Assessing the Effectiveness of Seagrass Detection Using Drone and Sonar Based Methods-Reference-Cited by-同舟云学术

Assessing the Effectiveness of Seagrass Detection Using Drone and Sonar Based Methods

Published:2023-09-25 Issue: Volume: Page:
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Container-title:OCEANS 2023 - MTS/IEEE U.S. Gulf Coast
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Author:

Biber Patrick¹,Oguntuase Johnson²,Raber George³,Waldron Margaret¹

Affiliation:

1. The University of Southern Mississippi,Dep't of Coastal Science,Ocean Springs,USA

2. The University of Southern Mississippi,Dep't of Marine Science,Stennis,USA

3. The University of Southern Mississippi,Dep't of Geology and Geography,Hattiesburg,USA

Funder

University of Southern Mississippi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10336884/10336949/10337091.pdf?arnumber=10337091

Reference20 articles.

1. Calibration of a Bio-optical Model in the North River, North Carolina (Albemarle–Pamlico Sound): A Tool to Evaluate Water Quality Impacts on Seagrasses

2. PING‐Mapper: Open‐Source Software for Automated Benthic Imaging and Mapping Using Recreation‐Grade Sonar

3. Historical changes in seagrass coverage on the Mississippi barrier islands, northern Gulf of Mexico, determined from vertical aerial imagery (1940–2007)

4. Short-term spatial variations in the beds of Ruppia maritima (Ruppiaceae) and Halodule wrightii (Cymodoceaceae) at Grand Bay National Estuarine Research Reserve, Mississippi, USA;Cho;Journal of the Mississippi Academy of Sciences,2008

5. A study of seagrass at Grand Bay National Estuarine Research Reserve, Mississippi;Cho,2009

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1. Automated River Substrate Mapping From Sonar Imagery With Machine Learning;Journal of Geophysical Research: Machine Learning and Computation;2024-07-09