Dennis Helder

Users of remotely sensed Earth optical imagery are increasingly demanding a surface reflectance or surface temperature product instead of the top-of-atmosphere products that have been produced historically. Validating the accuracy of surface products remains a difficult task since it involves assessment across a range of atmospheric profiles, as well as many different land surface types. Thus, the standard approaches from the satellite calibration community do not apply, and new technologies need to be developed. The Big Multi-Agency Campaign (BigMAC) was developed to assess current technologies that might be used for the validation of surface products derived from satellite imagery, with emphasis on Landsat. Conducted in August 2021, in Brookings, SD, USA, a variety of measurement technologies were fielded and assessed for accuracy, precision, and deployability. Each technology exhibited its strengths and weaknesses. Handheld spectroradiometers are capable of surface reflectance measurements with accuracies within the 0.01–0.02 absolute reflectance units, but these are expensive to deploy. Unmanned Aircraft System (UAS)-based radiometers have the potential of making measurements with similar accuracy, but these are also difficult to deploy. Mirror-based empirical line methods showed improved accuracy potential, but their deployment also remains an issue. However, there are inexpensive radiometers designed for long-term autonomous use that exhibited good accuracy and precision, in addition to being easy to deploy. Thermal measurement technologies showed an accuracy potential in the 1–2 K range, and some easily deployable instruments are available. The results from the BigMAC indicate that there are technologies available today for conducting operational surface reflectance/temperature measurements, with strong potential for improvements in the future.

Earth remote sensing optical satellite systems are often divided into two categories—geosynchronous and sun-synchronous. Geosynchronous systems essentially rotate with the Earth and continuously observe the same region of the Earth. Sun-synchronous systems are generally in a polar orbit and view differing regions of the Earth at the same local time. Although similar in instrument design, there are enough differences in these two types of missions that often the calibration of the instruments can be substantially different. Thus, respective calibration teams develop independent methods and do not interact regularly or often. Yet, there are numerous areas of overlap and much to learn from one another. To address this issue, a panel of experts from both types of systems was convened to discover common areas of concern, areas where improvements can be made, and recommendations for the future. As a result of the panelist’s efforts, a set of eight recommendations were developed. Those that are related to improvements of current technologies include maintaining sun-synchronous orbits (not allowing orbital decay), standardization of spectral bandpasses, and expanded use of well-developed calibration techniques such as deep convective clouds, pseudo invariant calibration sites, and lunar methodologies. New techniques for expanded calibration capability include using geosynchronous instruments as transfer radiometers, continued development of ground-based prelaunch calibration technologies, expansion of RadCalNet, and development of space-based calibration radiometer systems.

One of the biggest changes in the world of optical remote sensing over the last several years is the sheer increase in the number of sensors that are imaging the Earth in moderate to high spatial resolution. With respect to the calibration of these sensors, they are broadly classified into two types, namely government systems and commercial systems. Because of the differences in the design and mission of these sensor types, calibration approaches are often substantially different. Thus, an opportunity exists to foster discussion between calibration teams for these sensors with the goal of improving overall sensor calibration and data interoperability. The approach used to accomplish this task was a one-day workshop where team members from both government and commercial sensors could share best practices, discuss methods for collaboration and improvement, and make recommendations for continuing activities. Five major recommendations were developed from the event that focused on coordinated activities using pseudo invariant calibration sites (PICS), broader and more consistent communication, collaboration on specific cross-calibration opportunities, developing a reference sensor for all optical systems, and encouraging the coordinated development of surface reflectance products. Workshop participants concluded that regular interactions between these teams could foster a better calibration of all sensor systems and accelerate the improved interoperability of surface products.

Combining data from multiple sensors into a single seamless time series, also known as data interoperability, has the potential for unlocking new understanding of how the Earth functions as a system. However, our ability to produce these advanced data sets is hampered by the differences in design and function of the various optical remote-sensing satellite systems. A key factor is the impact that calibration of these instruments has on data interoperability. To address this issue, a workshop with a panel of experts was convened in conjunction with the Pecora 20 conference to focus on data interoperability between Landsat and the Sentinel 2 sensors. Four major areas of recommendation were the outcome of the workshop. The first was to improve communications between satellite agencies and the remote-sensing community. The second was to adopt a collections-based approach to processing the data. As expected, a third recommendation was to improve calibration methodologies in several specific areas. Lastly, and the most ambitious of the four, was to develop a comprehensive process for validating surface reflectance products produced from the data sets. Collectively, these recommendations have significant potential for improving satellite sensor calibration in a focused manner that can directly catalyze efforts to develop data that are closer to being seamlessly interoperable.

A field campaign had been organized in August 2010 on Tuz Golu 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.

Landsat Multispectral Scanner (MSS) data has the potential for being widely used in global change studies since it has been collected for nearly twenty years. It is crucial to the success of these studies that MSS data be as radiometrically accurate as possible. In order to assess the quality of relative radiometric correction algorithms, a study was undertaken to compare the two commonly used techniques: use of the internal calibrator, and use of scene statistics. A new technique was developed to quantify the observed differences. Results from this study indicated clear, consistent differences exist between the two commonly used relative calibration methods and suggest that relative radiometric calibration of MSS data can be performed more effectively using the scene statistics approach.