A new generation of satellites designed for low-uncertainty, SI-traceable measurements - termed ”SITSats” - marks a major advancement in Earth Observation (EO) capability. These missions aim to enhance the performance and interoperability of the EO “system of systems”. Among them, the ESA Earth Watch TRUTHS mission is designed to serve as a ”gold-standard” radiometric reference for cross-calibrating EO sensors in the solar reflective domain. In this work, uncertainties in cross-calibration comparisons arising from sensor characterisation and design are investigated. A processing chain to prepare collocated data for uncertainty-quantified comparison is presented. This includes steps to perform spectral band adjustment and spatial resampling. Using the Traceable Radiometry Underpinning Terrestrial- and Helio- Studies (TRUTHS) Hyperspectral Imaging Spectrometer (HIS) as the reference and Sentinel-2 MultiSpectral Imager (MSI) as the target, a simulation study based on high-resolution imagery assesses achievable comparison performance. A subset of uncertainty effects driven by sensor characterisation is propagated through the spectral and spatial processing using a Monte Carlo approach. Sentinel-2 data are assumed at 10 m resolution, which is most sensitive to the errors considered. The results highlight the importance of sensor characterisation, particularly inherent in-flight wavelength knowledge for target sensors, in such comparisons. Results from the simulation analysis give uncertainty estimates (k=1) of 0.31 % (blue), 0.50 % (green), and 0.23 % (red) for the combined error effects arising from sensor characterisation and geolocation uncertainty for comparisons over the Libya-4 desert Pseudo Invariant Calibration Sites (PICS) using an instantaneous 205 m square comparison region. Results for more heterogeneous scenes, such as rainforest, still achieve uncertainties of 0.6-1.2 % for the red-green-blue (RGB) bands over a 200 m×200 m area. The uncertainty is driven largely by the spectral component-up to 1 % due to the inherent Sentinel-2 wavelength knowledge of 1 nm across various representative scenes outside of the atmospheric absorption bands. While the impact of these uncertainties may decrease when considering a diverse range of scene types, they introduce systematic errors when scenes share similar spectral characteristics. The impact of some uncertainty contributions, e.g., geolocation uncertainty, is shown to substantially reduce by aggregating samples over larger regions or over longer time periods. This analysis supports the development of low-uncertainty, ideally SITSat-enabled intercalibration approaches needed to ensure radiometric consistency across missions for generating long-term climate data records.

Upcoming SI-traceable satellite (SITSat) missions such as traceable radiometry underpinning terrestrial and helio studies (TRUTHS) aim to achieve unprecedented accuracy for SI-traceable measurements of the Earth-reflected radiation. These measurements will support the generation of low-uncertainty climate records and significantly improve the calibration of other sensors. In such a context, the calibration transfer rather than the reference sensor dominates the uncertainty budget. This study presents an end-to-end global intercalibration simulator capable of assessing the potential uncertainty for multiple scenarios that consider the interrelation of different error sources and match-ups. We first define the sensor-to-sensor match-ups through an orbital analysis that is followed by a top-of-atmosphere (TOA) radiance modeling of each match-up. Finally, we calculate the radiometric uncertainty based on different error sources combined globally. In this first implementation, we have calculated the match-ups of TRUTHS against observations by the Copernicus Sentinel-2A satellite over land areas throughout the year. We calculate the angular mismatch for both viewing differences and solar changes from different overpass times. We define multiple intercalibration scenarios based on temporal, angular, or cloud constraints. These first results show that considering overpasses up to 15-min difference, low cloud probability, and matching field-of-view (FoV), within 5°, we sample most land areas with a mean error <0.1% and bias regression <0.5%. We have also restricted the sun zenith angle (SZA) to 60° to minimize solar angle and view azimuthal dispersion over the poles. This also results in data gaps of several months that might be complemented with dedicated maneuvers or dedicated processing of these polar-region match-ups.

Presented is a new quality assurance (QA) framework for Earth Observation missions that has been developed as a joint initiative between ESA and NASA. It aims ensure the rigorous assessment of all aspects of relevant aspects of mission quality, verifying claimed mission performance and, where applicable, reviewing the extent to which the mission follows community best practice in a manner that is “fit for purpose”. The QA framework has potential for more general use in both institutional and commercial Earth Observation – helping mission providers to understand the information their users' needs and empowering users to make informed decisions about which data is fit for their purpose.

