Google Earth Engine, Open-Access Satellite Data, and Machine Learning in Support of Large-Area Probabilistic Wetland Mapping
Published: Dec 13, 2017
Description: This journal article discusses a workflow for predicting the occurrence of wetlands on the landscape at a regional scale using Earth-observation data. When the probability-of-occurrence model is converted into a wet-dry classification, the model yields an overall accuracy of 85%. Given this accuracy, it provides a scalable foundation for province wide monitoring initiatives in Alberta.
Document Type:
Peer-reviewed Publications - ABMI-authored
Subject Area:
Remote Sensing,
Mapping
Citation:
Alberta Biodiversity Monitoring Institute. 2017.
Google Earth Engine, Open-Access Satellite Data, and Machine Learning in Support of Large-Area Probabilistic Wetland Mapping.
Available at: https://abmi.ca/publication/507.html
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Document Type:
Peer-reviewed Publications - ABMI-authored
Subject Area:
Remote Sensing,
Mapping
Citation:
Alberta Biodiversity Monitoring Institute. 2017.
Google Earth Engine, Open-Access Satellite Data, and Machine Learning in Support of Large-Area Probabilistic Wetland Mapping.
Available at: https://abmi.ca/publication/507.html