A Lightweight, Robust Exploitation System for Temporal Stacks of UAS Data: Use Case for Forward-Deployed Military or Emergency Responders
Abstract
:1. Introduction
1.1. Unmanned Aerial System (UAS)-Derived Three-Dimensional (3D) Data More Ubiquitous
1.2. Challenges with UAS-Derived 3D Analysis
2. Material and Methods
2.1. Study Area
2.2. Preprocessing and Data
2.3. Computing Resources
3. Theory and Calculation
3.1. Voxelization
3.2. Database (MongoDB and PostGres)
3.3. CesiumJS Front-End
4. Results
4.1. Front-End Rendering
4.2. Query and Analysis Tools
5. Discussion and Conclusions
Author Contributions
Funding
Acknowledgements
Conflicts of Interest
Abbreviations
AGL | Above Ground Level |
FAA | Federal Aviation Administration |
GCP | Ground Control Point |
GPS | Global Positioning System |
LAS | Log ASCII Standard |
LIDAR | Light Detection and Ranging |
RBG | Red Blue Green |
RTK | Real Time Kinetic |
UAS | Unmanned Aerial System |
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Processing Option | Selection |
---|---|
Keypoints Image Scale | Full |
Matching Image Pairs | Aerial Grid or Corridor |
Matching Strategy | Geometrically Verified Matching |
Targeted Number of Keypoints | Automatic |
Calibration | Accurate Geolocation and Orientation |
Processing Option | Selection |
---|---|
Image Scale | (½) Half Image Size |
Point Density | Optimal |
Minimum Number of Matches | 3 |
Export | LAS |
Matching Window Size | 9 × 9 pixels |
Processing Area | Use Processing Area |
Annotations | Use Annotations |
Limit Camera Depth | Use Limit Camera Depth Automatically |
Description | Value | |
---|---|---|
Position | cartographicDegrees | [longitude, latitude, elevation] |
Box | dimensions/cartesian | [x, y, z] |
material/solidColor/color/rgba | [r, g, b, a] | |
Availability | Time interval | |
Points | pointIndexes | List of point IDs |
size | Number of points |
Tool | Description |
---|---|
3D RGB Rendering | Rendering of voxels based on R,G,B values |
3D Point Count Classification Rendering | Rendering of voxels based on Point Count classifications |
Temporal Voxel Attribute Pull | Ability to retrieve and graph temporal values for R,G,B (can be customized for other attribute values) |
Temporal Voxel Point Count Pull | Ability to retrieve and graph temporal values of voxel point count |
Temporal Clustering Metric Pull | Ability to retrieve and graph clustering metric of voxels |
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Share and Cite
Marx, A.; Chou, Y.-H.; Mercy, K.; Windisch, R. A Lightweight, Robust Exploitation System for Temporal Stacks of UAS Data: Use Case for Forward-Deployed Military or Emergency Responders. Drones 2019, 3, 29. https://doi.org/10.3390/drones3010029
Marx A, Chou Y-H, Mercy K, Windisch R. A Lightweight, Robust Exploitation System for Temporal Stacks of UAS Data: Use Case for Forward-Deployed Military or Emergency Responders. Drones. 2019; 3(1):29. https://doi.org/10.3390/drones3010029
Chicago/Turabian StyleMarx, Andrew, Yu-Hsi Chou, Kevin Mercy, and Richard Windisch. 2019. "A Lightweight, Robust Exploitation System for Temporal Stacks of UAS Data: Use Case for Forward-Deployed Military or Emergency Responders" Drones 3, no. 1: 29. https://doi.org/10.3390/drones3010029