Deploying unmanned aerial vehicle (UAV) networks to provide coverage for outdoor users has attracted great attention during the last decade. Terrain information requires extensive attention in outdoor UAV networks, and it is one of the most important factors affecting coverage performance. Providing tractable models and common methods is necessary to generalize the terrain-based outdoor UAV positioning strategies. In this thesis, we demonstrate that UAVs can provide stable coverage for regularly moving users based on the existing local terrain reconstruction methods with UAV sampling. Next, a coarse-grained UAV deployment can be performed with a simple set of parameters that characterize the terrain features. A stochastic geometry framework can provide general analytical results for the above coarse-grained UAV networks. In addition, the UAV can avoid building blockage without prior terrain information through real-time linear-trajectory search. We proposed four algorithms related to the combinations of collecting prior terrain information and using real-time search, and then their performances are evaluated and compared in different scenarios. By adjusting the height of the UAV based on terrain information collected before networking, the performance is significantly enhanced compared to the one when no terrain information is available. The algorithm based on real-time search further improves the coverage performance by avoiding the shadow of buildings. During the execution of the real-time search algorithm, the search distance is reduced using the collected terrain information.

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The Development, presentation, and application of technique for interpreting examples of so-called muskeg terrain in Northern Canada. The emphasis is with a view to utilitarian aspects, not necessarily botanical implications, though the medium for the work is vegetal coverage. Illustrated with photographs. / Thesis / Bachelor of Arts (BA)

An average slope index and a number of agricultural productivity indices were determined for a sample of 100 districts in Costa Rica. To establish the relationship between these variables, correlation coefficients were calculated between the average slope index, on the one hand and, on the other, total gross agricultural income, total net agricultural income and also income and yields for individual crops. These relationships were calculated for the meseta central (the central, highly-populated area) and for areas outside of the meseta central and for the total sample taken from all of Costa Rica. Cases in which gross agricultural incomes were much lower than predicted by the study were investigated further to identify other factors which may have influenced the results. / Thesis / Master of Arts (MA)

The creation of landslide inventories is an important step in landslide susceptibility mapping, and automated algorithms for landslide detection will increasingly be relied upon as part of the mapping process. This study compares the effects of three different DTM generation methods on a pixel-based landslide detection algorithm developed by Shi et al. (2018) using a set of landslide-prone study areas in Pierce County, Washington. Non-parametric statistical analysis demonstrated that false-positive and false-negative rates were significantly different between DTM generation methods, showing that inpainting presents a more balanced error profile compared to TIN and morphological-based approaches. However, overall accuracy (kappa) rates were still very low overall, suggesting that geomorphometric curvature as an input needs to be processed in a different manner to make these types of pixel-based landslide detection algorithms more useful for landslide inventory database management. / Master of Science / The creation of landslide inventories is an important step in landslide susceptibility mapping, and automated algorithms for landslide detection will increasingly be relied upon as part of the mapping process. This study compares the effects of three different DTM generation methods on a pixel-based landslide detection algorithm developed by Shi et al. (2018) using a set of landslide-prone study areas in Pierce County, Washington. Statistical analysis demonstrated that false-positive and false-negative rates were significantly different between DTM generation methods, showing that inpainting presents a more balanced error profile compared to TIN and morphological-based approaches. However, overall accuracy rates were still very low overall, suggesting that curvature as an input needs to be processed in a different manner to make these types of pixel-based landslide detection algorithms more useful for landslide inventory database management.

Throughout a ground vehicle development program, it is necessary to possess the loads the vehicle will experience. Unfortunately, actual loads are only available at the conclusion of the program, when the vehicle has been built and design changes are costly. The design engineer is challenged with using predicted loads early in the design process, when changes are relatively easy and inexpensive to make. It is advantageous, therefore, to accurately predict these loads early in the program, thus improving the vehicle design and, ultimately, saving time and money. The prediction of these loads depends on the fidelity of the vehicle models and their excitation. The focus of this thesis is the development of techniques for using 3D terrain surface measurements for vehicular simulations. Contributions are made to vehicle model parameter identification, terrain filtering, and application-dependent interpolation methods for 3D terrain surfaces. Modeling and simulation are used to improve and shorten a vehicle's development cycle, thus, saving time and money. An important aspect in developing a vehicle model is to identify the parameters. Some parameters are easily measured with readily available tools; however, other parameters require dismantling the vehicle or using expensive test equipment. Initial estimates of these difficult or costly to obtain parameters are made based on similar vehicle models or standard practices. In this work, a parameter identification method is presented to obtain a better estimate of these inaccessible parameters using measured terrain excitations. By knowing the excitations to the physical vehicle, the simulated response can be compared to measured response, and then the vehicle model's parameters can be optimized such that the error between the responses is minimized. Through this process, better estimates of the vehicle's parameter are obtained, which demonstrates that measured terrain can improve vehicle development by increasing the accuracy of parameter estimates. The principal excitation to any ground vehicle is the terrain, and by obtaining more accurate representations of the terrain, vehicular simulation techniques are advanced. Many simple vehicle models use a point contact tire model, which performs poorly when short wavelength irregularities are present because the model neglects the tire's mechanical filtering properties. Therefore, a filter is used to emulate a tire's mechanical filtering mechanism and create an effective terrain profile. In this work, terrain filters are evaluated to quantify their effect on the sprung mass response of the dynamic simulation of a seven degree of freedom vehicle model. In any vehicular simulation, there is a balance between analytical expense and simulation realism. This balance often limits simulations to 2D terrain profile excitations, but as computing power increases the computational expense decreases. Thus, 3D terrain excitations for vehicular simulation are a tool for advancing simulation realism that is becoming less computationally expensive. Three dimensional terrain surfaces are measured with a non-uniform spacing in the horizontal plane; therefore, application-dependent gridding methods are developed in this work to interpolate 3D terrain surface to uniform grid spacing. The uniform grid spacing allows 3D terrain surfaces to be used more efficiently in any vehicular simulation when compared to non-uniform spacing. / Master of Science