-dimensional terrain elevation in airborne interferometric frequency-domain radar

This paper is devoted to the method for a three-dimensional radar image restoration of terrain elevations using airborne two antenna interferometric frequency-domain radar. A method’s main feature is the parallel obtaining of two-dimensional frequencydomain spectra both of radar terrain echo and its derivative for next synthesizing. The architecture of such interferometric radar is proposed, and math equations for one’s performance calculation are presented. The numerical algorithm for the terrain elevations calculation over an arbitrary horizontal plane is developed.

Optimal Planning of WSN Deployments for <italic>In Situ</italic> Lunar Surveys

Wireless sensor network deployments for in situ lunar surveys will be subject to a random scattering of sensors, resulting in random network connectivity and coverage. Models reflecting this property, as well as the three-dimensional terrain, lifetime, and mass constraints of the mission, are introduced. From them, an optimization problem solved with simulated annealing is defined, enabling selection of the best deployment configuration in order to characterize water distribution in the scenario recently described by Klima et al. in the Bullialdus Crater on the Moon.

Fuzzy Behavior-Based Online Command Generation for Unmanned Aircraft Guidance in Rough Terrain Environments

AbstractThis research is aimed at developing an efficient online path planner for unmanned air vehicle guidance in completely unknown three-dimensional (3D) rough terrain environments. A novel algo...

Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data: a case study in the Sierra Nevada Mountains, California

ABSTRACTImproved monitoring and understanding of tree growth and its responses to controlling factors are important for tree growth modeling. Airborne Laser Scanning (ALS) can be used to enhance the efficiency and accuracy of large-scale forest surveys in delineating three-dimensional forest structures and under-canopy terrains. This study proposed an ALS-based framework to quantify tree growth and competition. Bi-temporal ALS data were used to quantify tree growth in height (ΔH), crown area (ΔA), crown volume (ΔV), and tree competition for 114,000 individual trees in two conifer-dominant Sierra Nevada forests. We analyzed the correlations between tree growth attributes and controlling factors (i.e. tree sizes, competition, forest structure, and topographic parameters) at multiple levels. At the individual tree level, ΔH had no consistent correlations with controlling factors, ΔA and ΔV were positively related to original tree sizes (R > 0.3) and negatively related to competition indices (R < −0.3). At the forest-stand level, ΔH and ΔA were highly correlated to topographic wetness index (|R| > 0.7), ΔV was positively related to original tree sizes (|R| > 0.8). Multivariate regression models were simulated at individual tree level for ΔH, ΔA, and ΔV with the R2 ranged from 0.1 to 0.43. The ALS-based tree height estimation and growth analysis results were consistent with field measurements.

The Sensitivity of Orographic Precipitation to Flow Direction: An Idealized Modeling Approach

Abstract A major question regarding orographic precipitation is its sensitivity to flow direction, with some research suggesting substantial sensitivity. To examine this issue, this paper describes a full physics model with realistic three-dimensional terrain that is forced by a single input sounding. This system is used to investigate the sensitivity of orographic precipitation to wind direction over the Pacific Northwest for conditions approximating an atmospheric river. The model results show considerable modulation of regional precipitation as flow direction changes, with results for four Washington State river drainages agreeing well with previous observational studies. It is shown that precipitation amounts over such drainages can vary substantially with very small changes in the direction of the incoming flow. To explore the origin of directional sensitivity of precipitation over the Olympic Mountains of western Washington State, additional experiments were carried out using modified terrain fields with smoothed or idealized Olympic Mountains, or with nearby orography removed. These simulations suggest that the sensitivity of Olympic Mountain precipitation to wind direction is more strongly modulated by the presence of surrounding orography than by the specific geometry of the Olympic Mountains.

Establishment and application of three-dimensional realistic river terrain in the numerical modeling of flow over spillways

AbstractWe present an integrated three-dimensional (3D) spillway model where the realistic and complicated river terrain is implemented by the platform CATIA (Computer Aided Three Dimensional Interactive Application). This integrated 3D spillway model allows for complicated topographic and geomorphic conditions and describes the spatial distribution of the spillway dam (upstream reservoir, downstream river channel and the spillway dam itself) precisely, thus making it a real alternative to the physical model. Furthermore, this model provides the premise and possibility of a full-scale simulation of the spillway flow, that is, it can not only be used to study the hydraulics on the spillway face, but also can be used to study the hydraulics along the downstream river channel and estimate the scour problem associated with both the spillway flow and downstream river channel. In this model, turbulence was simulated using RNG k−ɛ equations. The flow velocity and surface pressure from the numerical model were verified by the data from experiments. Moreover, the river flow was studied and flow velocities downstream were obtained. The scour formed downstream of a ski-jump was also studied in this study on the location and shape of a scour hole. In all, this study provides new approaches for solving relevant hydraulic engineering problems.

