Solar spectral irradiometer for validation of remotely sensed hyperspectral data

Abstract

A new solar spectral irradiometer that operates in the visible and near-infrared spectral ranges has been developed. This instrument takes advantage of a new concept optical head that collects the light that impinges on a hemispheric surface, thus improving the instrument angular response with respect to traditional devices. The technical characteristics of the instrument are investigated and detailed, and its radiometric calibration, performed by means of a Langley-like method, is discussed. A new simplified theoretical model that accounts for the diffuse irradiance observed in an optically thin plane-parallel atmosphere has been developed to improve the fit of the irradiance diurnal evolution. An alternative polynomial parametric representation of monochromatic diffuse irradiance evolution has been attempted, but satisfactory results were not obtained from the fitting of experimental data. The new instrument could be useful to carry out remote-sensing validation campaigns.

Reduction of Radiometric Miscalibration—Applications to Pushbroom Sensors

“…The association is often realised by a polynomial least squares fit, which minimises the differences between modelled and measured at-sensor radiance [35,36]. This minimisation of the merit function can then be used to obtain the coefficients for radiometric transformations: ${\chi }^2={\Sigma }_{\text{j}=1}^{{\text{N}}_{\text{targets}}}{false[\text{L}-false({\text{c}}_0+{\Sigma }_{\text{i}=1}^{\text{M}}\hspace{0.17em}{\text{c}}_{\text{i}}\cdot {\text{DN}}^{\text{i}}false)false]}^2\wedge \text{M}\ge 1;\hspace{0.17em}{\text{N}}_{\text{targets}}\ge 2$where N targets denotes the number of calibration targets, c 0 is the offset contrary to the dark current, and M is the polynomial degree.…”

Investigating the angular and spectral properties of natural targets using CHRIS‐PROBA images of San Rossore test site

“…It can easily be shown that this equation is able to restore the processed data from light trapping effects, provided that the included transmittance term is modified by the addition of neighbouring spectral contributions, which depend on the scattering coefficient, the atmospheric direct transparency and a geometric factor, as reported by Barducci et al (2002). Almost all atmospheric parameters included in equation (2) were simulated by means of the Modtran 4 computer code (see Anderson et al 1995), with the exception of the downwelling total spectral irradiance at ground, which was in-field measured with a custom instrument described by Barducci et al (2004). Single-pixel Lambertian reflectance spectra obtained applying this procedure to CHRIS data were compared with hemispherical spectral measurements executed in the laboratory over target samples taken from the corresponding point of the soil.…”

Translational Imaging Spectroscopy for Proximal Sensing

“…Physically well-defined calibration targets are recorded in the calibration process. Sensor response is mathematically related to the targets by polynomial modelling [ 12 , 13 , 14 ]. The data can be related to as at-sensor radiance [ 4 , 6 ] after radiometric scaling: where h is the Planck constant, A is the area of the entrance aperture, is the solid angle of one pixel, is the spectral sampling of the camera, t is the integration time and is the radiometric response in DN .…”