Airborne Remote Sensing of Surface Velocities in a Tidal River

The global optimal solution (GOS) has proven to be very accurate for deriving water surface velocities from contemporaneous image pairs, but previous studies have used shore-based radars or satellite measurements with resolutions on the order of a kilometer or tens of meters to establish this. In co...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2018-08, Vol.56 (8), p.4559-4567
Main Authors: Mied, Richard P., Chen, Wei, Smith, Geoffrey B., Wagner, Ellen J., Miller, William David, Snow, Charlotte M., Marmorino, George O., Rhea, William Joseph
Format: Article
Language:English
Subjects:
Acoustic noise
Airborne remote sensing
Airborne sensing
Aircraft
Aircraft control
Collections
Data collection
Doppler sonar
Image contrast
Imagery
Infrared imaging
Measuring instruments
Meters
Remote control
Remote sensing
Rivers
Satellites
Sea measurements
Sea surface
Signal-to-noise ratio
Tidal rivers
Tidal waterways
tides
Velocity
Velocity distribution
Velocity measurement
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The global optimal solution (GOS) has proven to be very accurate for deriving water surface velocities from contemporaneous image pairs, but previous studies have used shore-based radars or satellite measurements with resolutions on the order of a kilometer or tens of meters to establish this. In contrast, the objective of this paper is to derive a GOS velocity field from infrared (IR) (3-5 \mu \text{m} ) images having a 1-m pixel size. Because IR images can frequently exhibit a low signal-to-noise ratio, a newly developed GOS technique with a local similarity metric is used to retrieve velocities from such low-contrast data sets. To demonstrate the utility of this new method, we use airborne data collected in the tidal Potomac River over 11 days and spatially varying flood, ebb, and slack conditions. The resulting GOS-derived velocity estimates are compared against acoustic Doppler current profiler (ADCP) measurements taken simultaneously with the airborne collections. Velocity magnitudes and directions are found to have GOS versus ADCP correlations of 0.93 and 0.99, respectively. This high correlation suggests that the GOS technique may be applicable to a variety of lower contrast imagery that can now be collected by a low-altitude remotely controlled aircraft.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2018.2826366