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Aerial Seismology Using Balloon-Based Barometers
Seismology on Venus has long eluded planetary scientists due to extreme temperature and pressure conditions on its surface, which most electronics cannot withstand for mission durations required for ground-based seismic studies. Here, we show that infrasonic (low-frequency) pressure fluctuations, generated as a result of ground motion, produced by an artificial seismic source known as a seismic hammer, and recorded using sensitive microbarometers deployed on a tethered balloon, are able to replicate the frequency content of ground motion. We also show that weak, artificial seismic activity thus produced may be geolocated by using multiple airborne barometers. The success of this technique paves the way for balloon-based aero-seismology, leading to a potentially revolutionary method to perform seismic studies from a remote airborne station on the earth and solar system objects with substantial atmospheres such as Venus and Titan.
Newer Aerial Platform for Emergency Response by the United States Department of Energy
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Aerial 3D Building Reconstruction from Drone Imagery (A3DBR) v1
This toolkit is composed of several modules for extracting buildings geometrical and thermal characteristics from RGB and thermal imagery captured using a drone. - Building 3D reconstruction module: leverage a photogrammetry software to construct a 3D point cloud from RGB drone imagery, which is then used in conjunction with image processing and geometric methods to extract building footprint and building height (i.e., 3D model of the building). - Windows to wall ratio estimation module: leverage deep learning semantic segmentation modeling to detect windows on 2D drone RGB images. The detected windows are then projected onto the extracted building 3D model (using building 3D reconstruction module) and their area is computed to obtain window to wall ratio estimation. - Thermal anomalies detection module: leverage image processing and machine learning algorithm to detect on 2D drone thermal images potential thermal anomalies within building's facades and roofs.
Novus: An Unmanned Aerial System and Virtual Reality Flight Deck for Data Collection and Visualization
Many emerging technologies offer tremendous new capabilities that will, without question, redefine how we interact with, utilize, understand, and optimize the energy systems around us. Drones offer a new ability to remotely capture data in ways that have previously been impractical. However, their flight control systems remain rudimentary and limit the ability of researchers to fully take advantage of these platforms as remote sensing devices. In this project, we constructed a hexarotor drone and outfitted it with advanced (yet inexpensive) sensors as well as a telemetry data management and control package. We then created a virtual reality flight deck that allows a drone operator to define waypoints "on-the-fly" or take manual control over flight operations. The flight deck provides a live on-board video stream display, a 3-dimensional topographic map with the drone’s position in space overlaid onto it, as well as a data visualization framework that keeps critical information immediately available to the operator. These advances provide a new platform for scientific data collection such as thermography of building envelopes or solar arrays. As the drone is in flight and data are being collected, these data are relayed to the virtual reality environment where they can be inspected for integrity and the flight plan altered if necessary to collect higher quality data. Future work will focus on implementing 3-dimensional mapping using both visible and thermal imagery collected from the drone, and streaming those into the virtual reality flight deck in real time.
High-Resolution Sampling of a River Plume Front with Uncrewed Underwater and Aerial Vehicles
Sampling fast-propagating oceanic features is inherently challenging and demands versatile instrumentation and innovative strategies. This paper introduces a novel sampling strategy designed to capture such phenomena, exemplified by a river plume front. Our method revolves around modifying the preprogrammed pathway of an uncrewed underwater vehicle (UUV) to dynamically track and three-dimensionally sample the evolution of the front. To enable the UUV to follow the feature, we adapt the use of a drifting gateway buoy to be positioned and trapped at the front’s convergence zone, allowing underway navigation relative to the buoy. In our demonstration, we showcase the effectiveness of this strategy by successfully conducting over 30 crossings of a river plume front within a 6-h window. The UUV sensors allowed a comprehensive assessment of key front characteristics, including density, velocity, and turbulence. Supplemental drone footage contributed to the overall picture and facilitated the transformation of the dataset into a front-following reference frame. This article provides an in-depth description of the deployment strategy and required postcollection data processing, including frontal crossing detection, the assessment of the frontal orientation from drone footage, and defining the plume bottom boundaries using backscatter intensity contours.
Association mapping by aerial drone reveals 213 genetic associations for Sorghum bicolor biomass traits under drought
Not Available
Data for Aerial Imagery Can Detect Nitrogen Fertilizer Effects on Biomass and Stand Health of Miscanthus × giganteus
Miscanthus × giganteus ( Miscanthus ) is a warm-season perennial grass grown for bioenergy feedstock production. Nitrogen (N) fertilizer management is crucial for the sustainability of Miscanthus production. In our two-year study (2018 and 2019), we investigated the role of vegetation indices (VIs) in evaluating N fertilization (0 N, 56 N, 112 N, and 168 N kg ha−1) impacts on Miscanthus biomass yield and stand health. The flight campaigns were conducted early, middle, and late during the summer growing season. Among the VIs, mid-summer growing season NDRE provided the best prediction of fresh biomass (R2 = 0.87 and 0.97) and dry biomass (R2 = 0.89 and 0.97) in 2018 and 2019, respectively. The VIs generally showed that it was possible to distinguish between 0 N and 168 N treatments, but neither 0 N and 56 N kg ha−1 nor 112 N and 168 N kg ha−1 could be separated. The results from this study highlight the importance of moderate application of N (112 kg N ha−1) in improving and maintaining the stand health and biomass yield of Miscanthus over time and suggest that mid-summer growing season VIs, NDRE in particular, can be useful for assessment of Miscanthus stand health and biomass yield.
MODCOPTER: Prompt, Precise Aerial Sample Collection Using Unmanned Systems [Slides]
Abstract not provided.
3D Background Oriented Schlieren Imaging to Detect Aerial Improvised Explosive Devices [Slides]
Abstract not provided.
3D Background Oriented Schlieren Imaging to Detect Aerial Improvised Explosive Devices
Abstract not provided.
Modcopter: Prompt, Precise Aerial Sample Collection Using Unmanned Systems
Abstract not provided.
Evaluation of unmanned aerial vehicles for radiation detection
No abstract provided
Feature Detection From LiDAR Point Cloud and Aerial Imagery Using Distance Dependent Chinese Restaurant Process [Slides]
It is possible to integrate data captured by UAS from multiple data modalities spatially. We can detect features by combining information across images and LiDAR point clouds. Performance issues exist with the current algorithms in place & could be improved. We hope to test it for at least 500 iterations. Post processing of data takes enormous efforts in case of data generated by proprietary software tools…We intend to develop a better framework for seamless integration.
ATMOSPHERIC RADON MODELING FOR AERIAL MEASUREMENTS
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4-D Aggregate Deconvolution for Aerial Measurements RSLN-026-20, Year 1
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Aerial Crosspolarized NQR-NMR: Buried Explosive Detection From a Safe Distance
Nuclear quadrupole resonance is a non-destructive detection and inspection technique with potential as a non-destructive test (NDT) tool. Establishment of the capability opens the door to its use in furthering the mission of the labs. There are many possible uses of the capability: explosive detection and stress/strain detection in epoxies are two of the more obvious and are the main results of this work. Enhancement of the signal-to-noise ratio (SNR) and improvements in the acquisition time of the experiment were key focuses of this work. These were achieved by combing special spin-lock pulse sequences with cross-polarization (CP) schemes to improve the signals with shorter acquisition times. A novel rotating magnetic field device was created to facilitate CP in the field. Implementation of these schemes provided a significant reduction in SNR/time.
Aerial Measuring System Geophysical Calibration Longitudinal Study
This is a poster reviewing AMS calibration procedures for the AGU conference