Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Large river bed sediment characterization with low-cost sidescan sonar

Large river bed sediment characterization with low-cost sidescan sonar

Presented at SEDHYD 2015

Daniel Buscombe

April 02, 2015
Tweet

More Decks by Daniel Buscombe

Other Decks in Science

Transcript

  1. Sampling riverbed substrates is tough when ... ... water is

    too turbid or deep to image the bed from aerial platforms ... too swift or deep to wade to obtain physical samples ... spatial variability is so great its impractical to sample using conventional methods
  2. Sampling riverbed substrates is tough when ... ... water is

    too turbid or deep to image the bed from aerial platforms ... too swift or deep to wade to obtain physical samples ... spatial variability is so great its impractical to sample using conventional methods
  3. Sampling riverbed substrates is tough when ... ... water is

    too turbid or deep to image the bed from aerial platforms ... too swift or deep to wade to obtain physical samples ... spatial variability is so great its impractical to sample using conventional methods
  4. Low-cost, low-profile inexpensive sidescan sonar Operated by one person in

    any river or stream navigable by small boat. Sufficient quality for bed imaging in shallow streams Automate sonar processing, positioning, and substrate classification
  5. Colorado River in Marble Canyon Anima et al, 1998 USGS

    OFR: sidescan and video surveys Up to 100% change in sand coverage over a few 100 m Up to 100% change in sand coverage over 2 years
  6. Correction for shadow bias Object of given height, shadow lengthening

    goes with with grazing angle Buscombe et al., Journal of Hydraulic Engineering, in review
  7. Texture Lengthscale Mean texture lengthscale (m) w = (s σ2(s)

    δs) cos(θ) Scale (m) Normalized variance spectrum Grazing angle Buscombe et al., Journal of Hydraulic Engineering, in review
  8. Summary Low-cost, low-profile, and highly portable sidescan sonar for imaging

    shallow riverine benthic sediments. A new automated, spatially explicit and physically based method for texture lengthscales in sidescan echograms Not a direct measure of grain size could provide a basis for objective, automated riverbed sediment classification
  9. Summary Low-cost, low-profile, and highly portable sidescan sonar for imaging

    shallow riverine benthic sediments. A new automated, spatially explicit and physically based method for texture lengthscales in sidescan echograms Not a direct measure of grain size could provide a basis for objective, automated riverbed sediment classification
  10. Summary Low-cost, low-profile, and highly portable sidescan sonar for imaging

    shallow riverine benthic sediments. A new automated, spatially explicit and physically based method for texture lengthscales in sidescan echograms Not a direct measure of grain size could provide a basis for objective, automated riverbed sediment classification
  11. Summary Low-cost, low-profile, and highly portable sidescan sonar for imaging

    shallow riverine benthic sediments. A new automated, spatially explicit and physically based method for texture lengthscales in sidescan echograms Not a direct measure of grain size could provide a basis for objective, automated riverbed sediment classification
  12. Thanks for listening Buscombe et al., Automated riverbed sediment classification

    using low-cost sidescan sonar. Journal of Hydraulic Engineering, in review [email protected]
  13. Texture Lengthscale Autospectral variance (function of scale, s) σ2(s) =

    (n - ( nW 2 n (s) δy))2 W 2 n (s)δy Location along scan (pixel) Wavelet power spectrum (function of location and scale) Metres between pixels Buscombe et al., Journal of Hydraulic Engineering, in review