A Peatland Sub-Class Map for the Canadian Boreal Forest
Description
Authors:
Pontone, N., Millard, K., Thompson, D. K., Guindon, L., Beaudoin A. (2024)
Contact:
NicholasPontone@cmail.carleton.ca
Description:
A map of peatland sub-classes (bog, poor fen, rich fen and permafrost peat complex) for the Canadian Boreal Forest circa 2020 created using a three-stage hierarchical classification framework. Training and validation data consisted of peatland locations derived from various sources (field data, aerial photo interpretation, measurements documented in literature). A combination of multispectral data, L-band SAR and C-Band interferometric SAR coherence, forest structure, and ancillary variables were used as model predictors. Ancillary data were used to mask agricultural areas and urban regions, and account for regions that may exhibit permafrost
Pixel Values:
1: Bog
2: Rich Fen
3: Poor Fen
4: Peatland Permafrost Complex
5: Mineral Wetlands
6: Water
7: Upands
8: Agriculture
9: Urban
Recommended Colours
1: 4C0073
2: FFFF00
3: E64C00
4: 727272
5: F4C2C2
6: 0070FF
7: 4C7300
8: 623131
9: 000000
Please cite as:
Pontone, N., Millard, K., Thompson, D.K., Guindon, L. and Beaudoin, A. (2024), A hierarchical, multi-sensor framework for peatland sub-class and vegetation mapping throughout the Canadian boreal forest. Remote Sens Ecol Conserv. https://doi.org/10.1002/rse2.384
This data was released in combination with PALSAR-2 L-band dual-polarized radar backscatter summer composites (circa 2020).
Beaudoin, A., Villemaire, P., Gignac, C., Tolszczuk, S., Guindon, L., Pontone, N., Millard, C. (2024). Canada’s PALSAR-2 dual-polarized L-band radar summer backscatter composite, circa 2020. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/8ec4ee78-9240-4bd0-9c97-d3a27829e209
The peatland map is also available as a Google Earth Engine asset (projects/ee-peatlandthesis/assets/PeatlandMap8b_2023_07_17).
Files
PeatlandMap8b_2023_07_17.tif
Files
(1.3 GB)
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md5:198a456bf5ec2df44eb99fd90c95bf28
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Additional details
Identifiers
- DOI
- 10.1002/rse2.384