The Canopy Radiation Model (CanRad) calculates direct and diffuse shortwave radiation transmission in forest canopies using either airborne lidar data (L2R) or a canopy height model (C2R). An additional module is available that calculates radiation transmission using only terrain data (T2R).
For a detailed description of L2R, see: Webster C, Mazzotti G, Essery E and Jonas T 2020, Enhancing airborne lidar data for improved forest structure representation in shortwave transmission models, Remote Sensing of Environment
L2R is an optimised and improved version of Lidar2HemiEval, which was based on Lidar2Hemi, written in MATLAB.
For a detailed description of C2R, see: Webster, C, Essery E, Mazzotti G and Jonas T, 2023 Using just a canopy height model to obtain lidar-level accuracy in 3D forest canopy shortwave transmissivity estimates, Agricultural and Forest Meteorology
Both models require some additional preperatory steps. Scripts to easily carry out these steps are currently under development to facilitate easy implementation for different sites/users and will be added ~/examples/prep/ as they are completed. In the meantime, please contact the author if you wish to have earlier access.
Both models can be run on an HPC to cover large domains. An example implementation will be added to ~/examples/cluster/. Feel free to contact the author for more information.
CanRad requires SpatialFileIO.jl and the python package scipy.
SpatialFileIO can be added by
]add https://github.com/c-webster/SpatialFileIO.jl
scipy can be added by
]add Conda
using Conda
Conda.add("scipy")
Then add CanRad
]add https://github.com/c-webster/CanRad.jl
Add required packages
]add DelimitedFiles, NCDatasets
Run the test (this will take several minutes)
using CanRad
]test CanRad
Use ~/test/L2R_Settings_test.jl or ~/test/C2R_Settings_test.jl for desired input parameters and file paths. Edit ~/test/run_CanRad_tests.jl