RadiometricCalibration: RadiometricCalibration

In tommasojulitta/FieldSpectroscopyCC: R package for Characterization and Calibration of spectrometers

Description

Compute the VIS-NIR radiometric calibration coefficients based on outdoor measurements

Usage

RadiometricCalibration(type, wl, radiance, DN, ReferenceCoeff)

Arguments

type	value: 1 if the same white panel has been used; 2 if the spectrometer connected to the cosine receptor has to be cross calibrated with measurements collected over a white panel
wl	numeric vector: wavelength vector
radiance	numeric vector: mean vector of n radiance spectra acquired
DN	numeric vector: mean vector of n spectra in Digital Number acquired over the same reference standard during the same time interval (DN spectrum has to be already dark current subtracted and divided by integration time used)
ReferenceCoeff	numeric numeric vector: vector fo the calibration coefficients of the refrence standard used.

Details

Outdoor measurements are acquired simoultaneously over the same reference standard (e.g. white panel)

or over different reference standard (e.g. white panel and cosine receptor)

by a reference spectrometer and the spectrometer to be calibrated.

All the provided data in input need to be pre-processed in order to be homogenized in terms of wavelength

(see LinearResample)

Value

numeric vector: conversion factor from digital counts to radiance for each wavelength

Author(s)

Tommaso Julitta, Mirco Migliavacca, Thomas Wutzler

Examples

  





#


#


#for Indoor radiometric claibration


#


#





data("indoor_rad_cal_data")


integration_time<-250


#Remove DC fro spectra


sub_dat_m<-DCSubtraction(signal=indoor_rad_cal_data$data_lamp,DarkSignal = indoor_rad_cal_data$data_dc,type=1)


#Create matrix for radiometric calibration


DN_mat<-DNSpectralMatrixRadCal(spectra = sub_dat_m,IntegrationTime = integration_time)


#calculate mean of several spectra


DN_mean<-StatsOnSpectra(wl=indoor_rad_cal_data$DN_wl,spectra=DN_mat,fun='mean')


#linear resample at refrence radiance wavelength 


radiance_lamp_res<-LinearResample(indoor_rad_cal_data$lamp_radiance$Wavelength,indoor_rad_cal_data$lamp_radiance$rad,indoor_rad_cal_data$DN_wl)


#calculate calibration coefficients


rad_cal<-RadiometricCalibration(type=1,wl=indoor_rad_cal_data$DN_wl,radiance = radiance_lamp_res,DN = DN_mean)


#exclude regions of the spectrum, optically black pixels


range_to_exclude<-data.frame(indoor_rad_cal_data$DN_wl[1],indoor_rad_cal_data$DN_wl[30])


range_to_exclude<-rbind(range_to_exclude,c(indoor_rad_cal_data$DN_wl[length(indoor_rad_cal_data$DN_wl)-35],indoor_rad_cal_data$DN_wl[length(indoor_rad_cal_data$DN_wl)]))


#exclude noisy pixels


excluded_noisy_pixels<-ExcludeSpectralRegions(wl=indoor_rad_cal_data$DN_wl,spectrum = rad_cal,SpectralRegionToExclude = range_to_exclude)


rad_cal_coeff<-SplineSmoothGapfilling(wl=indoor_rad_cal_data$DN_wl,excluded_noisy_pixels) 


#plot results


x11()


plot(indoor_rad_cal_data$DN_wl,rad_cal,ylim=c(0,0.02),xlab="WL [nm]",ylab="Conversion coefficients")


points(indoor_rad_cal_data$DN_wl,excluded_noisy_pixels,pch=20,col="red")


lines(indoor_rad_cal_data$DN_wl,rad_cal_coeff,col="green",lwd=2)





#


#


#for Outdoor radiometric claibration


#


#





data("outdoor_rad_cal_data")


data("atmospheric_absorption_regions")


integration_time<-450


#Create matrix for radiometric calibration


DN_mat<-DNSpectralMatrixRadCal(spectra = outdoor_rad_cal_data$DN_matrix,IntegrationTime = integration_time)


#calculate mean of several spectra


radiance_mean<-StatsOnSpectra(wl=outdoor_rad_cal_data$radiance_wl,spectra=outdoor_rad_cal_data$radiance_matrix,fun='mean')


#linear resample at refrence radiance wavelength 


radiance_mean_res<-LinearResample(wl = outdoor_rad_cal_data$radiance_wl,spectrum = radiance_mean,wlRef = outdoor_rad_cal_data$DN_wl)


wp_coeff_res<-LinearResample(outdoor_rad_cal_data$wp_coef$V1,outdoor_rad_cal_data$wp_coef$V2,outdoor_rad_cal_data$DN_wl)


#calculate mean of several spectra


DN_mean<-StatsOnSpectra(wl=outdoor_rad_cal_data$DN_wl,spectra=outdoor_rad_cal_data$DN_matrix,fun='mean')


#calculate calibration coefficients


rad_cal<-RadiometricCalibration(type=1,wl=outdoor_rad_cal_data$DN_wl,radiance = radiance_mean_res,DN = DN_mean)


#exclude regions of the spectrum affected by atmospheric absorptions and noisy pixels


range_to_exclude<-data.frame(wl_start=c(outdoor_rad_cal_data$DN_wl[1],outdoor_rad_cal_data$DN_wl[length(outdoor_rad_cal_data$DN_wl)-35]),wl_end=c(outdoor_rad_cal_data$DN_wl[30],outdoor_rad_cal_data$DN_wl[length(outdoor_rad_cal_data$DN_wl)]))


atmospheric_absorption_regions<-rbind(atmospheric_absorption_regions,c(range_to_exclude))


exclude_atmospheric_absorption_features<-ExcludeSpectralRegions(wl=outdoor_rad_cal_data$DN_wl, spectrum = rad_cal,SpectralRegion = atmospheric_absorption_regions)


#smooth results


rad_cal_coeff<-SplineSmoothGapfilling(wl=outdoor_rad_cal_data$DN_wl,spectrum = exclude_atmospheric_absorption_features) 


#plot results


x11()


plot(outdoor_rad_cal_data$DN_wl,rad_cal,ylim=c(0,0.000025),xlab="WL [nm]",ylab="Conversion coefficients")


points(outdoor_rad_cal_data$DN_wl,exclude_atmospheric_absorption_features,pch=20,col="red")


lines(outdoor_rad_cal_data$DN_wl,rad_cal_coeff,col="green",lwd=2)

tommasojulitta/FieldSpectroscopyCC documentation built on May 31, 2019, 6:19 p.m.