Unmanned Aerial Systems and Structure from Motion Revolutionize Wetlands Mapping

2015 ◽  
pp. 214-241 ◽  
Keyword(s):  
Structure From Motion ◽  
Unmanned Aerial Systems ◽  
Aerial Systems

scholarly journals Measuring ephemeral gully erosion rates and topographical thresholds in an urban watershed using unmanned aerial systems and structure from motion photogrammetric techniques

2018 ◽  
Vol 29 (6) ◽  
pp. 1896-1905 ◽  
Author(s):  
Napoleon Gudino-Elizondo ◽  
Trent W. Biggs ◽  
Carlos Castillo ◽  
Ronald L. Bingner ◽  
Eddy J. Langendoen ◽  
...  
Keyword(s):  
Structure From Motion ◽  
Gully Erosion ◽  
Unmanned Aerial Systems ◽  
Urban Watershed ◽  
Erosion Rates ◽  
Ephemeral Gully ◽  
Aerial Systems

Unmanned aerial vehicles can accurately, reliably, and economically compete with terrestrial mapping methods

2020 ◽  
Vol 8 (1) ◽  
pp. 57-74 ◽  
Author(s):  
Orrin Thomas ◽  
Christian Stallings ◽  
Benjamin Wilkinson
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Structure From Motion ◽  
Spatial Data ◽  
Mean Squared Error ◽  
Laser Scanner ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Squared Error ◽  
Similar Accuracy ◽  
Aerial Systems

Structure from motion (SfM) and imagery-derived point clouds (IDPC) are excellent tools for collecting spatial data. However, reported accuracies from unmanned aerial systems (UAS) commonly fall short of their theoretical potential. The research presented here, using a DJI Inspire 2 with post-processed kinematic direct geopositioning, demonstrates that UAS mapping can be consistently accurate enough for use in place of, or in concert with, terrestrial methods (2 cm vertical root mean squared error). We further demonstrate that features that are missing or distorted in IDPC (e.g., roof edges, break lines, and above-ground utilities) can be collected from UAS-imagery stereo models with similar accuracy. Accuracy in the experiments was verified by comparison to data from a total station and terrestrial laser scanner (TLS). Use of the recommended hardware and stereo compilation reduced mapping costs by 40%–75% on three test projects.

LIGHTER-THAN-AIR (LTA) UNMANNED AERIAL SYSTEM (UAS) CARRIER CONCEPT FOR SURVAILLANCE AND DISASTER MANAGEMENT

2019 ◽  
Vol 3 ◽  
pp. 1255
Author(s):  
Ahmad Salahuddin Mohd Harithuddin ◽  
Mohd Fazri Sedan ◽  
Syaril Azrad Md Ali ◽  
Shattri Mansor ◽  
Hamid Reza Jifroudi ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Disaster Management ◽  
Unmanned Aerial Systems ◽  
Unmanned Aerial System ◽  
Border Control ◽  
Aerial Vehicles ◽  
Operational Safety ◽  
In Situ Methods ◽  
Aerial Systems

Unmanned aerial systems (UAS) has many advantages in the fields of SURVAILLANCE and disaster management compared to space-borne observation, manned missions and in situ methods. The reasons include cost effectiveness, operational safety, and mission efficiency. This has in turn underlined the importance of UAS technology and highlighted a growing need in a more robust and efficient unmanned aerial vehicles to serve specific needs in SURVAILLANCE and disaster management. This paper first gives an overview on the framework for SURVAILLANCE particularly in applications of border control and disaster management and lists several phases of SURVAILLANCE and service descriptions. Based on this overview and SURVAILLANCE phases descriptions, we show the areas and services in which UAS can have significant advantage over traditional methods.

Beach and dune impacts due to Hurricane Florence in Dare County, North Carolina

Shore & Beach ◽  
2019 ◽  
pp. 44-49 ◽  
Author(s):  
Elizabeth Sciaudone ◽  
Liliana Velasquez-Montoya
Keyword(s):  
North Carolina ◽  
Prior Knowledge ◽  
Unmanned Aerial Systems ◽  
State University ◽  
National Wildlife Refuge ◽  
Sediment Samples ◽  
Wildlife Refuge ◽  
Full Report ◽  
Aerial Systems

Less than two weeks after Hurricane Florence made landfall in North Carolina (NC), a team of researchers from NC State University traveled to Dare County to investigate the storm’s effects on beaches and dunes. Using available post-storm imagery and prior knowledge of vulnerabilities in the system, the team identified several locations to visit in the towns of Kitty Hawk, Nags Head, Rodanthe, Buxton, and Hatteras, as well as a number of locations within the Pea Island National Wildlife Refuge (Figure 1). Data collected included topographic profiles, still imagery and video from unmanned aerial systems, sediment samples, and geo-located photography. This Coastal Observations piece presents some of the data and photos collected; the full report is available online (Sciaudone et al. 2019), and data collected will be made available to interested researchers upon request.

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