canopyboard/als-chm-1m-tmp

1 m Canopy Height Models — Panama and Mexico

Canopy height models (CHM) at 1 m resolution, as Cloud-Optimized GeoTIFFs (COGs), derived from airborne laser scanning. Values are canopy height in metres above ground; nodata is NaN.

chm/1m/forestgeo/<site>/2023/tin/     Panama, 7 sites
chm/1m/ncalm/usumacinta/2019/tin/     Mexico

CHM algorithm

Point clouds were processed to 1m resolution CHMs with the TIN algorithm — a Delaunay triangulation of first returns.

TIN was selected as a default algorithm in order to ensure CHM consistency across different sensors, platforms, and biomes. Fischer et al. (2024) found that two algorithms produced CHMs that are most robust to differences in pulse density: TIN and an adaptive variant on the 'spikefree' algorithm.

Fischer, F.J., Jackson, T., Vincent, G. & Jucker, T. (2024). Robust characterisation of forest structure from airborne laser scanning — A systematic assessment and sample workflow for ecologists. Methods in Ecology and Evolution, 15, 1873–1888. 10.1111/2041-210X.14416

Source data, licence and citation

Both source airborne lidar acquisitions are CC BY 4.0, and these CHMs are released under the same licence. Attribution is a condition of use.

Panama — chm/1m/forestgeo/

Smithsonian ForestGEO (2024). 2023 high-resolution airborne LiDAR data for Barro Colorado Island and other Smithsonian ForestGEO Sites in Central Panama. Smithsonian DataONE. 10.60635/C3F593. CC BY 4.0.

Principal investigator Helene C. Muller-Landau (Smithsonian Tropical Research Institute). Flown 26–27 May 2023 by Stereocarto using an IGI LiteMapper 6800i with a Riegl LMS-Q680 sensor, at 20.31 shots m⁻², from a Bell 206 JR III. Funded by Smithsonian ForestGEO and NASA Jet Propulsion Laboratory.

Mexico — chm/1m/ncalm/usumacinta/

Middle Usumacinta Archaeological Project (2019). Lidar survey of the Middle Usumacinta region, Mexico (MX19_Inomata). Collected by the National Center for Airborne Laser Mapping (NCALM) for Takeshi Inomata, University of Arizona. Distributed by OpenTopography. CC BY 4.0.

Reading a single plot

The 1m CHMs are COGs. An arbitrary window can be read over HTTP without downloading the file:

import rasterio
from rasterio.windows import from_bounds

url = ("https://huggingface.co/datasets/canopyboard/als-chm-1m-tmp/resolve/main/"
       "chm/1m/forestgeo/gigante/2023/tin/"
       "FORESTGEO_gigante_2023_625000_1006000_chm_1m.tif")
with rasterio.open(url) as src:
    window = from_bounds(625100, 1006100, 625200, 1006200, src.transform)
    heights = src.read(1, window=window)

Or you can download the whole set:

huggingface-cli download canopyboard/als-chm-1m-tmp --repo-type dataset --local-dir ./chm