knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
Corresponding author:
Alexey Shiklomanov
NASA Goddard Space Flight Center
alexey.shiklomanov@nasa.gov
Easiest way to install is via install_github
from the devtools
package.
devtools::install_github("ashiklom/pecanrtm")
If you want a specific branch, do install_github(..., ref="<branch>")
.
From there, you should be able to load the package in your typical R session.
NOTE: On some OS X systems, the automatic specification of gfortran
will
fail, causing the installation to abort. To fix this issue, you will need to
add something like the following the ~/.R/Makevars
file.
FC = gfortran
For more information, see the vignette (vignettes/pecanrtm.vignettes.Rmd
).
Simulate leaf reflectance and transmittance with different versions of the PROSPECT model.
library(PEcAnRTM) p4 <- prospect(c(N = 1.4, Cab = 40, Cw = 0.01, Cm = 0.005), version = "4") p5 <- prospect(c(N = 1.4, Cab = 40, Car = 8, Cw = 0.01, Cm = 0.005), version = "5") p5b <- prospect(c( N = 1.4, Cab = 40, Car = 8, Cbrown = 0.1, Cw = 0.01, Cm = 0.005 ), version = "5B") pd <- prospect(c( N = 1.4, Cab = 40, Car = 8, Canth = 10, Cbrown = 0.1, Cw = 0.01, Cm = 0.005 ), version = "D") wl <- seq(400, 2500) plot(0, 0, type = "n", xlim = c(400, 2500), ylim = c(0, 1), xlab = "Wavelength (nm)", ylab = "Reflectance or 1 - Transmittance") lines(wl, p4[, 1], col = 2) lines(wl, 1 - p4[, 2], col = 2, lty = 2) lines(wl, p5[, 1], col = 3) lines(wl, 1 - p5[, 2], col = 3, lty = 2) lines(wl, p5b[, 1], col = 4) lines(wl, 1 - p5b[, 2], col = 4, lty = 2) lines(wl, pd[, 1], col = 5) lines(wl, 1 - pd[, 2], col = 5, lty = 2) legend("topright", c("4", "5", "5B", "D"), col = 2:5, lty = 1)
Simulate canopy reflectance with the PRO4SAIL model (PROSPECT 5B coupled to the 4SAIL canopy RTM).
canopy <- pro4sail(c( N = 1.4, Cab = 40, Car = 8, Cbrown = 0, Cw = 0.01, Cm = 0.009, # Leaf angle distribution function parameters LIDFa = -0.35, LIDFb = -0.15, TypeLIDF = 1, # Leaf area index LAI = 3, # Hot spot parameter q = 0.01, # Solar zenith, degrees tts = 30, # Observer zenith, degrees tto = 10, # Sun-observer azimuth psi = 0, # Soil moisture fraction (0 = dry, 1 = wet) psoil = 0.7 )) matplot(canopy) legend("topright", c("BHR", "HDR", "DHR", "BDR"), col = 1:4, lty = 1:4)
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