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Full-Text Articles in Engineering
Assessing The Potential Of Uav-Based Multispectral And Thermal Data To Estimate Soil Water Content Using Geophysical Methods, Yunyi Guan, Katherine R. Grote
Assessing The Potential Of Uav-Based Multispectral And Thermal Data To Estimate Soil Water Content Using Geophysical Methods, Yunyi Guan, Katherine R. Grote
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Knowledge of the soil water content (SWC) is important for many aspects of agriculture and must be monitored to maximize crop yield, efficiently use limited supplies of irrigation water, and ensure optimal nutrient management with minimal environmental impact. Single-location sensors are often used to monitor SWC, but a limited number of point measurements is insufficient to measure SWC across most fields since SWC is typically very heterogeneous. To overcome this difficulty, several researchers have used data acquired from unmanned aerial vehicles (UAVs) to predict the SWC by using machine learning on a limited number of point measurements acquired across a …
Potential Benefits Of Combining Anomaly Detection With View Planning For Uav Infrastructure Modeling, R. Abraham Martin, Landen Blackburn, Joshua Pulsipher, Kevin W. Franke, John Hedengren
Potential Benefits Of Combining Anomaly Detection With View Planning For Uav Infrastructure Modeling, R. Abraham Martin, Landen Blackburn, Joshua Pulsipher, Kevin W. Franke, John Hedengren
Faculty Publications
This paper presents a novel method for UAV-based 3D modeling of large infrastructure objects, such as pipelines, canals and levees, that combines anomaly detection with automatic on-board 3D view planning. The study begins by assuming that anomaly detections are possible and focuses on quantifying the potential benefits of the combined method and the view planning algorithm. A simulated canal environment is constructed, and several simulated anomalies are created and marked. The algorithm is used to plan inspection flights for the anomaly locations, and simulated images from the flights are rendered and processed to construct 3D models of the locations of …
Evolutionary View Planning For Optimized Uav Terrain Modeling In A Simulated Environment, Ronald A. Martin, Ivan Rojas, Kevin W. Franke, John Hedengren
Evolutionary View Planning For Optimized Uav Terrain Modeling In A Simulated Environment, Ronald A. Martin, Ivan Rojas, Kevin W. Franke, John Hedengren
Faculty Publications
This work demonstrates the use of genetic algorithms in optimized view planning for 3D reconstruction applications using small unmanned aerial vehicles (UAVs). The quality of UAV site models is currently highly dependent on manual pilot operations or grid-based automation solutions. When applied to 3D structures, these approaches can result in gaps in the total coverage or inconsistency in final model resolution. Genetic algorithms can effectively explore the search space to locate image positions that produce high quality models in terms of coverage and accuracy. A fitness function is defined, and optimization parameters are selected through semi-exhaustive search. A novel simulation …
Comparison Of Sfm Computer Vision Point Clouds Of A Landslide Derived From Multiple Small Uav Platforms And Sensors To A Tls Based Model, Samantha Ruggles, Joseph Clark, Kevin W. Franke, Derek Wolfe, Brandon Reimschiissel, Ronald Abraham Martin, Trent Okeson, John Hedengren
Comparison Of Sfm Computer Vision Point Clouds Of A Landslide Derived From Multiple Small Uav Platforms And Sensors To A Tls Based Model, Samantha Ruggles, Joseph Clark, Kevin W. Franke, Derek Wolfe, Brandon Reimschiissel, Ronald Abraham Martin, Trent Okeson, John Hedengren
Faculty Publications
Structure from motion (SfM) computer vision is a remote sensing method that is gaining popularity due to its simplicity and ability to accurately characterize site geometry in three dimensions (3D). While many researchers have demonstrated the potential for SfM to be used with unmanned aerial vehicles (UAVs) to model in three dimensions various geologic features such as landslides, little is understood how the selection of the UAV platform can affect the resolution and accuracy of the model. This study evaluates the resolution and accuracy of 3D point cloud models of a large landslide that occurred in 2013 near Page, Arizona …
The Application And Accuracy Of Structure From Motion Computer Vision Models With Full-Scale Geotechnical Field Tests, L. Palmer, Kevin W. Franke, R. Abraham Martin, B. E. Sines, Kyle M. Rollins, John Hedengren
The Application And Accuracy Of Structure From Motion Computer Vision Models With Full-Scale Geotechnical Field Tests, L. Palmer, Kevin W. Franke, R. Abraham Martin, B. E. Sines, Kyle M. Rollins, John Hedengren
Faculty Publications
Structure from motion (SfM) computer vision is a relatively new technology that allows engineers to reconstruct a three-dimensional (3D) model of a given scene using twodimensional digital photographs captured from a single, moving camera. SfM computer vision provides an economic and user-friendly alternative to other 3D scene-capture and modeling tools such as light distance and ranging (LiDAR). Although the resolution and accuracy of laser-based modeling methods are generally superior to vision-based modeling methods, the economic advantages associated with the latter may make it a useful and practical alternative for many geotechnical engineering applications. Although other engineering disciplines have investigated the …