oci: Calculate OCI, the chlorophyll-a algorithm that blends OCx...

In BIO-RSG/oceancolouR: Various Functions for Satellite and Data Analysis

Calculate OCI, the chlorophyll-a algorithm that blends OCx and Hu.

Description

This is the algorithm currently used by NASA for chlor_a (as of April 2021).

Usage

oci(
  rrs,
  sensor = "seawifs",
  use_443nm = TRUE,
  ocx_bands = get_ocx_bands(sensor, use_443nm),
  ocx_coefs = get_ocx_coefs(sensor),
  hu_bands = get_ci_bands(sensor),
  hu_coefs = get_ci_coefs(2),
  CI_bound1 = 0.15,
  CI_bound2 = 0.2
)

Arguments

rrs	Either: Numeric matrix where rows = records, columns = Rrs wavebands, with named columns ("Rrs_XXX", where XXX is a wavelength in nanometres), OR: RasterStack or RasterBrick of rrs layers with stack layers following the same naming convention. Names must match Rrs wavebands used in OCx (blue and green bands) and Hu (blue/green/red bands), from shortest waveband to longest, starting with "Rrs_".
sensor	String, either modisaqua, seawifs, viirssnpp, landsat8, or sentinel2
use_443nm	Logical value, TRUE to make the 443nm band an option in the band ratio (OCx). If false, 443nm will be removed from the list of blue bands before calculating the band ratio. Note that this option does NOT affect hu.
ocx_bands	Sensor-dependent wavebands used in the OCx algorithm - named list of "blues" and "green" bands, e.g. list("blues"=c("Rrs_443","Rrs_488"), "green"="Rrs_547"). See ?get_ocx_bands
ocx_coefs	Numeric vector of coefficients corresponding to terms in the ocx polynomial (lowest degree to highest). See ?get_ocx_coefs
hu_bands	Numeric vector of wavebands (in nanometres) used in the hu algorithm (blue, green, and red, in that order), e.g. c(443,547,667). See ?get_ci_bands
hu_coefs	Numeric vector of coefficients for the hu algorithm. These are NOT sensor-dependent, and there are only two options: 1, for the original set of coefficients, and 2, for a more recent set. See ?get_ci_coefs. Note that these do not start with "Rrs_", but that is added later in the function in order to match them to rrs column names.
CI_bound1	Numeric value, the lower value where blending between OCI and OCX should begin
CI_bound2	Numeric value, the higher value where blending between OCI and OCX should end

Details

If Hu <= CI_bound1, the Hu is used. If it is between the two bounds, Hu and OCx are blended as described in Hu et al (2012).

Default waveband and coefficients are calculated based on sensor and whether or not the 443nm waveband should be used for OCx (note that there will be an error if use443nm=FALSE and 443nm is the only blue band available for the selected sensor).

Value

List containing OCI chlorophyll (For matrix rrs: Numeric value (or vector) – chlorophyll as computed by OCI for the given Rrs. For RasterStack/Brick rrs: equivalent raster with OCI chlorophyll-a), also the indices that were used for Hu and for blending.

References

See ?hu and ?ocx.

