Accuracy of SpectroRasp spectra

• Agustin.Lobo@geo3bcn.csic.es
• 20230306

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require(ggplot2)
require(grid)
require(gridExtra)
require(gganimate)
require(plotly)
require(lubridate)
require(colorRamps)
require(lmodel2)
require(broom)
require(pander)
source("selSessionRefs.R")
#Certified
load("/home/alobo/owncloudRSpect/RSpect/RefMCAA01.rda")
#load("C:/Users/Specim/ownCloud/RSpect/RefMCAA01.rda")

4. Accuracy of Reflectance readings (20230216 data) compared to other instruments

We compare reflectance spectra of a standard reflectance target (Labsphere WCS-MC-020) acquired with the following instruments:

• Cubert Firefleye S185 SE
• Specim IQ
  
• Specim FX10
• Specim FX17
• SpectroRasp (SpR), in-house integration of
  • STS-VIS (350 - 800 nm)
  • NIR QUEST (900-2500 nm)
  • Raspberry Pi 3

Particularly at the deepest absorption features (eg. 1260 nm), there is a significant difference between SpectroRasp NIRQUEST reflectance measurements and the certified values. In comparison, Specim FX17 readings are more accurate.

#fdir <- "../time_measures20230102"
fdir <- "../Testdist_20230206"
lista <- data.frame(fname=list.files(fdir, patt=glob2rx("*.txt")), fdir=fdir)
listasel <- lista[c(1,7),]
selRefs <- selSessionRefs(selflist=listasel)
selRefs$sample[selRefs$sample=="Ref_1"] <- "Initial" 
selRefs$sample[selRefs$sample=="Ref_2"] <- "Final" 

#Specim FX17 (see SdRef_Certif_FX17_SpR-SPR0_log.R)
#dirFX17Ref <- "/media/alobo/DecepNTFS2/Decepcion/Lapilli/DI61_graineffect/DRXDI61/FX17/FX17Spectra"
dirFX17Ref <- "../../DI61_graineffect_DRDXI61_FX17Spectra"
RefFX17 <- read.csv(file.path(dirFX17Ref,"Ref_FX17refl.csv"))
#head(RefFX17)
names(RefFX17)[4:5] <- c("Reflectance", "s")
RefFX17$sample <- "RefFX17"
#selRefs[1,]
#RefFX17[1,]
RefFX17$sample <- "FX17"
RefMCAA01$sample <- "Certification"

#Specim FX10 (see HSIsystems_comp.Rmd)
dirFX10 <- "../../miRPubs"
RefFX10 <- read.csv(file.path(dirFX10, "FX10_Sant_Finx_big_2019-06-11_14-01-10.csv"))
RefFX10 <- RefFX10[RefFX10$Sample == "WCS-MC-020",]
RefFX10$sample <- "FX10"

#Specim IQ (see HSIsystems_comp.Rmd)
dirIQ <- "../../miRPubs"
RefIQ <- read.csv(file.path(dirIQ,"IQ_20220914-018_ReflRefMCA.csv" ))
RefIQ <- RefIQ[RefIQ$Sample == "WCS-MC-020",]
RefIQ$sample <- "IQ"

a <- rbind(selRefs[,1:3],RefIQ[,c(7,2,4)],RefFX10[,c(7,2,4)], RefFX17[,c(1,3,4)],RefMCAA01[,c(4,1,3)])
names(a)[1] <- "Instrument"
#a[1,]
a$Instrument[a$Instrument=="Initial"] <- "SpR_initial"
a$Instrument[a$Instrument=="Final"] <- "SpR_final"
#time dif. ~11'
#table(a$Instrument)
micol <- c("Certification"="grey", "IQ"= "darkred","FX10"="navy","FX17"="blue", "SpR_initial"="darkgreen", "SpR_final"="green")


ggRefRefl <- ggplot(data=a,aes(x=Wavelength, y=Reflectance)) +
  geom_point(alpha=0.5, size=0.5,aes(group=Instrument,color=Instrument)) +
  geom_line (alpha=0.5, linewidth=0.5, aes(group=Instrument, color=Instrument)) +
  geom_line(data=RefMCAA01, aes(x=Wavelength, y=Reflectance),col="grey") +
  geom_point(data=RefMCAA01, aes(x=Wavelength, y=Reflectance),size=0.5, col="grey") +
  xlim(c(400, 2600)) +
  scale_color_manual(values=micol) +
  theme(legend.position="bottom") +
  ggtitle("Reflectance of Standard Target with different Instruments")
#print(ggRefRefl)

ggplotly(ggRefRefl)  %>%
  layout(legend = list(orientation = "h", x = 0.02, y = 0.1))