Derivation of River Bathymetry Using Imagery from Unmanned Aerial Vehicles (UAV)

Abstract

In many places that U.S. forces operate, there exists an insufficient amount of data regarding river water depths, which is a necessity for safe operational planning. Satellite sensors and airborne manned platforms have been used for bathymetric derivation, but are not in abundance, nor do they have the spatial resolution required to examine smaller rivers. Using Unmanned Aerial Vehicles (UAV), this research examines the feasibility of using a ratio method with digital imagery to derive water depths, as well as a simpler polynomial regression to create a lookup table for use in the field. The results show that the ratio method of Red to Blue had higher correlation than Red color band on its own, and that the simple polynomial regression using a ratio of Red to Blue had higher correlation than more widely accepted methods. However, both methods are limited by a maximum depth, which is defined as the point where color no longer changes with depth. All depths beyond this point appear as this maximum depth. These findings show that using imagery from UAVs for bathymetric derivation could be a feasible alternative to accepted satellite imagery methods, but further research is needed to demonstrate its operational utility.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2011
Accession Number
ADA552292

Entities

People

  • Matthew Pawlenko

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Artificial Satellites
  • Detection
  • Detectors
  • Electromagnetic Spectra
  • Full Motion Video
  • Geography
  • Lidar
  • Optical Properties
  • Optics
  • Radiative Transfer
  • Remote Sensing
  • Satellite Imaging
  • Unmanned Aerial Vehicles
  • Unmanned Systems
  • Vehicles
  • Visible Spectra

Readers

  • Coastal and Marine Engineering/Sediment Transport/Hydraulic Engineering
  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.

Technology Areas

  • Autonomy
  • Autonomy - UAVs
  • Space