pacu (version 0.1.74)

pa_compute_vi: Compute vegetation indices from a zipped Sentinel 2 file

Description

Compute vegetation indices from a zipped Sentinel 2 file.

Usage

pa_compute_vi(
  satellite.images,
  vi = c("ndvi", "ndre", "gcvi", "reci", "evi", "bsi", "other"),
  aoi = NULL,
  formula = NULL,
  check.clouds = FALSE,
  buffer.clouds = 100,
  downscale.to = NULL,
  pixel.res = c("default", "10m", "20m", "60m"),
  img.formats = c("jp2", "tif"),
  fun = function(x) mean(x, na.rm = TRUE),
  verbose = TRUE
)

Value

an object of class veg.index and stars

Arguments

satellite.images

list of file paths to the Sentinel 2 zip files

vi

the vegetation index to be computed

aoi

NULL or an sf object used to crop the vegetation index raster to an area of interest

formula

an optional two-sided formula with the vegetation index name on the left side and the relationship between the bands on the right side. See example.

check.clouds

whether to check for clouds over the area of interest. If clouds are found, the function will skip cloudy images.

buffer.clouds

distance in meters around the area of interest within a cloud would be considered to interfere with the index calculation. This is useful to eliminate the effect of cloud shading from the analysis.

downscale.to

the resolution in meters to downscale the resolution of the vegetation index raster layer

pixel.res

pixel resolution used to compute the vegetation index. Can be one of 10m, 20m, 30m

img.formats

image formats to search for in the zipped file

fun

function to be applied to consolidate duplicated images

verbose

whether to display information on the progress of operations

Author

Caio dos Santos and Fernando Miguez

Details

This is script that unzips the Sentinel 2 zipped file into a temporary folder, searches for the index-relevant bands, and then computes the index. If no ‘aoi’ is provided, the script will compute the vegetation index for the area covered by the image. The pre-specified vegetation indices are computed as follows: $$BSI = \frac{(SWIR + RED) - (NIR + BLUE)}{(SWIR + RED) + (NIR + BLUE)}$$ $$EVI = \frac{2.5 \times (NIR - RED)}{(NIR + (6 \times RED) - (7.5 \times BLUE) - 1) }$$ $$GCVI = \frac{(NIR)}{(GREEN)} - 1$$ $$NDRE = \frac{(NIR - RED edge)}{(NIR + RED edge)}$$ $$NDVI = \frac{(NIR - RED)}{(NIR + RED)}$$ $$RECI = \frac{(NIR)}{(RED edge)} - 1$$

The user can also specify custom vegetation indices using the formula argument. The formula should be two-sided, with the left side naming the vegetation index and the right side defining the mathematical operations used to calculate the vegetation index. The bands should be specified as B01, B02, ..., B12.

An important detail of this function is that, if there are duplicated dates, the function will consolidate the data into a single raster layer. The default behavior is to average the layers that belong to the same date. This can be changed with the 'fun' argument.

Examples

# \donttest{
extd.dir <- system.file("extdata", package = "pacu")
## List of zipped Sentinel files in a directory
s2a.files <- list.files(extd.dir, '\\.zip', full.names = TRUE)
area.of.interest <- sf::st_read(file.path(extd.dir, 'cobs_a_aoi.shp'))

## computing ndvi
ndvi <- pa_compute_vi(satellite.images = s2a.files,
                            vi = 'ndvi',
                            aoi = area.of.interest,
                            check.clouds = TRUE)

## computing ndre
ndre <- pa_compute_vi(satellite.images = s2a.files,
                            vi = 'ndre',
                            aoi = area.of.interest,
                            check.clouds = TRUE)

## specifying a differente vegetation index, in this case, the 
## excess green index
egi <- pa_compute_vi(satellite.images = s2a.files,
                            vi = 'other',
                            formula = EGI ~ (2 * B03) - B02 - B04,
                            aoi = area.of.interest,
                            check.clouds = TRUE)
# }