Airborne Infrared Remote Sensing of Riverine Currents

Measurements of surface currents have been made in a variety of rivers and estuaries to evaluate the accuracy and robustness of techniques based on airborne infrared (IR) imaging of the advection of small-scale temperature variations. The imaging system is a modification of our Airborne Remote Optic...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2014-07, Vol.52 (7), p.3895-3907
Main Authors: Dugan, J. P., Anderson, S. P., Piotrowski, C. C., Zuckerman, S. B.
Format: Article
Language:English
Subjects:
Algorithms
Applied geophysics
Cameras
Current measurement
Density
Earth sciences
Earth, ocean, space
Errors
Estuarine
Exact sciences and technology
Freshwater
Imaging
Infrared
infrared (IR)
Internal geophysics
Noise
Ocean temperature
Remote sensing
Retrieval
riverine
Rivers
Sea measurements
Sea surface
surface currents
turbulence
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Summary:Measurements of surface currents have been made in a variety of rivers and estuaries to evaluate the accuracy and robustness of techniques based on airborne infrared (IR) imaging of the advection of small-scale temperature variations. The imaging system is a modification of our Airborne Remote Optical Spotlight System to include a midwave IR camera. This system collects image sequences that are subsequently registered and mapped to the mean water level, providing space-time data proportional to water surface temperature along the watercourse. The temperature modulations are analyzed with two algorithms to assess the data and retrieve the currents. The full 3-D frequency-wavenumber spectrum is used to evaluate the signal and competing noise sources. A version of the maximum cross-correlation (MCC) algorithm, often used for measuring fluid motions, is applied to retrieve currents for most of the data analyzed here. The retrieved currents agree with the acoustic Doppler current profiler measurements with no mean bias and within 10 cm/s in 60% or more of ~ 1500 independent comparisons on multiple rivers. An error metric based on an MCC reciprocal filtering technique provides a numerical measure of confidence in each retrieval. Most bad points are flagged, as the retrieved current vector fields exhibit few obvious large errors. The density of retrieval postings is nominally one every 8-16 pixels or 8-16 m.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2013.2277815