Automating drone image processing to map coral reef substrates using Google Earth Engine

Bennett, Mary K., Younes Cardenas, Nicolas, and Joyce, Karen E. (2020) Automating drone image processing to map coral reef substrates using Google Earth Engine. Drones, 4 (3). 50.

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Abstract

While coral reef ecosystems hold immense biological, ecological, and economic value, frequent anthropogenic and environmental disturbances have caused these ecosystems to decline globally. Current coral reef monitoring methods include in situ surveys and analyzing remotely sensed data from satellites. However, in situ methods are often expensive and inconsistent in terms of time and space. High-resolution satellite imagery can also be expensive to acquire and subject to environmental conditions that conceal target features. High-resolution imagery gathered from remotely piloted aircraft systems (RPAS or drones) is an inexpensive alternative; however, processing drone imagery for analysis is time-consuming and complex. This study presents the first semi-automatic workflow for drone image processing with Google Earth Engine (GEE) and free and open source software (FOSS). With this workflow, we processed 230 drone images of Heron Reef, Australia and classified coral, sand, and rock/dead coral substrates with the Random Forest classifier. Our classification achieved an overall accuracy of 86% and mapped live coral cover with 92% accuracy. The presented methods enable efficient processing of drone imagery of any environment and can be useful when processing drone imagery for calibrating and validating satellite imagery.

Item ID: 66718
Item Type: Article (Research - C1)
ISSN: 2504-446X
Keywords: Coral reefs, Drone imagery, Drone mapping, Google Earth Engine, Heron reef, Random forest, Remote sensing, RPAS
Copyright Information: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Date Deposited: 02 Mar 2021 00:43
FoR Codes: 40 ENGINEERING > 4013 Geomatic engineering > 401304 Photogrammetry and remote sensing @ 30%
31 BIOLOGICAL SCIENCES > 3103 Ecology > 310305 Marine and estuarine ecology (incl. marine ichthyology) @ 30%
40 ENGINEERING > 4013 Geomatic engineering > 401302 Geospatial information systems and geospatial data modelling @ 40%
SEO Codes: 18 ENVIRONMENTAL MANAGEMENT > 1805 Marine systems and management > 180501 Assessment and management of benthic marine ecosystems @ 70%
22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220403 Artificial intelligence @ 30%
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