mosaic_analyze_iter: Analyze mosaics iteratively

Description

High-resolution mosaics can take a significant amount of time to analyze, especially when segment_individuals = TRUE is used in mosaic_analyze(). This is because the function needs to create in-memory arrays to segment individual using the watershed algorithm. This process utilizes a for-loop approach, iteratively analyzing each shape within the mosaic one at a time. To speed up processing, the function crops the original mosaic to the extent of the current shape before analyzing it. This reduces the resolution for that specific analysis, sacrificing some detail for faster processing.

Usage

mosaic_analyze_iter(
  mosaic,
  shapefile,
  basemap = NULL,
  r = 3,
  g = 2,
  b = 1,
  re = NA,
  nir = NA,
  swir = NA,
  tir = NA,
  plot = TRUE,
  verbose = TRUE,
  max_pixels = 3e+06,
  attribute = NULL,
  summarize_fun = "mean",
  segment_plot = FALSE,
  segment_individuals = FALSE,
  segment_index = "VARI",
  plot_index = "VARI",
  color_regions = rev(grDevices::terrain.colors(50)),
  alpha = 0.75,
  quantiles = c(0, 1),
  parallel = FALSE,
  workers = NULL,
  ...
)

Value

A list containing the following objects:

result_plot: The results at a plot level.
result_plot_summ: The summary of results at a plot level. When segment_individuals = TRUE, the number of individuals, canopy coverage, and mean values of some shape statistics such as perimeter, length, width, and diameter are computed.
result_individ: The results at an individual level.
map_plot: An object of class mapview showing the plot-level results.
map_individual: An object of class mapview showing the individual-level results.

Arguments

mosaic: A mosaic of class SpatRaster, generally imported with mosaic_input().
shapefile: An optional shapefile containing regions of interest (ROIs) for analysis.
basemap: An optional basemap generated with mosaic_view().
r, g, b, re, nir, swir, tir: The red, green, blue, red-edge, near-infrared, shortwave Infrared, and thermal infrared bands of the image, respectively. By default, the function assumes a BGR as input (b = 1, g = 2, r = 3). If a multispectral image is provided up to seven bands can be used to compute built-in indexes. There are no limitation of band numbers if the index is computed using the band name.
plot: Logical, indicating whether to generate plots (default: TRUE).
verbose: Logical, indicating whether to display verbose output (default: TRUE).
max_pixels: Maximum number of pixels to render in the map or plot (default: 500000).
attribute: The attribute to be shown at the plot when plot is TRUE. Defaults to the first summary_fun and first segment_index.
summarize_fun: The function to compute summaries for the pixel values. Defaults to "mean," i.e., the mean value of the pixels (either at a plot- or individual-level) is returned.
segment_plot: Logical, indicating whether to segment plots (default: FALSE). If TRUE, the segment_index will be computed, and pixels with values below the threshold will be selected.
segment_individuals: Logical, indicating whether to segment individuals within plots (default: FALSE). If TRUE, the segment_index will be computed, and pixels with values below the threshold will be selected, and a watershed-based segmentation will be performed.
segment_index: The index used for segmentation. The same rule as plot_index. Defaults to NULL
plot_index: The index(es) to be computed for the drawn plots. Either a single vegetation index (e.g., "GLAI"), a vector of indexes (e.g., c("GLAI", "NGRDI", "HUE")), or a custom index based on the available bands (e.g., "(R-B)/(R+B)"). See pliman_indexes() and image_index() for more details.
color_regions: The color palette for regions (default: rev(grDevices::terrain.colors(50))).
alpha: opacity of the fill color of the raster layer(s).
quantiles: the upper and lower quantiles used for color stretching.
parallel: If TRUE processes the images asynchronously (in parallel) in separate R sessions running in the background on the same machine. It may speed up the processing time, especially when pattern is used is informed. When object_index is informed, multiple sections will be used to extract the RGB values for each object in the image. This may significantly speed up processing time when an image has lots of objects (say >1000).
workers: A positive numeric scalar or a function specifying the number of parallel processes that can be active at the same time. By default, the number of sections is set up to 30% of available cores.
...: Further arguments passed on to mosaic_analyze()