In GastonMauroDiaz/caiman: Canopy Image Analysis

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)

caiman

CAnopy IMage ANalysis

Description

Caiman uses the functionalities of the packages raster and EBImage to provide algorithms specially developed to process photographs of the plant canopy.

Canopy structure can be estimated using gap fraction (GF) data, which can be directly measured with hemispherical photography. However, GF data accuracy is affected by sunlit canopy, multiple scattering, vignetting, blooming, and chromatic aberration. The caiman package implement the algorithm presented in IEEE Geoscience and Remote Sensing Letters, whose aim is to reduce errors in the extraction of Gap Fraction data. The target errors are those that are produced by sunlit canopy, multiple scattering, vignetting, blooming, and chromatic aberration.

On the other hand, this package has functions to obtain unbiased estimation of GF with high angle resolution in carefully acquired hemispherical photographs. You can read the research here: http://www.nrcresearchpress.com/doi/full/10.1139/cjfr-2018-0006.

How to use caiman

---

The main function of caiman package is doOBIA. Use it to get binarized images for extracting gap fraction, and estimating forest structure or understory light transmission. After binarization, you will need to continue the proccess with specific software as CIMES.

This document shows you how to use a simple script for processing all the hemispherical photographs in an input directory with doOBIA (batch processing).

If you are a frequently user of R, probably you do not need to read this vignette.

Script for batch processing

I assume that you take upward looking hemispherical photographs, whit the optical axis aligned with the zenith (leveled). Also, I assume that the equipment gives you a circular picture inside the rectangular frame (i.e., is not a full-frame equipment) in JPEG format.

In the root of your c disk create a folder named folder_in and copy your photographs there. Also, create a folder named folder_out.

Run this code:

path_in <- "c:/folder_in" # Please edit it (Do not use / at the end of the string)
path_out <- "c:/folder_out"

listofpics <- list.files(path_in, pattern = ".jpg", ignore.case = TRUE)

for (i in unique(listofpics)) {
  # see the help of loadPhoto with ?loadPhoto. 
  # Maybe you need to use the arguments upperLeft, width and height.
  x <- loadPhoto(paste0(path_in, "/", i))
  fisheye(x) <- newFishEye(TRUE, TRUE, FALSE)
  x <- normalize(x, 0, 255)
  # Here, I assume that your lens has perfect polor projection.
  z <- makeZimage(ncol(x), lensPolyCoef())
  m <- doMask(z)
  bin <- autoThr(enhanceHP(x, m, sharpen = FALSE))
  # This takes a while but you can see the progres
  seg <- doPolarQtree(x, z, scaleParameter = 0.2)
  name <- strsplit(i, "\\.")[[1]][1]
  out <- doOBIA(x, bin, z, seg, zlim = asAngle(c(20, 80)))
  writeRaster(out * 255, paste0(path_out, "/", name, ".TIF"), datatype = "INT1U", overwrite = TRUE)
}

Wait… The result will be written in c:/folder_out whit the same name of the original photo.

How to install caiman

---

You can install caiman package in your system using devtools package from CRAN. Make sure you have devtools installed, if not run install.packages("devtools") in the console. Next, run devtools::install_github("GastonMauroDiaz/caiman").

Probably, you do not have installed the dependent packages EBImage. This is a package in the BioConductor repository, follow the link to get full instruction about how to install BioConductor packages or run:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("EBImage")

If you have any problem, please contact me: gastonmaurodiaz[at]gmail.com

GastonMauroDiaz/caiman documentation built on Jan. 22, 2022, 4:43 a.m.