Large-scale probabilistic identification of boreal peatlands using Google Earth Engine, open-access satellite data, and machine learning
Published: Jun 16, 2019
Description: Freely available high resolution satellite imagery has made frequent, large-scale landcover mapping a reality. This publication uses Google Earth Engine, a fusion of satellite data, and machine learning to map peatland probability across the boreal region of Alberta. Results are promising in terms of accuracy and reproducibility.
Document Type:
Peer-reviewed Publications - ABMI-authored,
Biodiversity Research and Science Development - Geospatial Research
Subject Area:
Mapping,
Remote Sensing,
Boreal Region
Citation:
Alberta Biodiversity Monitoring Institute. 2019.
Large-scale probabilistic identification of boreal peatlands using Google Earth Engine, open-access satellite data, and machine learning.
Available at: https://abmi.ca/publication/539.html
Share this publication
Document Type:
Peer-reviewed Publications - ABMI-authored,
Biodiversity Research and Science Development - Geospatial Research
Subject Area:
Mapping,
Remote Sensing,
Boreal Region
Citation:
Alberta Biodiversity Monitoring Institute. 2019.
Large-scale probabilistic identification of boreal peatlands using Google Earth Engine, open-access satellite data, and machine learning.
Available at: https://abmi.ca/publication/539.html
Share this publication
