Bathymetry Derivatives and Habitat Data from Hyperspectral Imagery Establish a High-Resolution Baseline for Managing the Ningaloo Reef, Western Australia.

Bibliographic Details
Title: Bathymetry Derivatives and Habitat Data from Hyperspectral Imagery Establish a High-Resolution Baseline for Managing the Ningaloo Reef, Western Australia.
Authors: Kobryn, Halina T.1 (AUTHOR) h.kobryn@murdoch.edu.au, Beckley, Lynnath E.1 (AUTHOR), Wouters, Kristin1 (AUTHOR)
Source: Remote Sensing. Apr2022, Vol. 14 Issue 8, pN.PAG-N.PAG. 19p.
Subject Terms: *REEFS, *WORLD Heritage Sites, *ECOLOGICAL surveys, *BATHYMETRY, *TOPOGRAPHIC maps
Geographic Terms: WESTERN Australia
Abstract: The Ningaloo Reef, Australia's longest fringing reef, is uniquely positioned in the NW region of the continent, with clear, oligotrophic waters, relatively low human impacts, and a high level of protection through the World Heritage Site and its marine park status. Non-invasive optical sensors, which seamlessly derive bathymetry and bottom reflectance, are ideally suited for mapping and monitoring shallow reefs such as Ningaloo. Using an existing airborne hyperspectral survey, we developed a new, geomorphic layer for the reef for depths down to 20 m, through an object-oriented classification that combines topography and benthic cover. We demonstrate the classification approach using three focus areas in the northern region of the Muiron Islands, the central part around Point Maud, and Gnaraloo Bay in the south. Topographic mapping combined aspect, slope, and depth into 18 classes and, unsurprisingly, allocated much of the area into shallow, flat lagoons, and highlighted narrow, deeper channels that facilitate water circulation. There were five distinct geomorphic classes of coral-algal mosaics in different topographic settings. Our classifications provide a useful baseline for stratifying ecological field surveys, designing monitoring programmes, and assessing reef resilience from current and future threats. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Academic Search Complete
Full text is not displayed to guests.
More Details
ISSN:20724292
DOI:10.3390/rs14081827
Published in:Remote Sensing
Language:English