About

Despite significant recent advances in cloud-based geospatial analysis platforms and free access to immense earth observation archives, global-scale monitoring of many coastal ecosystem types has remained unfeasible. This is largely due to the considerable resources required to develop large, analysis-ready, reference datasets suitable for training and testing remote sensing classification models.

We have developed an open-access reference library of coastal ecosystems suitable for training and verifying the latest generation of remote sensing classification models. coastTrain currently consists of >190,000 point occurrence records of 7 coastal ecosystem types. Absence data is also included (permanent water and other terrestrial data) to enable researchers, modellers and conservation organisations to quickly develop maps of the distribution of coastal ecosystem types.

coastTrain includes training data from several high profile coastal mapping projects, including the Global Tidal Flats project (http://intertidal.app), Global Mangrove Watch (https://www.globalmangrovewatch.org/), Global Tidal Wetlands Change (www.globalintertidalchange.org) and the Allen Coral Atlas (https://allencoralatlas.org/).

A full description of the methods, dataset, usage notes and data updates is provided in the published paper, Zenodo data archive and the coastTrain github repository.

Release notes

9-11-2022

• Version 1.0 of the coastTrain dataset made available via Zenodo data archive. https://doi.org/10.5281/zenodo.7080756

• coastTrain Github repository is live. https://github.com/nick-murray/coastTrain

• The coastTrain manuscript accepted at Remote Sensing.