The Landsat-8 Operational Land Imager (OLI) was radiometrically calibrated prior to launch in terms of spectral radiance, using an integrating sphere source traceable to National Institute of Standards and Technology (NIST) standards of spectral irradiance. It was calibrated on-orbit in terms of reflectance using diffusers characterized prior to launch using NIST traceable standards. The radiance calibration was performed with an uncertainty of ~3%; the reflectance calibration to an uncertainty of ~2%. On-orbit, multiple calibration techniques indicate that the sensor has been stable to better than 0.3% to date, with the exception of the shortest wavelength band, which has degraded about 1.0%. A transfer to orbit experiment conducted using the OLI’s heliostat-illuminated diffuser suggests that some bands increased in sensitivity on transition to orbit by as much as 5%, with an uncertainty of ~2.5%. On-orbit comparisons to other instruments and vicarious calibration techniques show the radiance (without a transfer to orbit adjustment), and reflectance calibrations generally agree with other instruments and ground measurements to within the uncertainties. Calibration coefficients are provided with the data products to convert to either radiance or reflectance units.

Vicarious calibration approaches using in situ measurements saw first use in the early 1980s and have since improved to keep pace with the evolution of the radiometric requirements of the sensors that are being calibrated. The advantage of in situ measurements for vicarious calibration is that they can be carried out with traceable and quantifiable accuracy, making them ideal for interconsistency studies of on-orbit sensors. The recent development of automated sites to collect the in situ data has led to an increase in the available number of datasets for sensor calibration. The current work describes the Radiometric Calibration Network (RadCalNet) that is an effort to provide automated surface and atmosphere in situ data as part of a network including multiple sites for the purpose of optical imager radiometric calibration in the visible to shortwave infrared spectral range. The key goals of RadCalNet are to standardize protocols for collecting data, process to top-of-atmosphere reflectance, and provide uncertainty budgets for automated sites traceable to the international system of units. RadCalNet is the result of efforts by the RadCalNet Working Group under the umbrella of the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and the Infrared Visible Optical Sensors (IVOS). Four radiometric calibration instrumented sites located in the USA, France, China, and Namibia are presented here that were used as initial sites for prototyping and demonstrating RadCalNet. All four sites rely on collection of data for assessing the surface reflectance as well as atmospheric data over that site. The data are converted to top-of-atmosphere reflectance within RadCalNet and provided through a web portal to allow users to either radiometrically calibrate or verify the calibration of their sensors of interest. Top-of-atmosphere reflectance data with associated uncertainties are available at 10 nm intervals over the 400 nm to 1000 nm spectral range at 30 min intervals for a nadir-viewing geometry. An example is shown demonstrating how top-of-atmosphere data from RadCalNet can be used to determine the interconsistency between two sensors.

This paper presents the vicarious calibration results of Landsat 8 OLI that were obtained using the reflectance-based approach at test sites in Nevada, California, Arizona, and South Dakota, USA. Additional data were obtained using the Radiometric Calibration Test Site, which is a suite of instruments located at Railroad Valley, Nevada, USA. The results for the top-of-atmosphere spectral radiance show an average difference of −2.7, −0.8, 1.5, 2.0, 0.0, 3.6, 5.8, and 0.7% in OLI bands 1–8 as compared to an average of all of the ground-based measurements. The top-of-atmosphere spectral reflectance shows an average difference of 1.6, 1.3, 2.0, 1.9, 0.9, 2.1, 3.1, and 2.1% from the ground-based measurements. Except for OLI band 7, the spectral radiance results are generally within ±5% of the design specifications, and the reflectance results are generally within ±3% of the design specifications. The results from the data collected during the tandem Landsat 7 and 8 flight in March 2013 indicate that ETM+ and OLI agree to each other to within ±2% in similar bands in top-of-atmosphere spectral radiance, and to within ±4% in top-of-atmosphere spectral reflectance.

The Sentinel-2A and Landsat-8 satellites carry on-board moderate resolution multispectral imagers for the purpose of documenting the Earth’s changing surface. Though they are independently built and managed, users will certainly take advantage of the opportunity to have higher temporal coverage by combining the datasets. Thus it is important for the radiometric and geometric calibration of the MultiSpectral Instrument (MSI) and the Operational Land Imager (OLI) to be compatible. Cross-calibration of MSI to OLI has been accomplished using multiple techniques involving the use of pseudo-invariant calibration sites (PICS) using direct comparisons as well as through use of PICS models predicting top-of-atmosphere reflectance. A team from the University of Arizona is acquiring field data under both instruments for vicarious calibration of the sensors. This paper shows that the work done to date by the Landsat and Sentinel-2 calibration teams has resulted in stable radiometric calibration for each instrument and consistency to ~2.5% between the instruments for all the spectral bands that the instruments have in common.

Remote sensing instruments, both aircraft and on-orbit platforms, undergo extensive laboratory calibrations to determine their geometric, spectral, and radiometric responses. Additional in-flight radiometric calibrations can be performed using well-characterized earth targets. The Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign provided such an opportunity when the ER-2 aircraft overflew Railroad Valley on August 13 and 15, 2019. Surface reflectances were available from the August 4, 2019 field team and from the Radiometric Calibration Network (RadCalNet) portal, and spectral aerosol optical depths from an on-site AERosol RObotic NETwork (AERONET) sunphotometer. The Enhanced MODIS Airborne Simulator (eMAS), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), and the “Classic” Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-C) sensors individually performed a vicarious calibration using their respective methodologies and selection of input parameters. A comparison of the at-sensor radiances predicted from these independent analyses highlights some of the uncertainties in the inputs, including choice of solar irradiance model. Although good agreement, within 5%, is found at visible wavelengths, difference can be as large as 15% in the shortwave infrared (SWIR). This highlights the need for the remote sensing community to agree upon a standard solar model, to remove sensor-to-sensor biases derived from in-flight calibrations.