2019
DOI: 10.3390/d11070116
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Accuracy and Precision of Low-Cost Echosounder and Automated Data Processing Software for Habitat Mapping in a Large River

Abstract: The development of consumer hydroacoustic systems continues to advance, enabling the use of low-cost methods for professional mapping purposes. Information describing habitat characteristics produced with a combination of low-cost commercial echosounder (Lowrance HDS) and a cloud-based automated data processing tool (BioBase EcoSound) was tested. The combination frequently underestimated water depth, with a mean absolute error of 0.17 ± 0.13 m (avg ± 1SD). The average EcoSound bottom hardness value was high (0… Show more

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Cited by 18 publications
(16 citation statements)
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“…To understand differences in daytime physicochemical parameters in the water column (i.e., pH, temperature (°C), dissolved oxygen saturation % (hereafter oxygen), and specific conductivity (μS cm −1 at 25°C) associated with growth of macrophyte beds over the peak accumulation period, field data were collected at four sites in each of the lacustrine ( C. demersum ) and riverine ( E. densa ) sections between 20 November and 7 December 2018 ( C. demersum only) and January 22–30, 2019 (both species) following an initial echo‐sound survey and aquatic vegetation mapping (Helminen, Linnansaari, Bruce, Dolson‐Edge, & Curry, 2019; for site locations see Figure 1). At each site, vertical profiles of water‐column physicochemical parameters were measured at four points designated in terms of macrophyte proportion (range 0–1) as: ‘macrophyte‐free’ (A; x¯ ± SD ; 0.1 ± 0.3 proportional macrophyte height), ‘light’ (B; 0.3 ± 0.2), ‘dense‐edge’ (C; 0.6 ± 0.3), and ‘dense‐bed’ (D; 0.7 ± 0.3) (see Figure 2b for further explanation).…”
Section: Methodsmentioning
confidence: 99%
“…To understand differences in daytime physicochemical parameters in the water column (i.e., pH, temperature (°C), dissolved oxygen saturation % (hereafter oxygen), and specific conductivity (μS cm −1 at 25°C) associated with growth of macrophyte beds over the peak accumulation period, field data were collected at four sites in each of the lacustrine ( C. demersum ) and riverine ( E. densa ) sections between 20 November and 7 December 2018 ( C. demersum only) and January 22–30, 2019 (both species) following an initial echo‐sound survey and aquatic vegetation mapping (Helminen, Linnansaari, Bruce, Dolson‐Edge, & Curry, 2019; for site locations see Figure 1). At each site, vertical profiles of water‐column physicochemical parameters were measured at four points designated in terms of macrophyte proportion (range 0–1) as: ‘macrophyte‐free’ (A; x¯ ± SD ; 0.1 ± 0.3 proportional macrophyte height), ‘light’ (B; 0.3 ± 0.2), ‘dense‐edge’ (C; 0.6 ± 0.3), and ‘dense‐bed’ (D; 0.7 ± 0.3) (see Figure 2b for further explanation).…”
Section: Methodsmentioning
confidence: 99%
“…run, riffle, pool and slack water) were classified using a decision tree adapted from Borsányi et al (2004; Table 1) based on crisp depth (1.0 and 3.0 m to delimit between shallow to medium and medium to deep categories, respectively) and water velocity (0.5 m s −1 to classify between fast and slow habitat) thresholds and drawn as geo‐referenced polygons on a field tablet running ArcGIS software. Depth was measured using an echosounder (with accuracy assessments by Helminen, Linnansaari, Bruce, Dolson‐Edge, & Curry, 2019), whereas water velocity was measured using an OTT metre (Type C20 ‘10.005’) with a calibration counter (model CMCsp from Hydrological Services Inc.). Field‐based mesohabitat maps at discrete flows were further used to evaluate the robustness of a 2D hydrodynamic model (Delft3D‐FLOW 4.01.00; Deltares, 2013) to predict the spatio‐temporal distribution of HMUs in the vicinity of the MGS and analyse patterns in HMU configuration.…”
Section: Methodsmentioning
confidence: 99%
“…In navigable rivers, river bathymetry is typically measured with single beam or multi-beam sonar on-board manned or unmanned vessels (Bio et al, 2020;Halmai et al, 2020;Leyland et al, 2017;Specht et al, 2020;Stateczny et al, 2019;Young et al, 2017). However, sonar systems have limitations in measuring very shallow depths due to surface clutter and multipath effects (Albright Blomberg et al, 2013); furthermore, the accuracy of sonar signi cantly degrades in vegetated rivers (Helminen et al, 2019), indeed the high level of re ection of sound waves from the vegetation can result in depth measurements within vegetation canopy (Sabol, 2002). Additionally, deployment of boats can be time-consuming in remote areas and is limited to navigable water.…”
Section: Sonarmentioning
confidence: 99%