NDLI: Mapping of Submerged Aquatic Vegetation Using Autonomous Underwater Vehicles in Nearshore Regions

Content Provider	IEEE Xplore Digital Library
Author	Jones, M.E. Miller, L. Woodruff, D.L. Ewert, D.W.
Copyright Year	2007
Description	Author affiliation: Pacific Northwest Nat. Lab., Marine Res. Oper., Sequim, WA (Jones, M.E.; Miller, L.; Woodruff, D.L.; Ewert, D.W.)
Abstract	The use of an autonomous underwater vehicle (AUV) equipped with sidescan sonar was investigated for determining the boundaries of nearshore submerged aquatic vegetation beds, specifically eelgrass (Zostera marina). Shifts in eelgrass bed morphology, size, and distribution are used as indicators in monitoring programs to measure the impacts of coastal development and environmental stressors on nearshore ecosystem health and to establish the efficacy of restoration programs. However, many monitoring programs necessarily extend over multiple-year time periods. Therefore, techniques that are easily reproducible, accurate, and cost-effective can demonstrate distinct advantages over some of the more traditional and labor-intensive methods, such as diver assessments and transects of shoot counts. Remote monitoring of eelgrass beds using satellite and aerial imagery has been demonstrated with moderate success, but requires groundtruthing, which can be costly and which frequently cannot delineate the deeper boundaries of eelgrass beds. One possible means for low-cost mapping is the use of AUVs equipped with acoustic imaging hardware. AUVs provide an ideal platform, because they can be deployed by small teams (two people), they are highly maneuverable, they can cover large areas over a relatively short time period (3 knot operational speed), and they are equipped with multiple oceanographic instruments for correlated data collection. This paper describes the use of sidescan-equipped AUV technology deployed over multiple time periods at the same location where imagery of eelgrass beds was obtained and analyzed for comparative purposes.
Starting Page	1
Ending Page	7
File Size	3870096
Page Count	7
File Format	PDF
ISBN	9780933957350
DOI	10.1109/OCEANS.2007.4449331
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-29
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	MTS
Subject Keyword	Vegetation mapping Underwater vehicles Sea measurements Remote monitoring Sonar measurements Morphology Stress measurement Size measurement Ecosystems Image restoration
Content Type	Text
Resource Type	Article

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