Radiance and Reflectance spectra of Standard Reference Target under different lab illuminators

• Agustin.Lobo@geo3bcn.csic.es
• 20230717

Goal: Assess the effect of different illuminators on reflectance readings of the Standard Reference Target

require(ggplot2)
require(plotly)
library(RColorBrewer)
require(prospectr)
library(soilspec)
#NOTE: there is also asdreader::get_spectra() (see EspCrater_FS3_nb.Rmd)

# > getwd()
# [1] "/media/alobo/DecepNTFS2/HSI_Lab/Testllum_20230717/Rtestllum_20230717"

dirRSpect <- "/home/alobo/owncloudRSpect/RSpect"
dirdat20230717 <- "../TestllumStdRef_20230717"

1. Reading data

#testllum_20230717_samples.csv created in datadoc_log.R
#edited to become "testllum_20230717_samples_v2.csv"

f <- read.csv(file.path(dirdat20230717,"testllum_20230717_samples_v2.csv"), stringsAsFactors = FALSE)
f$ID <- paste0(f$type,"_",f$replicate)
f <- na.omit(f)
#f <- f[f$target=="StdRef",]

certif <- read.csv(file.path(dirRSpect,"RefMCAA01.csv"), stringsAsFactors = FALSE)

2. Build data frame (long format)

d.lf <-  NULL
for (i in 1:nrow(f)) {
  r <- readASD(file.path(dirdat20230717,f$file[i]), out_format = 'list')[[1]]$radiance
  rf <- readASD(file.path(dirdat20230717,f$file[i]), out_format = 'list')[[1]]$reference
  s <- readASD(file.path(dirdat20230717,f$file[i]), out_format = 'list')[[1]]$reflectance
  w <- readASD(file.path(dirdat20230717,f$file[i]), out_format = 'list')[[1]]$wavelength
  #sc <- spliceCorrection(s,wav=w, splice = c(1000, 1800))
  d.lf <- rbind(d.lf,data.frame(f[i,],w,r,rf,s))
  #d <- cbind(d,)
}
head(d.lf,3)

3. Spectra acquired under each illumination type

dW.lf <- d.lf[d.lf$target=="W",]
dStdR.lf <- d.lf[d.lf$target=="StdRef",]

3.1 White Reference

gW <- ggplot(data=dW.lf) +
  geom_line(aes(x=w, y=r, color=type, group=file), linewidth=0.3) +
  #geom_point(aes(x=Wavelength, y=Reflectance,color=site, group=file)) +
  xlab("Wavelength") + ylab("Radiance") + 
  scale_color_brewer(palette = "Set1") +
  theme(legend.position="bottom")
ggplotly(gW + ggtitle("White Reference Target"))

g1 <- ggplot(data=d.lf) +
  geom_line(aes(x=w, y=r, color=type, linetype=target,group=file), linewidth=0.3) +
  xlab("Wavelength") + ylab("Radiance") + 
  scale_color_brewer(palette = "Set1") +
  ggtitle("White (W) and Standard (StdRef) Reference Target") +
  facet_wrap(~type,nrow=3)
print(g1)

Note that in some parts of the spectra acquired under PROLAMP illumination, the radiance of the Standard Reference is higher than that of the White Reference, which will imply some reflectance values > 1.

3.2 Standard Reference

a <- data.frame(file=NA, type="Certification", grade=NA, target="StdRef", replicate=NA, time=NA, ID="certif", w=certif$Wavelength, r=NA, rf=NA, s=certif$Reflectance)

micolor <- c(Certification="black", brewer.pal(3,"Set1") )
names(micolor) <- c("Certification", "KAISER", "PROLAMP", "VILALTA")
g2 <- ggplot(data=rbind(dStdR.lf,a)) +
  geom_line(aes(x=w, y=s, color=type, group=file), linewidth=0.3) +
  #geom_line(data=certif, aes(x=Wavelength, y=Reflectance), color="black")+
  #geom_point(aes(x=Wavelength, y=Reflectance,color=site, group=file)) +
  xlab("Wavelength") + ylab("Reflectance") + 
  scale_color_manual(values=micolor)  +
  theme(legend.position="bottom")
ggplotly(g2 + ggtitle("Standard Reference Target"))

We observe

• There is a notorious variability of reflectance readings with consumer-grade illumination systems (VILLALTA and KAISER), in particular after 1000 nm.
• Reflectance readings under VILALTA illumination are more variable than under KAISER illumination (but we did not control for the same warming up of the bulbs).
• Reflectance values are lower with consumer-grade illumination (VILLALTA and KAISER), despite the fact that both optimization and white reference readings were performed for each type of illumination type.

4. Paired Comparison of illumination systems

TBD using the resampled certification spectra as the X axis

dK <- dStdR.lf[dStdR.lf$type=="KAISER", c(8,9,11)]
dV <- dStdR.lf[dStdR.lf$type=="VILALTA",c(8,9,11)]
dP <- dStdR.lf[dStdR.lf$type=="PROLAMP", c(8,9,11)]
#head(dK)
#head(dV)

dKVP <- cbind(dK,rV=dV$r, sV=dV$s, sP=dP$s)
#head(dKV)
names(dKVP)[2:3] <- c("rK", "sK", "sP")
dKVP$detector <- "1"
dKVP$detector[dKV$w>1000 & dKV$w<=1800] <- "2"
dKVP$detector[dKV$w>1800] <- "3"

g3a <- ggplot(data=dKVP) +
  geom_point(aes(x=sP,y=sV, color=detector),shape=21, size=0.5)+
  xlab("Prolamp") + ylab("Vilalta") +
  theme(aspect.ratio = 1) +
  ggtitle("Reflectance of Standard Target: Vilalta vs Prolamp illumination")
#print(g3a + facet_wrap(~detector, ncol=2, scales="free"))

g3b <- ggplot(data=dKVP) +
  geom_point(aes(x=sP,y=sK, color=detector),shape=21, size=0.5)+
  xlab("Prolamp") + ylab("Kaiser") +
  theme(aspect.ratio = 1) +
  ggtitle("Reflectance of Standard Target: Kaiser vs Prolamp illumination")
#print(g3b + facet_wrap(~detector, ncol=2, scales="free"))

g3c <- ggplot(data=dKVP) +
  geom_point(aes(x=sK,y=sV, color=detector),shape=21, size=0.5)+
  xlab("Kaiser") + ylab("Vilalta") +
  theme(aspect.ratio = 1) +
  ggtitle("Reflectance of Standard Target: Vilalta vs Kaiser bulbs")
#print(g3c + facet_wrap(~detector, ncol=2, scales="free"))
#(Note that we are not reading a uniform white target but a standard reference target with very different #reflectance values along wavelength).

5. Conclusions

1. Consumer-grade illumination systems (VILLALTA and KAISER) cannot be used for reflectance readings after 1000 nm of wavelength, but can be used with the Specim IQ.
2. Kaiser bulbs appear to be more powerful and slightly more stable than Vilalta bulbs.