Name
Title | ||
|---|---|---|
An Experimental Evaluation of the Feasibility of Inferring Concentrations of a Visible Tracer Dye from Remotely Sensed Data in Turbid Rivers. |
Abstract | ||
|---|---|---|
The movement of contaminants and biota within river channels is influenced by the flow field via various processes of dispersion. Understanding and modeling of these processes thus can facilitate applications ranging from the prediction of travel times for spills of toxic materials to the simulation of larval drift for endangered species of fish. A common means of examining dispersion in rivers involves conducting tracer experiments with a visible tracer dye. Whereas conventional in situ instruments can only measure variations in dye concentration over time at specific, fixed locations, remote sensing could provide more detailed, spatially-distributed information for characterizing dispersion patterns and validating two-dimensional numerical models. Although previous studies have demonstrated the potential to infer dye concentrations from remotely sensed data in clear-flowing streams, whether this approach can be applied to more turbid rivers remains an open question. To evaluate the feasibility of mapping spatial patterns of dispersion in streams with greater turbidity, we conducted an experiment that involved manipulating dye concentration and turbidity within a pair of tanks while acquiring field spectra and hyperspectral and RGB (red, green, blue) images from a small Unoccupied Aircraft System (sUAS). Applying an optimal band ratio analysis (OBRA) algorithm to these data sets indicated strong relationships between spatially averaged reflectance (i.e., water color) and Rhodamine WT dye concentration across four different turbidity levels from 40-60 NTU. Moreover, we obtained high correlations between spectrally based quantities (i.e., band ratios) and dye concentration for the original, essentially continuous field spectra; field spectra resampled to the bands of a five-band imaging system and an RGB camera; and both hyperspectral and RGB images acquired from an sUAS during the experiment. The results of this study thus confirmed the potential to map dispersion patterns of tracer dye via remote sensing and suggested that this empirical approach can be extended to more turbid rivers than those examined previously. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3390/rs12010057 | REMOTE SENSING |
Keywords | Field | DocType |
tracer,dye,concentration,river,turbidity,Rhodamine,hyperspectral,multispectral,UAS,dispersion | TRACER,Remote sensing,Geology | Journal |
Volume | Issue | Citations |
12 | 1 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carl J. Legleiter | 1 | 0 | 0.68 |
| Paul V. Manley | 2 | 0 | 0.34 |
| Susannah O. Erwin | 3 | 0 | 0.34 |
| Edward A. Bulliner | 4 | 0 | 0.34 |