CubeSats are currently gaining significant traction in Earth Observation, with increasingly advanced instrumentation such as hyperspectral imaging. However, the challenges of bringing such instrumentation to CubeSats are great; the platform suffers from severe physical, operational and budgetary constraints. Adopting a holistic design methodology may hold the key to allowing science-grade Earth Observation to be achieved from a CubeSat. Presented here is CHAFF (CubeSat Hyperspectral Application For Farming), a low-cost hyperspectral imager prototype, capable of taking 1024 spectral bands between 460 nm - 820 nm. CHAFF has been constructed using commercial off-the-shelf optics, in order to produce a design commensurate with the typical resources of a university CubeSat mission. CHAFF has been calibrated at the National Physical Laboratory, in order to assess the performance of the COTS optics. An impressive spectral resolution of 3.46 nm at 546 nm has been achieved, and 74.95% of CHAFF's pixels exhibit a linearity deviation of < 2%.

The Radiometric Uncertainty Tool (RUT) is a software tool integrated as part of the Sentinel Application Platform (SNAP). The tool estimates the radiometric uncertainty associated with each pixel in the top-of-atmosphere reflectance factor images of the Sentinel-2 (S2) Level-1C products provided by the European Space Agency. The tool and the uncertainty analysis are under continuous evolution. This paper summarises the main features and improvements considered for a second version of the RUT. This second version has under-gone a set of software improvements such as: metadata associated to the uncertainty image, integration of the S2 L1C masks, and the feasibility of parallel processing. Furthermore, it includes upgrades in the uncertainty analysis as distinguishing between S2A and S2B satellites or the estimate of the uncertainty of a mean of pixels in a region-of-interest. Finally, the second version also includes an improved user guide and documentation.

A new permanently instrumented radiometric calibration site for high/medium resolution imaging satellites in the visible/near-IR has been set up in Gobabeb, Namibia in July 2017. The station location has been decided after a global analysis of satellite data assessing surface spatial homogeneity, cloud coverage, temporal variability, atmospheric turbidity etc. which has been compared with insitu data (surface reflectance, BRDF etc.) from a field campaign which took place in late 2015. The instrumentation automatically measures atmospheric (aerosol optical thickness etc.) and surface conditions (BRDF) from 414 nm to 1600 nm in 12 narrow spectral bands. The data processing is performed at CNES and includes the calibration of the photometer itself using in-situ measurements, and the simulation of the top-of-atmosphere radiance seen by any optical sensor over-passing the site, thus calibrating the sensor. This paper describes the instrument location, measurement protocol, calibration principle and calibration results of satellites Sentinel2A and Sentine12B.

A 3-D Monte Carlo (MC) ray-tracing radiative transfer model is tested for its ability to simulate the bidirectional reflectance factors (BRFs) of a grooved artificial target given SI-traceable measurements of the optical and topographic properties of the target's surface. The optical properties of a grooved target and an identical flat target were measured with the goniospectrophotometer at the National Metrology Institute of U.K. (NPL) and are traceable to the NPL scales of radiance factor. The topographic measurements were performed with the coordinate measuring machine at the National Metrology Institute of Finland (MIKES), and are traceable to the realization of the meter. The BRFs of the flat target were used to parameterize analytical scattering functions for rough surfaces. Similarly, the topographic measurement results were used to construct a structural model of the grooved target. Each element within this structural model then had its optical properties defined by the parameterized scattering function before the 3-D MC model simulated the BRFs of the grooved target under well-defined illumination and viewing conditions. The measured and modeled BRFs agreed for 72% of the measured geometries in the plane of incidence within the measurement and modeling uncertainties. The relative root-mean-squared (RMSE) error was 0.19. In the plane orthogonal to the plane of incidence, the measured and modeled BRFs agreed for 45% of the measured geometries, and the relative RMSE between measured and modeled values was 0.65.

A new permanently instrumented radiometric calibration site for high/medium resolution imaging satellite sensors is currently under development, focussing on the visible and near infra-red parts of the spectrum. The site will become a European contribution to the Committee on Earth Observation Satellites (CEOS) initiative RadCalNet (Radiometric Calibration Network). This paper describes the site characterisation that was carried out, both to define the exact location of permanent monitoring instrumentation, and to provide an initial detailed assessment of the site's properties. The characterisation involved a range of tests, using an ASD FieldSpec spectroradiometer, and the Gonio Radiometric Spectrometer System, a hyperspectral, multi-angle HDRF instrument. Teams from NPL and CNES each performed parts of this characterisation, working together to acquire the data and generate the final outcome.

