Automating Drone Image Processing to Map Coral Reef Substrates Using Google Earth Engine

Mary K Bennett,Karen Joyce,Nicolas Younes

doi:10.3390/drones4030050

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.

Highlights

When the Great Barrier Reef Marine Park Authority released its 2019 Outlook Report, the Authority reported the greatest threat to the Great Barrier Reef was climate change [1]
The objective of this study is to present a distributable, semi-automated workflow using Google Earth Engine (GEE) to substrate classification, and classification accuracy assessment usingfor andimage free and open source classify coral reef substrates in drone imagery
We produced a substrate classification of Heron Reef, Australia, with an overall mapping accuracy of 86%, which maps coral cover with 92% accuracy

Summary

Introduction

When the Great Barrier Reef Marine Park Authority released its 2019 Outlook Report, the Authority reported the greatest threat to the Great Barrier Reef was climate change [1]. Dynamical and statistical models and projections demonstrate that climate change is likely to increase the intensity of extreme weather events including tropical cyclones [2], contribute to sea level rise, and increase sea surface temperatures [3]. Each of these aspects pose significant challenges for coral reef environments, and the increasing frequency of mass bleaching events brought on by warmer water temperatures alone threatens the resiliency and survival of reefs worldwide [4,5].

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