Leaf and canopy radiative transfer modeling tools built on PROSPECT-D and SAIL
Project description
xleaf
Leaf and canopy radiative transfer modeling tools built on PROSPECT-D and SAIL.
Introduction
🌳 xleaf
is a python package for running leaf and canopy simulation models using PROSAIL. It provides python bindings to the PROSPECT-D & 4SAIL Fortran code.
🌿 It includes sensible defaults that make it easy to get up and running quickly, and clear code documentation in the form of docstrings and type hints.
📚 All credit for the fundamental modeling code and for the underlying science belongs to the original researchers. Please see their most recent research:
@article{feret2017prospect,
title={PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle},
author={Feret, J-B and Gitelson, AA and Noble, SD and Jacquemoud, S},
journal={Remote Sensing of Environment},
volume={193},
pages={204--215},
year={2017},
publisher={Elsevier}
}
🧙 Shout out to my man JB.
Usage
import xleaf
import matplotlib.pyplot as plt
# run with off-the-shelf defaults
leaf = xleaf.simulate_leaf()
# or specify detailed parameters
canopy = xleaf.simulate_canopy(
chl = 40, # ug/cm2
car = 8, # ug/cm2
antho = 0.5, # ug/cm2
ewt = 0.01, # cm
lma = 0.009, # g/cm2
N = 1.5, # unitless
lai = 3.0, # m2/m2
lidf = 30, # degrees
soil_dryness = 0.75, # %
solar_zenith = 35, # degrees
solar_azimuth = 120, # degrees
view_zenith = 0, # degrees
view_azimuth = 60, # degrees
hot_spot = 0.01, # unitless
)
# and plot them together
plt.plot(xleaf.parameters.wavelengths, leaf, label='leaf')
plt.plot(xleaf.parameters.wavelengths, canopy, label='canopy')
plt.legend()
The definition and expected range of values for each parameter is described in the xleaf
docstrings.
Install
pip install xleaf
This may require a FORTRAN compiler. So on ubuntu you could run sudo apt install gcc
and on macos you'd run brew install gcc
.
Developed by
Christopher Anderson[^1] [^2]
[^1]: Planet Labs PBC, San Francisco [^2]: Center for Conservation Biology, Stanford University
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