Climbing favours the tripod gait over alternative faster insect gaits

To escape danger or catch prey, running vertebrates rely on dynamic gaits with minimal ground contact. By contrast, most insects use a tripod gait that maintains at least three legs on the ground at any given time. One prevailing hypothesis for this difference in fast locomotor strategies is that tripod locomotion allows insects to rapidly navigate three-dimensional terrain. To test this, we computationally discovered fast locomotor gaits for a model based on Drosophila melanogaster. Indeed, the tripod gait emerges to the exclusion of many other possible gaits when optimizing fast upward climbing with leg adhesion. By contrast, novel two-legged bipod gaits are fastest on flat terrain without adhesion in the model and in a hexapod robot. Intriguingly, when adhesive leg structures in real Drosophila are covered, animals exhibit atypical bipod-like leg coordination. We propose that the requirement to climb vertical terrain may drive the prevalence of the tripod gait over faster alternative gaits with minimal ground contact.

Visualizing 3D Terrain, Geo-Spatial Data, and Uncertainty

Visualizing geo-spatial data embedded into a three-dimensional terrain is challenging. The problem becomes even more complex when uncertainty information needs to be presented as well. This paper addresses the question of how to visually communicate all three aspects: the 3D terrain, the geo-spatial data, and the data-associated uncertainty. We argue that visualizing all aspects with a high degree of detail will likely exceed the visual budget. Therefore, we propose a visualization strategy based on prioritizing a selected aspect and presenting the remaining two with less detail. We discuss various design options that allow us to obtain differently prioritized visual representations. Our approach has been implemented as a tool for rapid visualization prototyping in the context of avionics applications. Practical solutions are described for a use case related to the visualization of 3D terrain and uncertain weather data.

Landslide Identification and Information Extraction Based on Optical and Multispectral UAV Remote Sensing Imagery

Landslide is one of the most serious natural disasters which caused enormous economic losses and casualties in the world. Fast and accurate identification of newly occurred landslide and extraction of relevant information are the premise and foundation for landslide disaster assessment and relief. As the places where landslides occur are often inaccessible for field observation because of the temporary failure in transportation and communication. Therefore, UAV remote sensing can be adopted to collect landslide information efficiently and quickly with the advantages of low cost, flexible launch and landing, safety, under-cloud-flying, and hyperspatial image resolution. Newly occurred landslides are usually accompanied with those phenomena such as vegetation burying and bedrock or bare soil exposure, which can be easily detected in optical or multispectral UAV images. By taking one typical landslide occurred in Wenchuan Earthquake stricken area in 2010 as an example, this paper demonstrates the process of integration of multispectral camera with UAV platform, NDVI generation with multispectral UAV images, three-dimensional terrain and orthophoto generation with optical UAV images, and identification and extraction of landslide information such as its location, impacted area, and earthwork volume.

An integrated UAV-borne lidar system for 3D habitat mapping in three forest ecosystems across China

ABSTRACTIn recent decades, global biodiversity has gradually diminished due to the increasing pressure from anthropogenic activities and climatic change. Accurate estimations of spatially continuous three-dimensional (3D) vegetation structures and terrain information are prerequisites for biodiversity studies, which are usually unavailable in current ecosystem-wide studies. Although the airborne lidar technique has been successfully used for mapping 3D vegetation structures at landscape and regional scales, the relatively high cost of airborne lidar flight mission has significantly limited its applications. The unmanned aerial vehicle (UAV) provides an alternative platform for lidar data acquisition, which can largely lower the cost and provide denser lidar points compared with airborne lidar. In this study, we implemented a low-cost UAV-borne lidar system, including both a hardware system and a software system, to collect and process lidar data for biodiversity studies. The implemented UAV-borne lidar system was tested in three different ecosystems across China, including a needleleaf–broadleaf mixed forest, an evergreen broadleaf forest, and a mangrove forest. Various 3D vegetation structure parameters (e.g. canopy height model, canopy cover, leaf area index, aboveground biomass) were derived from the UAV-borne lidar data. The results show that the implemented UAV-borne lidar system can generate very high resolution 3D terrain and vegetation information. The developed UAV-based hardware and software systems provide a turn-key solution for the use of UAV-borne lidar data on biodiversity studies.

Three-dimensional flood routing of a dam break based on a high-precision digital model of a dense urban area

Dense buildings are the major factor affecting urban flood routing. Currently, the study of urban dam-break flood routing primarily focuses on a simplified terrain model and 2D shallow water equations, which ignore the effects of dense urban buildings. Furthermore, the complex interactions between the dam-break wave and the wall surfaces of buildings are not reflected in the results. To tackle these problems, three-dimensional flood routing with a high-precision digital model of an urban area is studied in this paper. Firstly, the vector data of various land types is extracted from a remote sensing image, and the NURBS algorithm based on the TIN algorithm is introduced to construct a three-dimensional terrain model. Coupled with the vector data and the terrain model, a three-dimensional digital model of the urban area is established. Next, a three-dimensional \(k{-}\varepsilon\) turbulence model is proposed for the flood routing simulation. A polyhedral grid with a second-order accuracy and a discrete format is used to divide the digital model of the urban area, and the governing equations are solved using the PISO algorithm. Finally, the superiority of the 3D mathematical model and the computational efficiency of the polyhedral mesh model are validated according to the urban flood routing experiments of Testa and Soares-Frazao. An urban reservoir, located in SZ City, China, is modelled to show that a dam-break flood in an urban area exhibits significant three-dimensional characteristics. Moreover, due to the surrounding buildings, the flood exhibits complex three-dimensional turbulence phenomena, including collision, reflection and vortices.