Examples

in_situ_chl <- c(0.589,1.835,0.151,5.368,1.715,0.3,5.092,4.132,0.418,0.182,2.075,1.023,5.671,2.153,0.416,0.53,0.88,2.593,1.067,3.01,0.396,2.834,4.019,4.984,1.259,1.875,2.739,0.411,9.533,0.22,0.514,2.279,0.856,2.332,0.421,0.996,0.331,0.266,0.849,2.656,1.746,0.208,1.251,2.019,0.808,2.23,2.073,0.564,0.666,0.122,2.381,1.571,0.183,1.01,0.517,1.568,0.195,1.824,1.153,0.533,2.611,5.901,2.041,0.627,1.261,6.832,1.094,1.053,3.297,1.232)
rrs <- matrix(c(0.0042,0.0036,0.011,0.0047,0.003,0.0072,0.0044,0.0153,0.0058,0.0053,3e-04,0.0052,0.0124,0.0044,0.0066,0.0013,0.0054,0.0064,0.0015,0.0046,0.003,0.004,0.0132,0.0022,0.0022,0.0066,0.0046,0.0067,0.0114,0.0031,0.0135,0.0063,0.006,0.0043,0.0067,0.0035,0.0049,0.0035,0.0022,0.0026,0.014,0.0202,0.0013,0.0015,0.004,0.012,0.0061,0.0101,0.0035,0.0034,0.0045,0.0074,0.0037,0.0025,0.0044,0.0113,0.0019,0.0099,0.0038,0.0158,0.0064,0.0043,0.0059,0.0014,0.0048,0.0042,0.0022,0.0017,0.0025,0.004,0.0046,0.0041,0.0083,0.005,0.0034,0.0071,0.0038,0.0101,0.0096,0.0045,0.0016,0.0048,0.0084,0.0036,0.007,0.0032,0.0054,0.0066,0.002,0.0049,0.0038,0.0042,0.0083,0.0028,0.0032,0.0051,0.0052,0.0062,0.0087,0.0032,0.0082,0.0056,0.0051,0.0045,0.0066,0.0045,0.0052,0.0035,0.0028,0.003,0.0095,0.0128,0.0022,0.0037,0.0042,0.0085,0.0045,0.0085,0.0036,0.0037,0.0055,0.0075,0.0041,0.003,0.0045,0.0096,0.003,0.0068,0.0038,0.0116,0.0057,0.0041,0.0049,0.0022,0.0055,0.0047,0.0037,0.0029,0.0031,0.0043,0.0045,0.0045,0.0042,0.0041,0.0028,0.0034,0.002,0.0056,0.0116,0.0034,0.002,0.0037,0.0052,0.0035,0.0035,0.0032,0.0043,0.0041,0.002,0.0042,0.0034,0.0028,0.0052,0.0039,0.0031,0.0038,0.0031,0.0045,0.0048,0.0027,0.0051,0.003,0.0042,0.0035,0.0034,0.0034,0.0044,0.003,0.0032,0.0028,0.0043,0.0062,0.0028,0.0028,0.0035,0.0045,0.0034,0.0039,0.0023,0.0033,0.005,0.0074,0.0036,0.0035,0.004,0.0049,0.0028,0.0035,0.0032,0.005,0.0033,0.0028,0.0035,0.003,0.0035,0.0041,0.0033,0.0027,0.0029,0.0036,9e-04,9e-04,3e-04,8e-04,4e-04,3e-04,1e-04,8e-04,0.0043,5e-04,2e-04,6e-04,0.0012,8e-04,5e-04,3e-04,8e-04,5e-04,3e-04,8e-04,8e-04,2e-04,7e-04,9e-04,6e-04,5e-04,3e-04,5e-04,5e-04,4e-04,4e-04,4e-04,7e-04,7e-04,3e-04,4e-04,7e-04,5e-04,7e-04,5e-04,5e-04,4e-04,6e-04,4e-04,6e-04,6e-04,1e-04,1e-04,2e-04,5e-04,7e-04,0.0044,8e-04,7e-04,7e-04,5e-04,3e-04,5e-04,5e-04,5e-04,4e-04,2e-04,4e-04,7e-04,4e-04,8e-04,6e-04,3e-04,5e-04,8e-04), ncol=4)
colnames(rrs) <- c("Rrs_443", "Rrs_488", "Rrs_547", "Rrs_667")
lambdas <- get_ocx_bands("modisaqua", use_443nm = TRUE)
chl_oci <- oci(rrs, sensor="modisaqua", ocx_coefs=get_ocx_coefs("modisaqua","nwa","ocx"))
library(ggplot2)
p <- ggplot(data.frame(x=in_situ_chl, y=chl_oci$oci_chl,
                  algorithm=ifelse(chl_oci$hu_ind, "hu", ifelse(chl_oci$blend_ind, "blend", "ocx")))) +
    geom_point(aes(x=x, y=y, color=algorithm)) +
    geom_abline(slope=1, intercept=0) +
    scale_x_log10(limits=c(0.05, 20)) +
    scale_y_log10(limits=c(0.05, 20)) +
    theme_minimal() +
    labs(x="in situ chl", y="satellite chl")
print(p)

# transform rrs matrix into RasterStack, and test it
library(raster)
library(magrittr)
rrs_stack <- stack(lapply(1:4, function(i) raster(matrix(rrs[1:9,i], nrow=3))))
names(rrs_stack) <- colnames(rrs)
chl_raster <- oci(rrs_stack, sensor="modisaqua", ocx_coefs=get_ocx_coefs("modisaqua","nwa","ocx"))$oci_chl
plot(chl_raster)

BIO-RSG/oceancolouR documentation built on April 30, 2024, 7:54 a.m.