TRUTHS (Traceable Radiometry Underpinning Terrestrial-and Helio- Studies) is a proposed small satellite mission to enable a space-based climate observing system capable of delivering data of the quality needed to provide the information needed by policy makers to make robust mitigation and adaptation decisions. This is achieved by embedding trust and confidence in the data and derived information (tied to international standards) from both its own measurements and by upgrading the performance and interoperability of other EO platforms, such as the Sentinels by in-flight reference calibration. TRUTHS would provide measurements of incoming (total and spectrally resolved) and global reflected spectrally and spatially (50 m) solar radiation at the 0.3% uncertainty level. The calibration scheme components and the route to SI-traceable Earth-reflected solar spectral radiance and solar spectral irradiance are described.

Data from Earth Observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model simulations and forecasts and manage natural resources. Policy makers are progressively relying on information derived from EO data to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires complete confidence in satellite-derived products as well as the in situ measurements used to calibrate, validate or complement these data. This paper provides an overview of the components required to develop robust quality assurance procedures for terrestrial essential climate variable (ECV) data products derived from Earth Observation (EO) satellite datasets.

This paper describes a set of tools, algorithms and methodologies that have been developed and used in order to estimate the radiometric uncertainty achievable for a Sentinel 2/3 like sensor through in-flight cross-calibration using a well-calibrated hyperspectral SI traceable reference sensor such as the proposed TRUTHS (Traceable Radiometry Underpinning Terrestrial- and Helio- Studies) mission. This first study considers the criticality of the instrumental and observational characteristics in a fully iterative manner and uses the Libya-4 Pseudo Invariant Calibration Site (PICS) as a demonstration. The main uncertainty contributions have been studied: spectral response, reflectance heterogeneity, sun angular effect and aerosol (spatial and temporal) effects. The tool contributes to optimizing the design of TRUTHS; but will find immediate use in support of existing sensor-to-sensor cross-calibration activities being carried out under the auspices of Committee on Earth Observation Satellites (CEOS).

Ground-based measurements of the hemispherical directional reflectance factor (HDRF) of windblown snow covered Arctic tundra were measured at large solar zenith angles (79°-85°) for six sites near the international research base in Ny-Ålesund, Svalbard. Measurements were made with the Gonio RAdiometric Spectrometer System over the viewing angles 0°-50° and the azimuth angles 0°-360°, for the wavelength range 400-1700 nm. The HDRF measurements showed good consistency between sites for near-nadir and backward viewing angles, with a relative standard deviation of less than 10% between sites where the snowpack was smooth and the snow depth was greater than 40 cm. The averaged HDRF showed good symmetry with respect to the solar principal plane and exhibited a forward scattering peak that was strongly wavelength dependent, with greater than a factor of 2 increase in the ratio of maximum to minimum HDRF values for all viewing angles over the wavelength range 400-1300 nm. The angular effects on the HDRF had minimal influence for viewing angles less than 150 in the backward viewing direction for the averaged sites and agreed well with another study of snow HDRF for infrared wavelengths, but showed differences of up to 0.24 in the HDRF for visible wavelengths owing to light-absorbing impurities measured in the snowpack. The site that had the largest roughness elements showed the strongest anisotropy in the HDRF, a large reduction in forward scattering, and a strong asymmetry with respect to the solar principal plane.

This forty papers in this special issue focus on how intercalibration and comparison between sensors can provide an effective and convenient means of verifying their postlaunch performance and correcting their measurement differences.

Intercalibration of satellite instruments is critical for detection and quantification of changes in the Earth's environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be interoperable, the instruments must be cross-calibrated. To meet the stringent needs of such applications, instruments must provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d'unités traceable calibration and validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stability monitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Intercalibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Intercalibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated intercalibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth's climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of postlaunch radiometric calibration of remote sensing satellite instruments through intercalibration.

The response of a variety of Earth observation satellite sensors from multiple platforms, as well as different sensors on the same platform, were cross-compared over Dome C in Antarctica. A single unified methodology was employed to remove geometric, temporal, and atmospheric biases between different sensors with a range of spatial resolutions, bandwidths, and overpass times. The result assumes no “correct” baseline value, only relative responses. The resulting responses of the sensors, namely, AATSR, MERIS, and VEGETATION 2, are here presented and, where overlap occurs, compared with the results from other groups. In addition to applying the Quality Assurance for Earth Observation protocols for the quality assurance of environmental monitoring satellites, this paper discusses the intercalibration of several sensors used to establish the technical basis of the ESA GlobAlbedo project.

