Within the COBECORE project a goal was to quantify the complexity of the canopy in old archival images using the FOTO (Fourier Transform Textural Ordination) method.
FOTO uses a principal component analysis (PCA) on radially averaged 2D Fourier spectra to characterize (grayscale) image texture and was first described by Couteron et al. 2005 to quantify canopy stucture in relation to biomass and biodiversity.
To formalize this routine the approach was converted into an R package and peer-reviewed for inclusion into the Comprehensive R Archive Network (or CRAN). As such the “foto” package can be easily installed in your R working environment using:
The complete documentation and source code of the project can be found on the github page: https://github.com/khufkens/foto.
An example analysis is run below. In the resulting image pixels with a similar colour have a similar texture. The analysis is run on a historical image of plantations near Yangambi, DR Congo, as recovered in the COBECORE project. The regular pattern of planted trees is picked up readily by the algorithm.
# load the library library(foto) # load demo data r <- raster::raster(system.file("extdata", "yangambi.png", package = "foto", mustWork = TRUE)) # classify pixels using zones (discrete steps) output <- foto(r, plot = TRUE, window_size = 25, method = "zones")