Polarization properties of FEL lamps as applied to radiometric calibration

Measuring the spectral response of a division-of-focal-plane polarization imager using a grating monochromator

Spectral characterizations are performed on imagers to obtain a relative spectral response (RSR) curve. This process often utilizes a grating monochromator with an output that changes polarization as a function of wavelength (our monochromator's degree of linear polarization was found to vary from less than 10% to more than 70%). When characterizing a polarization-sensitive imager, this introduces polarization artifacts into the RSR curve. We present a simple method to avoid these polarization artifacts for division-of-focal-plane polarization imagers by directly illuminating the camera with the monochromator output and calculating the S₀ Stokes parameter at each super pixel, then we show consistent results from this method for two division-of-focal-plane polarization imagers. We also show that ignoring the monochromator polarization results in order-of-magnitude RSR errors. The recommended method uses an iris to limit the spatial extent of the monochromator output, which was found experimentally to increase the minimum signal-to-noise ratio by more than a factor of 2.

Laboratory Intercomparison of Radiometers Used for Satellite Validation in the 400–900 nm Range

An intercomparison of radiance and irradiance ocean color radiometers (The Second Laboratory Comparison Exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8–13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: 1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; 2) Indoor intercomparison using stable radiance and irradiance sources in controlled environment; and 3) Outdoor intercomparison of natural radiation sources over terrestrial water surface. The aim of the experiment was to provide one link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether different instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the activities and results of the first two phases of LCE-2: the SI-traceable radiometric calibration and indoor intercomparison, the results of outdoor experiment are presented in a related paper of the same journal issue. The indoor experiment of the LCE-2 has proven that uniform calibration just before the use of radiometers is highly effective. Distinct radiometers from different manufacturers operated by different scientists can yield quite close radiance and irradiance results (standard deviation s < 1%) under defined conditions. This holds when measuring stable lamp-based targets under stationary laboratory conditions with all the radiometers uniformly calibrated against the same standards just prior to the experiment. In addition, some unification of measurement and data processing must be settled. Uncertainty of radiance and irradiance measurement under these conditions largely consists of the sensor’s calibration uncertainty and of the spread of results obtained by individual sensors measuring the same object.

Direct Reflectance Measurements from Drones: Sensor Absolute Radiometric Calibration and System Tests for Forest Reflectance Characterization

Drone-based remote sensing has evolved rapidly in recent years. Miniaturized hyperspectral imaging sensors are becoming more common as they provide more abundant information of the object compared to traditional cameras. Reflectance is a physically defined object property and therefore often preferred output of the remote sensing data capture to be used in the further processes. Absolute calibration of the sensor provides a possibility for physical modelling of the imaging process and enables efficient procedures for reflectance correction. Our objective is to develop a method for direct reflectance measurements for drone-based remote sensing. It is based on an imaging spectrometer and irradiance spectrometer. This approach is highly attractive for many practical applications as it does not require in situ reflectance panels for converting the sensor radiance to ground reflectance factors. We performed SI-traceable spectral and radiance calibration of a tuneable Fabry-Pérot Interferometer -based (FPI) hyperspectral camera at the National Physical Laboratory NPL (Teddington, UK). The camera represents novel technology by collecting 2D format hyperspectral image cubes using time sequential spectral scanning principle. The radiance accuracy of different channels varied between ±4% when evaluated using independent test data, and linearity of the camera response was on average 0.9994. The spectral response calibration showed side peaks on several channels that were due to the multiple orders of interference of the FPI. The drone-based direct reflectance measurement system showed promising results with imagery collected over Wytham Forest (Oxford, UK).

Polarimetric characteristics of a class of hyperspectral radiometers

The polarimetric characteristics of a class of hyperspectral radiometers commonly applied for above-water radiometry have been investigated by analyzing a sample of sensors. Results indicate polarization sensitivity increasing with wavelength and exhibiting values varying from sensor to sensor. In the case of radiance sensors, the maximum differences increase from approximately 0.4% at 400 nm to 1.3% at 750 nm. In the case of irradiance sensors, due to depolarizing effects of the diffusing collector, the maximum differences between horizontal and vertical polarization sensitivities vary from approximately 0.3% at 400 nm to 0.6% at 750 nm. Application of the previous results to above-water radiometry measurements performed in sediment dominated waters indicates that neglecting polarization effects may lead to uncertainties not exceeding a few tenths of a percent in remote sensing reflectance R_RS determined in the 400-570 nm spectral interval. Conversely, uncertainties spectrally increase toward the near infrared, reaching several percent at 750 nm in the case of oligotrophic waters.