Pre-flight radiometric calibration is critical to ensure that sensors can demonstrate that they meet their design performance specification. However, following launch it is critical that this performance is verified and in particular that the radiometric accuracy is validated or if necessary corrected. As Earth observation data becomes widely used it becomes increasingly important that data from each satellite sensor can be relied upon in the short and longer term and any potential biases between sensors can be removed. This post-launch calibration/validation is thus recognized as a key activity by all satellite operators. There are various methods available for carrying out this post-launch vicarious calibration but one of the most common and generic approaches is to use a dedicated and characterised “test site”. In such a method, ground based measurements of surface reflectance/radiance using similar solar illumination angles and sensor view angles (or at least corrected for these) is propagated to the top of the atmosphere (TOA) using a radiative transfer code. For the highest accuracy, surface measurements should be made within a few minutes of the satellite overpass and the characteristics of the atmosphere at that time also measured, particularly its optical depth.

In this paper, the response of 7 Earth observation satellite sensors from multiple platforms, as well as different sensors on the same platform, are cross-compared over the Dome C plateau, Antarctica, during the austral summer of 2008-2009. A single, unified methodology is employed to remove geometric, temporal and atmospheric biases between different sensors with a range of spatial resolutions, bandwidths and overpass times. The result assumes no “correct” baseline value, only relative responses. The method is derived from an in-depth sensitivity analysis, presented elsewhere [1], [2], that takes into account: BRDF effect, cloud cover, macro-scale hoar-frost change and variations in atmospheric pressure, temperature and composition, including water vapour, ozone and aerosol content variation with altitude. The resulting responses of the sensors: AATSR, AVNIR-2, ETM+ (Landsat 7), MERIS, NigeriaSat-1, VEGETATION 2 and UK-DMC-1 are presented, and where overlap occurs, compared with the results from other groups [3], [4], [5]. In addition to introducing the QA4EO protocols for the quality assurance of environmental monitoring satellites, this paper also discusses several sensors used to establish the technical basis of the ESA GlobAlbedo project: an open access, validated, 15 year long record of broadband land surface albedo (both snow and snow-free) from European sensors alone [6].

A field campaign had been organized in August 2010 on Tüz Gölü salt lake, Turkey, with the aim of characterizing the site for satellite optical sensor vicarious calibration, and of comparing different methodologies of surface reflectance factor characterization. Several teams have made ground-based reflectance measurements with a field spectrometer on different areas of the salt lake of 100 m × 300 m and 1km × 1 km size. Different types of sampling strategies and measurements methods have been used by the participants, and are described in this paper. Preliminary results on one area are presented, that show a good agreement between the different measurements.

This paper presents the results of the laboratory and field based reflectance panel and radiometer comparisons that took place as part of the CEOS 2010 Key comparison of "techniques and instruments used for the vicarious calibration of Land surface imaging through a ground reference standard test site". The results of the comparisons are presented which shows that the different ways in which reflectance panels are calibrated can give different results for the reflectance attributed to a test site and that changing illumination and environmental conditions can effect the measured target reflectance.

An international team of remote sensing calibration experts, representing space agencies from 10 different countries, conducted a two week field campaign at Tuz Golu, Turkey in August, 2010 sponsored by the Committee on Earth Observation Satellites (CEOS). While the campaign focused on surface reflectance factor measurement, five specific CEOS objectives were being addressed: evaluating differences in field instrument primary calibrations, evaluating difference in field characterization methodologies and possible establishment of best practices, perform a multi-sensor absolute calibration comparison, identification of minimum and ideal instrumentation / characterization for use as a reference standard, and formal characterization of the Tuz Golu absolute calibration site. This paper will focus on the latter component. An evaluation of the temporal, spatial and directional dependencies of the surface reflectance of the Tuz Golu salt flat will be presented. Also, an evaluation of the optical atmospheric stability of the site was conducted.

Tuz GGölü, a salt lake situated in the central Anatolia, which dries during summer resulting in a spatially homogeneous high reflective surface is one of the LANDNET Sites [4, 6]. As a relatively new site and with support from the European Space Agency (ESA) and Space Technologies Research Institute of The Scientific and Technological Research Council of Turkey (TUBITAK UZAY) it was decided that this would be a good candidate to carry out an international comparison of this nature. This paper provides an overview of the CEOS international comparison carried out at Tuz Gölü in 13 – 27 August 2010.

