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Remote Sens. 2016, 8(1), 48; doi:10.3390/rs8010048

Development of a Regional Coral Observation Method by a Fluorescence Imaging LIDAR Installed in a Towable Buoy

1
National Maritime Research Institute, 6-38-1 Shinkawa, Mitaka, Tokyo 181-0004, Japan
2
National Institute of Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
*
Author to whom correspondence should be addressed.
Academic Editors: Stuart Phinn, Chris Roelfsema, Xiaofeng Li and Prasad S. Thenkabail
Received: 21 September 2015 / Revised: 28 December 2015 / Accepted: 30 December 2015 / Published: 8 January 2016
(This article belongs to the Special Issue Remote Sensing for Coral Reef Monitoring)
View Full-Text   |   Download PDF [2572 KB, uploaded 8 January 2016]   |  

Abstract

Coral bleaching and mortality is predicted to increase under global climate change. A new observation technique is required to monitor regional coral conditions. To this end, we developed a light detection and ranging (LIDAR) system installed in a towable buoy for boat observations, which acquires continuous fluorescent images of the seabed during day-time. Most corals have innate fluorescent proteins in their tissue, and they emit fluorescence by ultraviolet excitation. This fluorescence distinguishes living coral from dead coral skeleton, crustose coralline algae, and sea algae. This paper provides a proof of concept for using the LIDAR system and fluorescence to map coral distribution within 1 km scale and coral cover within 100 m scale for a single reef in Japan. View Full-Text
Keywords: coral; fluorescence; ultraviolet; laser; LIDAR coral; fluorescence; ultraviolet; laser; LIDAR
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sasano, M.; Imasato, M.; Yamano, H.; Oguma, H. Development of a Regional Coral Observation Method by a Fluorescence Imaging LIDAR Installed in a Towable Buoy. Remote Sens. 2016, 8, 48.

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