The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21363081

Camile Sothe; Alemu Gonsamo; James Snider; Ricardo B. Lourenço; Werner A. Kurz (2022): Spatially continuous canopy height maps of forested ecosystems of Canada. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21363081.v1

Dataset

• Forestry Sciences

canopy height distribution, GEDI, ICESat-2, LiDAR analysis

2020

CC BY 4.0

• Carbon storage and distribution in terrestrial ecosystems of Canada

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by Camile Sothe , Alemu Gonsamo , James Snider, Ricardo B. Lourenço, Werner A. Kurz

  This dataset contains two canopy height maps from forested ecosystems of Canada at 250m spatial resolution — one using information from the spaceborne LiDAR GEDI, and the other from ICESat-2. GEDI and ICESat-2 are particular in acquiring canopy height information in Canada — the former providing more accurate information of vegetation, yet not reaching full coverage in Canada, whilst the latter is not specifically designed to provide vegetation information but has a global coverage. We created wall-to-wall maps using ATL08 LiDAR product from the ICESat-2 satellite, and GEDI L2A from GEDI. The data were download for the mid growing season (June and August 2020). Points were filtered regarding solar background noise and atmospheric scattering, totaling 208,554 points from ICESat-2, and 1,249,354 points for GEDI after filtering and point thinning. These points were associated with 14 ancillary variables primarily corresponding to structure information, such as seasonal Sentinel-1 VV and VH polarization, seasonal Sentinel-2 red and NIR bands, and annual PALSAR-2 HH and HV polarization. Afterwards, the random forest algorithm was used to extrapolate LiDAR observations and develop regression models with the abovementioned spatially continuous variables. GEDI had a better performance than ICESat-2 with a mean difference (MD) of 0.9 m and 2.9 m in relation to ALS data used for validation, and a root mean square error (RMSE) of 4.2 m and 5.2 m, respectively. However, as both GEDI and ALS have no coverage in most of the hemi-boreal forests, ICESat-2 captures the tall canopy heights expected for these forests better than GEDI.

• 2022-10-20 first online, published, posted

4TU.ResearchData

tif

Spatially Continuous Mapping of Forest Canopy Height in Canada by Combining GEDI and ICESat-2 with PALSAR and Sentinel

• NSERC Alliance Grant (ALLRP 566310-21)
• NSERC Discovery Grant (RGPIN-2020-05,708)
• WWF Canada
• Canada Research Chairs Program

McMaster University
WWF Canada