This paper summarizes lessons learned from the 2009 and 2010 joint field campaigns to Tuz Golu, Turkey. Emphasis is placed on the 2010 campaign related to understanding the equipment and measurement protocols, processing schemes, and traceability to SI quantities. Participants in both 2009 and 2010 used an array of measurement approaches to determine surface reflectance. One lesson learned is that even with all of the differences in collection between groups, the differences in reflectance are currently dominated by instrumental artifacts including knowledge of the white reference. Processing methodology plays a limited role once the bi-directional reflectance of the white reference is used rather than a hemispheric-directional value. The lack of a basic set of measurement protocols, or best practices, limits a group's ability to ensure SI traceability and the development of proper error budgets. Finally, rigorous attention to sampling methodology and its impact on instrument behavior is needed. The results of the 2009 and 2010 joint campaigns clearly demonstrate both the need and utility of such campaigns and such comparisons must continue in the future to ensure a coherent set of data that can span multiple sensor types and multiple decades.

A significant challenge for the Global Earth Observation System of Systems (GEOSS) interoperability is the lack of consistency in the Earth observations from satellites developed, calibrated, and operated by different space agencies worldwide, and the potential for significant discrepancies among products exists. The Committee on Earth Observation Satellites (CEOS) and its Working Group on Calibration and Validation (WGCV) are taking specific steps to facilitate interoperability by developing data quality assurance strategies and conducting joint cross-calibration studies. In this study, the Antarctic Plateau Dome C site is used for cross-comparison of visible/near infrared, and microwave instruments. Observations from AVHRR, MODIS, Hyperion, AMSR-E, and other instruments were intercompared. The findings suggest that the site is stable with relatively low radiometric uncertainties, and is a good candidate for CEOS endorsed cal/val site for satellite cross-comparison to facilitate GEOSS interoperability.

The measurement of spectral data in the field has an important role in remote sensing, and a long history, but instruments and methods to achieve this have serious limitations under all but the most ideal conditions. Problems arise from the instruments themselves, from the environment in which they are used, and from the methodologies that are commonly adopted. The variable most commonly sought from field measurements is spectral reflectance, or more strictly the bidirectional reflectance factor (BRF), but this is dependent to some extent on the instrument used to make the measurement, and the conditions of measurement, notably the sky irradiance distribution. In this paper we argue that field spectral measurements should be recorded in the appropriate SI units, which will normally be the derived units of radiance for the flux reflected from the target and irradiance for the incident energy. Reflectance data remain a convenient way to represent the energy interactions occurring at the surface, and they have value in generic spectral libraries, but ultimately they lack reproducibility unless accompanied by much more detailed metadata than is the norm in most spectral libraries.

Satellite sensors can measure the solar energy reflected from the Earth's atmosphere and surface, and provide the only feasible method of obtaining global scale data on the state of the planet. The accuracy and reliability of data from satellite sensors is therefore of vital importance, and much effort goes into characterizing such instruments before launch. However, the stress of launch, and the extreme environment of space is known to affect the calibration of sensors, introducing uncertainty into the data they provide, especially the long time-series data necessary to investigate and monitor climate change. It is therefore vitally important that methods for the post-launch calibration and validation of data from satellite sensors are developed and tested. In order to do this it is necessary to have highly accurate data on the angular reflectance of natural surfaces, and this project aims to develop and test a new instrument to achieve this. To improve the accuracy of field measurements, a new instrument is being designed, in conjunction with the Natural Environmental Research Council Field Spectroscopy Facility (NERC FSF). The Gonio RAdiometric Spectrometer System (GRASS) is being developed at the National Physical Laboratory (NPL), in its Optical Radiation Measurement Team. It is intended to provide quasi-simultaneous, multi-angle, multi- spectral measurements of Earth surface reflected sunlight to support vicarious calibration of satellite sensors operating in the optical region and the validation of their products. The instrument is required to be easily and quickly assembled in remote situations, be robust and transportable to remote locations and its measurements fully traceable to SI units. The GRASS instrument is currently being assembled at the NPL and will be deployed in summer 2006 as part of an experiment to validate data from a range of airborne and satellite sensors. The paper will review existing methods of measuring BRDF in the field, highlight the improvements that GRASS will provide to users, and describe the experiments performed to test its performance.