Frontiers in Remote Sensing (Apr 2024)
Evaluating the potential for efficient, UAS-based reach-scale mapping of river channel bathymetry from multispectral images
Abstract
Introduction: Information on spatial patterns of water depth in river channels is valuable for numerous applications, but such data can be difficult to obtain via traditional field methods. Ongoing developments in remote sensing technology have enabled various image-based approaches for mapping river bathymetry; this study evaluated the potential to retrieve depth from multispectral images acquired by an uncrewed aircraft system (UAS).Methods: More specifically, we produced depth maps for a 4 km reach of a clear-flowing, relatively shallow river using an established spectrally based algorithm, Optimal Band Ratio Analysis. To assess accuracy, we compared image-derived estimates to direct measurements of water depth. The field data were collected by wading and from a boat equipped with an echo sounder and used to survey cross sections and a longitudinal profile. We partitioned our study area along the Sacramento River, California, USA, into three distinct sub-reaches and acquired a separate image for each one. In addition to the typical, self-contained, per-image depth retrieval workflow, we also explored the possibility of exporting a relationship between depth and reflectance calibrated using data from one site to the other two sub-reaches. Moreover, we evaluated whether sampling configurations progressively more sparse than our full field survey could still provide sufficient calibration data for developing robust depth retrieval models.Results: Our results indicate that under favorable environmental conditions like those observed on the Sacramento River during low flow, accurate, precise depth maps can be derived from images acquired by UAS, not only within a sub-reach but also across multiple, adjacent sub-reaches of the same river.Discussion: Moreover, our findings imply that the level of effort invested in obtaining field data for calibration could be significantly reduced. In aggregate, this investigation suggests that UAS-based remote sensing could facilitate highly efficient, cost-effective, operational mapping of river bathymetry at the reach scale in clear-flowing streams.
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