Performs root turnover analysis for either a single multi-layer image or two separate images
Usage
root_turnover(
img1,
img2 = NULL,
method = "kimura",
unit = "cm",
dpi = 300,
select.layer = NULL,
product.layer = 2,
decay.layer = 1,
blur.capture = 0.95,
im.return = FALSE,
include.virtualroots = FALSE
)Arguments
- img1
Primary SpatRaster input (either multi-layer or first timepoint image)
- img2
Optional second timepoint image (if img1 is single timepoint)
- method
Analysis method: "kimura", "rootpx", or "dpc" (root decomposition)
- unit
Unit of root length measurement (only for method = "kimura"). Default: "cm"
- dpi
Image resolution (only for method = "kimura"). Default: 300
- select.layer
Integer or NULL. When two images are provided with multiple layers, specifies which layer to use. When img1 is multi-layer, ignored for DPC method.
- product.layer
Integer indicating the production layer index for DPC method (1-3)
- decay.layer
Integer indicating the decay & tape layer index for DPC method (1-3)
- blur.capture
Threshold for pixel inclusion in DPC method (0-1). Default: 0.95
- im.return
Logical: return images instead of values for DPC method? Default: FALSE
- include.virtualroots
Logical: consider all roots present at any timepoint in DPC method? Default: FALSE
Value
Depends on method and parameters: - For temporal comparison: data.frame with root production and turnover - For DPC method: tibble with pixel sums and ratios or list of SpatRaster layers