Abstract
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.
Highlights
Earth observation (EO) is used for a wide range of societal and commercial applications
While the RadCalNet TOA reflectance and their associated uncertainty should be sufficient to assess the in-flight radiometric performance of spaceborne sensors operating in the visible to shortwave infrared designed with an absolute radiometric accuracy requirement of the order of 5%, they might not be able to address the needs of sensor with high absolute radiometric calibration requirements of around 2%
The data from the sites are provided to the RadCalNet Processor: a central facility that ensures the data from the individual sites are processed with the same approach to provide TOA reflectances and associated uncertainties based on the inputs from the instrumented site
Summary
Earth observation (EO) is used for a wide range of societal and commercial applications. Users are combining data from different sensors, either to provide long-term records of environmental change that require time series greater than the lifetime of a single sensor, or to provide operational services using data from different sensors (from different satellites) to maximize coverage Both the space agencies and commercial operators are launching a wider range of sensors with different spectral bands, and increasingly small, relatively cheap sensors are being launched with no on-board calibration (e.g., onboard CubeSats). The method relies on spatially and spectrally characterizing the surface reflectance from aircraft data and using the reflectance with coincident atmospheric data to predict the at-sensor radiance Such an approach was used to compare data from a wide array of sensors viewing the Railroad Valley instrumented site on a single day [11] and has been used to cross-compare data from sensors viewing the site on different dates [12]. The last section of the paper shows an example interconsistency study between two sensors and two independent instrumented sites to illustrate how RadCalNet users will benefit from the data available from the network
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