A Seagrass Mapping Toolbox for South Pacific Environments

Bremner, Julie, Petus, Caroline, Dolphin, Tony, Hawes, Jon, Beguet, Benoît, and Devlin, Michelle J. (2023) A Seagrass Mapping Toolbox for South Pacific Environments. Remote Sensing, 15 (3). 834.

[img]
Preview
PDF (Published Version) - Published Version
Available under License Creative Commons Attribution.

Download (75MB) | Preview
View at Publisher Website: https://doi.org/10.3390/rs15030834
 
2
14


Abstract

Seagrass beds provide a range of ecosystem services but are at risk from anthropogenic pressures. While recent progress has been made, the distribution and condition of South Pacific seagrass is relatively poorly known and selecting an appropriate approach for mapping it is challenging. A variety of remote sensing tools are available for this purpose and here we develop a mapping toolbox and associated decision tree tailored to the South Pacific context. The decision tree considers the scale at which data are needed, the reason that monitoring is required, the finances available, technical skills of the monitoring team, data resolution, site safety/accessibility and whether seagrass is predominantly intertidal or subtidal. Satellite mapping is recommended for monitoring at the national and regional scale, with associated ground-reference data where possible but without if time and funds are limiting. At the local scale, satellite, remotely piloted aircraft (RPA), kites, underwater camera systems and in situ surveys are all recommended. In the special cases of community-based initiatives and emergency response monitoring, in situ or satellite/RPA are recommended, respectively. For other types of monitoring the primary driver is funding, with in situ, kite and satellite recommended when finances are limited and satellite, underwater camera, RPA or kites otherwise, dependent on specific circumstances. The tools can be used individually or in combination, though caution is recommended when combining tools due to data comparability.

Item ID: 78423
Item Type: Article (Research - C1)
ISSN: 2072-4292
Keywords: coastal, drone, habitats, Oceania, remote sensing, satellite
Copyright Information: © 2023 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Date Deposited: 17 Oct 2023 22:08
FoR Codes: 41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410402 Environmental assessment and monitoring @ 100%
SEO Codes: 18 ENVIRONMENTAL MANAGEMENT > 1805 Marine systems and management > 180506 Oceanic processes (excl. in the Antarctic and Southern Ocean) @ 100%
Downloads: Total: 14
Last 12 Months: 8
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page