Using Unmanned Aircraft System (UAS) Photogrammetry to Monitor Bank - - PowerPoint PPT Presentation

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Using Unmanned Aircraft System (UAS) Photogrammetry to Monitor Bank - - PowerPoint PPT Presentation

Using Unmanned Aircraft System (UAS) Photogrammetry to Monitor Bank Erosion along River Corridors 08-Jan-2018 Scott D. Hamshaw, Ph.D., P.E. Project Goals Evaluate UAS-based photogrammetry system Accuracy comparison to SenseFly eBee UAS


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Using Unmanned Aircraft System (UAS) Photogrammetry to Monitor Bank Erosion along River Corridors

08-Jan-2018 Scott D. Hamshaw, Ph.D., P.E.

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Project Goals

¨ Evaluate UAS-based

photogrammetry system

¨ Accuracy comparison to

ground survey

¨ Geomorphic change

measurement

SenseFly eBee UAS

Ground survey: RIEGL VZ-1000 TLS TopCon HiperLite+ GPS

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What we get from UAS

1.

Orthomosaic imagery

2.

Photogrammetric point cloud (RGB colorized)

3.

Derived products:

n Digital surface model (DSM) n Digital elevation model (DEM)

Filtering and/or Machine learning classification and processing Computer vision: Structure-from-motion (SfM) & multi-view stereo

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Orthomosaic imagery

3.2 cm UAS 0.5 m Ortho 1 m NAIP

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Photogrammetric point cloud

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Digital elevation and surface models

DSM DEM Airborne LiDAR DEM

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Accuracy Assessment – X-Sections

¨ 11 cm vertical / 28 cm horizontal

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Accuracy Assessment - GCPs

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Field Data Collection

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Data collection metrics

Year Number

  • f flights

Total Length of River Surveyed (km) Mean Length

  • f River per

Flight (m) Total days** in field for surveying Number of days impacted* by weather 2015 55 21.7 395 12 3 2016 18 13.7 760 5 5 2017 17 14.3 843 4 1

¨ 43% of survey days rescheduled/shortened ¨ 2-3 person survey team ¨ Direct georeferenecing with sparse GCPs for check

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Geomorphic Change Detection Volumetric Change Analysis

¨ Difference of DEMs (DoD) ‘12 ALS to ‘17 UAS ¨ Net change of -19,920 m3

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Geomorphic Change Detection Cross Section Analysis

3.5 m2

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UAS for monitoring river corridors

¨ Optimal survey time: early spring ¨ Sparse network of GCPs = check / bias adjustment ¨ Vegetation density dependent ¨ Technology rapidly developing (during project)

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Contact Info & Acknowledgements

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¨ Scott Hamshaw, Ph.D., P.E.

¤ Vermont EPSCoR | 23 Mansfield Ave, Burlington, VT ¤ scott.hamshaw@uvm.edu ¤ 802.324.6221

¨

Support provided by: ¤ Vermont Water Resources and Lake Studies Center

¤

Vermont EPSCoR with (NSF) Grant EPS-1101317 and EPS-1556770

¤

NSF Graduate Research Fellowship (Grant No. DGE-0925179NSF)

¤

Robert & Patricia Switzer Foundation

¤

University of Vermont

Special thanks to co-authors:

  • Mandar Dewoolkar
  • Jarlath O’Neil-Dunne
  • Donna Rizzo
  • Tayler Engel
  • Jeff Frolik
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Quantifying Streambank Movement and Topography Using Unmanned Aircraft System Photogrammetry with Comparison to Terrestrial Laser Scanning River Research and Applications 33 (8):1354–67. https://doi.org/10.1002/rra.3183.

Supplementary Information

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River corridor vegetation

Spring ‘12 Fall ‘15 Spring ‘17 Summer ‘16

Bristol Flats, New Haven River

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DoDs – New Haven River

2017 - 2016 2016 - 2012

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DoDs – New Haven River

2015 - 2012 2015 - 2012

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