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A Peatland Sub-Class Map for the Canadian Boreal Forest

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NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/10627579
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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: Bog2: Rich Fen3: Poor Fen4: Peatland Permafrost Complex5: Mineral Wetlands6: Water7: Upands8: Agriculture9: Urban Recommended Colours 1: 4C00732: FFFF003: E64C004: 7272725: F4C2C26: 0070FF7: 4C73008: 6231319: 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).
创建时间:
2024-07-13
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