Abstract
Coral reefs are among the most diverse and iconic ecosystems on Earth, but a range of anthropogenic pressures are threatening their persistence. Owing to their remoteness, broad spatial coverage and cross-jurisdictional locations, there are no high-resolution remotely sensed maps available at the global scale. Here we present a framework that is capable of mapping coral reef habitats from individual reefs (~200 km2) to entire barrier reef systems (200 000 km2) and across vast ocean extents (>6 000 000 km2). This is the first time this has been demonstrated using a consistent and transparent remote sensing mapping framework. The ten maps that we present achieved good accuracy (78% mean overall accuracy) from multiple input image datasets and training data sources, and our framework was shown to be adaptable to either benthic or geomorphic reef features and across diverse coral reef environments. These new generation high-resolution map data will be useful for supporting ecosystem risk assessments, detecting change in ecosystem dynamics and targeting efforts to monitor local-scale changes in coral cover and reef health.
Original language | English (US) |
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Pages (from-to) | 557-568 |
Number of pages | 12 |
Journal | Remote Sensing in Ecology and Conservation |
Volume | 6 |
Issue number | 4 |
DOIs | |
State | Published - Dec 2020 |
Keywords
- Coral reefs
- machine learning
- mapping
- monitoring
- remote sensing
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Ecology
- Computers in Earth Sciences
- Nature and Landscape Conservation