High spatial resolution hyperspectral mapping of in-stream habitats, depths, and woody debris in mountain streams

Marcus, W. Andrew; Legleiter, Carl J.; Aspinall, Richard; Boardman, Joseph W.; Crabtree, Robert L.

doi:10.1016/s0169-555x(03)00150-8

Cited by 167 publications

(166 citation statements)

References 19 publications

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“…Detailed bathymetry maps of inland water bodies are essential for simulating flow dynamics and forecasting flood hazard (Conner and Tonina, 2014;Gichamo et al, 2012;Schäppi et al, 2010), predicting sediment transport and streambed morphological evolution (Manley and Singer, 2008;Nitsche et al, 2007;Rovira et al, 2005;Snellen et al, 2011), and monitoring instream habitats (Brown and Blondel, 2009;Powers et al, 2015;Strayer et al, 2006;Walker and Alford, 2016). Whereas exposed floodplain areas can be directly monitored from aerial surveys, riverbed topography is not directly observable from airborne or space-borne methods (Alsdorf et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, remote sensing imagery from satellites, such as Landsat (Liceaga-Correa and Euan-Avila, 2002), QuickBird (Lyons et al, 2011), IKONOS (Stumpf et al, 2003), WorldView-2 (Hamylton et al, 2015;Lee et al, 2011), and aircrafts (Carbonneau et al, 2006;Marcus et al, 2003), has been used to monitor the bathymetry of inland water bodies. However, bathymetry can only be derived from optical imagery when water is very clear and shallow, the sediment is comparatively homogeneous, and atmospheric conditions are favorable (Legleiter et al, 2009;Lyzenga, 1981;Lyzenga et al, 2006;Overstreet and Legleiter, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle

Bandini

Olesen

Jakobsen

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. High-quality bathymetric maps of inland water bodies are a common requirement for hydraulic engineering and hydrological science applications. Remote sensing methods, such as space-borne and airborne multispectral imaging or lidar, have been developed to estimate water depth, but are ineffective for most inland water bodies, because of the attenuation of electromagnetic radiation in water, especially under turbid conditions. Surveys conducted with boats equipped with sonars can retrieve accurate water depths, but are expensive, time-consuming, and unsuitable for unnavigable water bodies.We develop and assess a novel approach to retrieve accurate and high-resolution bathymetry maps. We measured accurate water depths using a tethered floating sonar controlled by an unmanned aerial vehicle (UAV) in a lake and in two different rivers located in Denmark. The developed technique combines the advantages of remote sensing with the potential of bathymetric sonars. UAV surveys can be conducted also in unnavigable, inaccessible, or remote water bodies. The tethered sonar can measure bathymetry with an accuracy of ∼ 2.1 % of the actual depth for observations up to 35 m, without being significantly affected by water turbidity, bed form, or bed material.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle

Bandini

Olesen

Jakobsen

et al. 2018

Hydrol. Earth Syst. Sci.

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“…Both 4-and 7-unit classifications were generated, and an accuracy assessment including all pixels not used as training sites resulted in low overall accuracies of 64.7% and 47.5%, respectively (Table 3). Although Marcus et al (2003) obtained 85.5% accuracy by applying a 2 m buffer to field map polygons, the reduction in accuracy incurred when transitional boundary zones between habitat units are not excluded suggests that conventional image classification procedures might be inadequate for characterizing the full continuum of fluvial form. Supervised classifications are only as valid as the training sites from which they are derived, and sophisticated technology can not resolve the ambiguity among similar in-stream habitats.…”

Section: Crisp Supervised Classification Of In-stream Habitat: Lamarmentioning

confidence: 99%

“…This stream has been the site of prior research into remote mapping of fluvial environments and detailed descriptions of the study area are provided in Marcus et al (2003) and Legleiter (2003). Both data sets featured the fine spatial resolution required for small mountain streams, but provided different levels of spectral detail and radiometric precision (Table 1).…”

Section: Remotely Sensed Data and Image Processingmentioning

confidence: 99%

Alternative representations of in‐stream habitat: classification using remote sensing, hydraulic modeling, and fuzzy logic

Legleiter

Goodchild

2005

International Journal of Geographical Information Science

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Improved techniques are needed to characterize complex fluvial systems and monitor ecologically important, yet highly vulnerable riverine environments. This paper explores potential alternatives to traditional mapping of in-stream habitat and presents fuzzy set theory as a means of departing from the rigid, Boolean, object-based framework. We utilize hydrodynamic modeling, remotely sensed data, and fuzzy clustering to obtain classifications that allow for continuous partial membership and gradual transitions among habitat types. Methods of assessing cluster validity are available, but data quality is a crucial consideration. Crisp, vector-based representations can be derived from raster fuzzy classifications by applying a threshold to maximum membership values. This process results in conditional objects separated by ambiguous transition zones, and a compromise must be reached between the proportion of the channel assigned to polygons and the certainty with which this assignment can be made. Spatial patterns of classification uncertainty can also be used to identify areas of confusion, infer boundaries of variable width, and highlight areas of increased habitat diversity. Hydraulic modeling and remote sensing complement one another and, together with field work, could provide a more realistic representation of the fluvial environment.

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“…For example such robots could help locate hazardous chemical leaks [2], function as self propelled inspection devices [3], and search for victims in disaster sites [4,5,6]. Limbless robots that use their bodies to move appear better suited to navigate complex terrains than traditional wheeled [7,8,9,10] and legged [11,12,13,14,15,16,17] robots which are often impeded by the size or shape of their appendages which can result in entrapment or failure.…”

Section: Introductionmentioning

confidence: 99%

Robotics: Science and Systems VI

2010

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Abstract-Previous study of a sand-swimming lizard, the sandfish, Scincus scincus, revealed that the animal swims within granular media at speeds up to 0.4 body-lengths/cycle using body undulation (approximately a single period sinusoidal traveling wave) without limb use [1]. Inspired by this biological experiment and challenged by the absence of robotic devices with comparable subterranean locomotor abilities, we developed a numerical simulation of a robot swimming in a granular medium (modeled using a multi-particle discrete element method simulation) to guide the design of a physical sand-swimming device built with off-the-shelf servo motors. Both in simulation and experiment the robot swims limblessly subsurface and, like the animal, increases its speed by increasing its oscillation frequency. It was able to achieve speeds of up to 0.3 body-lengths/cycle. The performance of the robot measured in terms of its wave efficiency, the ratio of its forward speed to wave speed, was 0.34±0.02, within 8 % of the simulation prediction. Our work provides a validated simulation tool and a functional initial design for the development of robots that can move within yielding terrestrial substrates.

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High spatial resolution hyperspectral mapping of in-stream habitats, depths, and woody debris in mountain streams

Cited by 167 publications

References 19 publications

Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle

Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle

Alternative representations of in‐stream habitat: classification using remote sensing, hydraulic modeling, and fuzzy logic

Robotics: Science and Systems VI

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