Improved Path Loss Simulation Incorporating Three-Dimensional Terrain Model Using Parallel Coprocessors

Current network simulators abstract out wireless propagation models due to the high computation requirements for realistic modeling. As such, there is still a large gap between the results obtained from simulators and real world scenario. In this paper, we present a framework for improved path loss simulation built on top of an existing network simulation software, NS-3. Different from the conventional disk model, the proposed simulation also considers the diffraction loss computed using Epstein and Peterson’s model through the use of actual terrain elevation data to give an accurate estimate of path loss between a transmitter and a receiver. The drawback of high computation requirements is relaxed by offloading the computationally intensive components onto an inexpensive off-the-shelf parallel coprocessor, which is a NVIDIA GPU. Experiments are performed using actual terrain elevation data provided from United States Geological Survey. As compared to the conventional CPU architecture, the experimental result shows that a speedup of 20x to 42x is achieved by exploiting the parallel processing of GPU to compute the path loss between two nodes using terrain elevation data. The result shows that the path losses between two nodes are greatly affected by the terrain profile between these two nodes. Besides this, the result also suggests that the common strategy to place the transmitter in the highest position may not always work.

ACCURACY OF 3D (THREE-DIMENSIONAL) TERRAIN MODELS IN SIMULATIONS

The usage of realistic three-dimensional (3D) polygon terrain models with multiple levels of detail (LOD) is becoming widespread in popular applications like computer games or simulations, as it offers many advantages. These models, which represent an actual location in the world, are essential for the simulation-based training of military vehicles like planes, helicopters or tanks. Because training scenarios on this kind of simulations are used to observe or to hit a target on the modeled location. In addition to that, driving the behavior of terrestrial vehicles is influenced by the terrain properties like slopes, ramps, hitches, etc. because of the direct interaction with the ground. For this reason, the terrain models in the simulation scene should not only display the textures realistically, but also represent an accurate morphology; meaning the terrain altitudes should be modeled as correct as possible. Such terrain representations can be created by using Digital Terrain Model (DTM) for the geometry and satellite images for texturing. The geometry models are in the form of polygonal meshes through the triangulation methods. However, the accuracy is influenced by some parameters. Using insufficient (under-refined) triangles during the 3D modeling causes missing of some altitude vertices. That means these points will not be present in the model. Consequently, it can be thought that the number of triangles should be increased for a better geometrical fidelity. Nevertheless, it is not always correct as the usage of too much (over-refined) triangles can also cause errors, especially in terrains with almost vertical faces (like cliffs). In addition to that, the performance of the system deteriorates drastically through the increase in the number of triangles, as the computational complexity is also getting higher.

The potential of global solar radiation in the Silesia region as a renewable source of energy

Abstract Historically, Silesia has been at the centre of the Polish coal industry for many years and thus has experienced poorer air quality compared to other voivodeships. However, in recent years strong economic transformation in the area has led to a considerable reduction in coal production. This study aimed to assess the variability of global solar radiation at selected stations within the Silesian voivodeship, in order to re-evaluate the resources of renewable solar energy during the period 1994–2013. The theoretical potential of solar radiation was calculated based on a three-dimensional terrain model. The data on global solar radiation from 13 stations within the Silesia region, covering the period 1994–2013, were obtained from the Regional Inspectorate of Environmental Protection in Katowice. The most favourable conditions for the use of solar energy were found at the cities Sosnowiec and Cieszyn. The largest increase in global radiation over the research period was observed in Zabrze. The average annual global radiation ranged between 600–1300 kWh·m−2. Digital Elevation Models (DEM) for selected districts of the Silesia region were used to calculate the theoretical potential of global solar radiation. The highest theoretical potential of global radiation was found in the district of Cieszyn, located at the highest altitude.

A new DDA model for kinematic analyses of rockslides on complex 3-D terrain

Landslides are common phenomena in mountainous regions worldwide. Over the past two decades, catastrophic rockslides in mountainous regions have caused serious damage and fatalities. To develop effective preventive countermeasures, it is important to estimate the kinematic behavior of displaced masses after slope failures, such as the velocity, run-out distance, and extent. Discontinuous deformation analysis (DDA) is an appropriate tool to analyze the dynamics, kinematics, and deformability of a block assembly. Many studies have reported applications of DDA to kinematic analyses of rockslides on two-dimensional (2-D) terrain. However, because of the restrictions of numerical techniques, few kinematic analyses of rockslides on three-dimensional (3-D) terrain have been performed using DDA. This study developed a new DDA model for the analysis of rockslides on 3-D terrain. First, contact treatment techniques for the 3-D model were developed to create an accurate and efficient computational scheme. The new model was then verified by the benchmark tests on the four basic types of block motion on 3-D terrain. Finally, the new model was applied to a designed rockslide with complex terrain to demonstrate its practical applicability. The results indicate that the new 3-D DDA model is an effective tool to analyze 3-D rockslides and could potentially be used to optimize protection designs for rockslides.