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The reproducibility of remotely piloted aircraft systems to monitor seasonal variation in submerged seagrass and estuarine habitats

Authors :
T.S. Prystay
G. Adams
B. Favaro
R.S. Gregory
A. Le Bris
Source :
FACETS, Vol 8, Iss , Pp 1-22 (2023)
Publication Year :
2023
Publisher :
Canadian Science Publishing, 2023.

Abstract

Seasonal variation in seagrass growth and senescence affects the provision of ecosystem services and restoration efforts, requiring seasonal monitoring. Remotely piloted aircraft systems (RPAS) enable frequent high-resolution surveys at full-meadow scales. However, the reproducibility of RPAS surveys is challenged by varying environmental conditions, which are common in temperate estuarine systems. We surveyed three eelgrass (Zostera marina) meadows in Newfoundland, Canada, using an RPAS equipped with a three-color band (red, green, blue [RGB]) camera, to evaluate the seasonal reproducibility of RPAS surveys and assess the effects of flight altitude (30–115 m) on classification accuracy. Habitat percent cover was estimated using supervised image classification and compared to corresponding estimates from snorkel quadrat surveys. Our results revealed inconsistent misclassification due to environmental variability and low spectral separability between habitats. This rendered differentiating between model misclassification versus actual changes in seagrass cover infeasible. Conflicting estimates in seagrass and macroalgae percent cover compared to snorkel estimates could not be corrected by decreasing the RPAS altitude. Instead, higher altitude surveys may be worth the trade-off of lower image resolution to avoid environmental conditions shifting mid-survey. We conclude that RPAS surveys using RGB imagery alone may be insufficient to discriminate seasonal changes in estuarine subtidal vegetated habitats.

Details

Language :
English
ISSN :
23711671
Volume :
8
Issue :
1-22
Database :
Directory of Open Access Journals
Journal :
FACETS
Publication Type :
Academic Journal
Accession number :
edsdoj.8f8fbf717fe34f29a67046c6df381b5a
Document Type :
article
Full Text :
https://doi.org/10.1139/facets-2022-0149