read_caim: Read a canopy image from a file

In rcaiman: CAnopy IMage ANalysis

Read a canopy image from a file

Description

Wrapper function for terra::rast().

Usage

read_caim(path = NULL, upper_left = NULL, width = NULL, height = NULL)

Arguments

path	Character vector of length one. Path to an image, including file extension. The function will return a data example if no arguments are provided.
upper_left	An integer vector of length two. The pixels coordinates of the upper left corner of a region of interest (ROI). These coordinates should be in the raster coordinates system. This system works like a spreadsheet, i.e, when going down through the vertical axis, the row number increases (IMPORTANT: column and row must be provided instead of row and column, as is the norm for objects from the class data.frame and others alike)
width, height	An integer vector of length one. The size of the boxy ROI whose upper left corner is the upper_left argument.

Details

Run read_caim() to obtain an example of a hemispherical photo taken in non-diffuse light conditions in a Nothofagus pumilio forest with a FC-E9 auxiliary lens attached to a Nikon Coolpix 5700.

Since this function aims to read born-digital color photographs, RGB-JPEG and RGB-TIFF are the expected input. However, since this function is a wrapper for terra::rast(), format compatibility is heritages from it.

Use upper_left, width, and height to read a particular region from the file. Although any image editor can be used to obtain those parameters, this function was tested with ‘ImageJ’, so it might be wise to use it.

TIP: For obtaining upper_left, width, and height, open the image on the Fiji distro of ImageJ, draw a rectangular selection, and go to Edit>Selection>Specify. The same workflow may work with other distros.

Value

An object from class SpatRaster with its layers named Red, Green, and Blue when a born-digital color photographs is provided as input.

Note

The example image was obtained with this code:

zenith_colrow <- c(1290, 988)
z <- zenith_image(745*2, lens("Nikon_FCE9"))
a <- azimuth_image(z)
r <- read_caim_raw("DSCN4606.NEF", z, a, zenith_colrow, radius = 300)
z <- zenith_image(ncol(r), lens())
r <- correct_vignetting(r, z, c(0.0638, -0.101))
r <- c(mean(r$Y, r$M), r$G, r$C)
r <- normalize(r, -1)
write_caim(r*2^16-2, "example.tif", 16)

See Also

Other Tool Functions: colorfulness(), correct_vignetting(), defuzzify(), extract_dn(), extract_feature(), extract_rl(), extract_sky_points_simple(), extract_sky_points(), extract_sun_coord(), find_sky_pixels_nonnull(), find_sky_pixels(), masking(), optim_normalize(), percentage_of_clipped_highlights(), read_bin(), read_caim_raw(), write_bin(), write_caim()

Examples

path <- system.file("external/DSCN4500.JPG", package = "rcaiman")
zenith_colrow <- c(1250, 1020)
diameter <- 745*2
caim <- read_caim(path, zenith_colrow - diameter/2, diameter, diameter)
plot(caim$Blue)

rcaiman documentation built on Nov. 15, 2023, 1:08 a.m.