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K. T. Holland

Publications and source records attributed to K. T. Holland.

8 recordsLinked to original sources
USGS2012

Quantifying riverine surface currents from time sequences of thermal infrared imagery

River surface currents are quantified from thermal and visible band imagery using two methods. One method utilizes time stacks of pixel intensity to estimate the streamwise velocity at multiple locations. The other method uses particle image velocimetry to solve for optimal two-dimensional pixel displacements between successive frames. Field validation was carried out on the Wolf River, a small coastal plain river near Landon, Mississippi, United States, on 26-27 May 2010 by collecting imagery in association with in situ velocities sampled using electromagnetic current meters deployed 0.1 m below the river surface. Comparisons are made between mean in situ velocities and image-derived velocities from 23 thermal and 6 visible-band image sequences (5 min length) during daylight and darkness conditions. The thermal signal was a small apparent temperature contrast induced by turbulent mixing of a thin layer of cooler water near the river surface with underlying warmer water. The visible-band signal was foam on the water surface. For thermal imagery, streamwise velocities derived from the pixel time stack and particle image velocimetry technique were generally highly correlated to mean streamwise current meter velocities during darkness (r 2 typically greater than 0.9) and early morning daylight (r 2 typically greater than 0.83). Streamwise velocities from the pixel time stack technique had high correlation for visible-band imagery during early morning daylight hours with respect to mean current meter velocities (r 2 > 0.86). Streamwise velocities for the particle image velocimetry technique for visible-band imagery had weaker correlations with only three out of six correlations performed having an r 2 exceeding 0.6. Copyright 2012 by the American Geophysical Union.

Water Resources Research↗
USGS2011

Short-term sandbar variability based on video imagery: Comparison between Time-Average and Time-Variance techniques

Time–exposure intensity (averaged) images are commonly used to locate the nearshore sandbar position ( x b ), based on the cross-shore locations of maximum pixel intensity ( x i ) of the bright bands in the images. It is not known, however, how the breaking patterns seen in Variance images (i.e. those created through standard deviation of pixel intensity over time) are related to the sandbar locations. We investigated the suitability of both Time–exposure and Variance images for sandbar detection within a multiple bar system on the southern coast of Brazil, and verified the relation between wave breaking patterns, observed as bands of high intensity in these images and cross-shore profiles of modeled wave energy dissipation ( x D ). Not only is Time–exposure maximum pixel intensity location ( x i-Ti ) well related to x b , but also to the maximum pixel intensity location of Variance images ( x i-Va ), although the latter was typically located 15 m offshore of the former. In addition, x i-Va was observed to be better associated with x D even though x i-Ti is commonly assumed as maximum wave energy dissipation. Significant wave height (Hs) and water level (η) were observed to affect the two types of images in a similar way, with an increase in both Hs and η resulting in x i shifting offshore. This η-induced x i variability has an opposite behavior to what is described in the literature, and is likely an indirect effect of higher waves breaking farther offshore during periods of storm surges. Multiple regression models performed on x i , Hs and η allowed the reduction of the residual errors between x b and x i , yielding accurate estimates with most residuals less than 10 m. Additionally, it was found that the sandbar position was best estimated using x i-Ti ( x i-Va ) when x b was located shoreward (seaward) of its mean position, for both the first and the second bar. Although it is unknown whether this is an indirect hydrodynamic effect or is indeed related to the morphology, we found that this behavior can be explored to optimize sandbar estimation using video imagery, even in the absence of hydrodynamic data.

Marine Geology↗
USGS2009

The effect of bathymetric filtering on nearshore process model results

Nearshore wave and flow model results are shown to exhibit a strong sensitivity to the resolution of the input bathymetry. In this analysis, bathymetric resolution was varied by applying smoothing filters to high-resolution survey data to produce a number of bathymetric grid surfaces. We demonstrate that the sensitivity of model-predicted wave height and flow to variations in bathymetric resolution had different characteristics. Wave height predictions were most sensitive to resolution of cross-shore variability associated with the structure of nearshore sandbars. Flow predictions were most sensitive to the resolution of intermediate scale alongshore variability associated with the prominent sandbar rhythmicity. Flow sensitivity increased in cases where a sandbar was closer to shore and shallower. Perhaps the most surprising implication of these results is that the interpolation and smoothing of bathymetric data could be optimized differently for the wave and flow models. We show that errors between observed and modeled flow and wave heights are well predicted by comparing model simulation results using progressively filtered bathymetry to results from the highest resolution simulation. The damage done by over smoothing or inadequate sampling can therefore be estimated using model simulations. We conclude that the ability to quantify prediction errors will be useful for supporting future data assimilation efforts that require this information.

Coastal Engineering↗
USGS2008

Ocean wavenumber estimation from wave-resolving time series imagery

We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution). ?? 2008 IEEE.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS1997

Practical use of video imagery in nearshore oceanographic field studies

An approach was developed for using video imagery to quantify, in terms of both spatial and temporal dimensions, a number of naturally occurring (nearshore) physical processes. The complete method is presented, including the derivation of the geometrical relationships relating image and ground coordinates, principles to be considered when working with video imagery and the two-step strategy for calibration of the camera model. The techniques are founded on the principles of photogrammetry, account for difficulties inherent in the use of video signals, and have been adapted to allow for flexibility of use in field studies. Examples from field experiments indicate that this approach is both accurate and applicable under the conditions typically experienced when sampling in coastal regions. Several applications of the camera model are discussed, including the measurement of nearshore fluid processes, sand bar length scales, foreshore topography, and drifter motions. Although we have applied this method to the measurement of nearshore processes and morphologic features, these same techniques are transferable to studies in other geophysical settings.

IEEE Journal of Oceanic Engineering↗