Big Data for a Big Country: The first generation of Canadian wetland inventory map at a spatial resolution of 10-m using Sentinel-1 and Sentinel-2 data on the Google Earth engine cloud computing platform
Document Type
Article
Publication Date
1-27-2020
Department
Michigan Tech Research Institute
Abstract
Detailed information on the spatial distribution of wetlands is crucial for sustainable management and resource assessment. Furthermore, regularly updated wetland inventories are of particular importance given that wetlands comprise a dynamic, rather than permanent, land condition. Accordingly, satellite-derived wetland maps are greatly beneficial, as they capture a synoptic and multi-temporal view of landscapes. Leveraging state-of-the-art remote sensing data and tools, this study produces a high-resolution 10-m wetland inventory map of Canada, covering an approximate area of one billion hectares, using multi-year, multi-source (Sentinel-1 and Sentinel-2) Earth Observation (EO) data on the Google Earth Engine™ cloud computing platform. The whole country is mapped using a large volume of reference samples using an object-based random forest classification scheme with an overall accuracy approaching 80% and individual accuracies varying from 74% to 84% in different provinces. This nationwide wetland inventory map illustrates that 19% of Canada’s land area is covered by wetlands, most of which are peatlands dominate in the northern ecozones. Importantly, the resulting ever-demanding wetland inventory map of Canada provides unprecedented details on the extent, status, and spatial distribution of wetlands and thus, is useful for many stakeholders, including federal and provincial governments, municipalities, NGOs, and environmental consultants.
Publication Title
Canadian Journal of Remote Sensing
Recommended Citation
Mahdianpari, M.,
Salehi, B.,
Mohammadimanesh, F.,
Brisco, B.,
Homayouni, S.,
Gill, E.,
DeLancey, E. R.,
&
Bourgeau-Chavez, L.
(2020).
Big Data for a Big Country: The first generation of Canadian wetland inventory map at a spatial resolution of 10-m using Sentinel-1 and Sentinel-2 data on the Google Earth engine cloud computing platform.
Canadian Journal of Remote Sensing,
46(1), 15-33.
http://doi.org/10.1080/07038992.2019.1711366
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/1695
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