Overview of Intercalibration of Satellite Instruments

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, stabilitymonitoring, 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

Overview of Intercalibration of Satellite Instruments

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, stabilitymonitoring, 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

Vicarious Methodologies to Assess and Improve the Quality of the Optical Remote Sensing Images: A Critical Review

Over the past decade, number of optical Earth observing satellites performing remote sensing has increased substantially, dramatically increasing the capability to monitor the Earth. The quantity of remote sensing satellite increase is primarily driven by improved technology, miniaturization of components, reduced manufacturing, and launch cost. These satellites often lack on-board calibrators that a large satellite utilizes to ensure high quality (e.g., radiometric, geometric, spatial quality, etc.) scientific measurement. To address this issue, this work presents “best” vicarious image quality assessment and improvement techniques for those kinds of optical satellites which lacks on-board calibration system. In this article, image quality categories have been explored, and essential quality parameters (e.g., absolute and relative calibration, aliasing, etc.) have been identified. For each of the parameters, appropriate characterization methods are identified along with its specifications or requirements. In cases of multiple methods, recommendation has been made based-on the strengths and weaknesses of each method. Furthermore, processing steps have been presented, including examples. Essentially, this paper provides a comprehensive study of the criteria that needs to be assessed to evaluate remote sensing satellite data quality, and best vicarious methodologies to evaluate identified quality parameters such as coherent noise, ground sample distance, etc

Ultra-Portable Field Transfer Radiometer for Vicarious Calibration of Earth Imaging Sensors

A small portable transfer radiometer has been developed as part of an effort to ensure the quality of upwelling radiance from test sites used for vicarious calibration in the solar reflective. The test sites are used to predict top-of-atmosphere reflectance relying on ground-based measurements of the atmosphere and surface. The portable transfer radiometer is designed for one-person operation for on-site field calibration of instrumentation used to determine ground-leaving radiance. The current work describes the detector-and source-based radiometric calibration of the transfer radiometer highlighting the expected accuracy and SI-traceability. The results indicate differences between the detector-based and source-based results greater than the combined uncertainties of the approaches. Results from recent field deployments of the transfer radiometer using a solar radiation based calibration agree with the source-based laboratory calibration within the combined uncertainties of the methods. The detector-based results show a significant difference to the solar-based calibration. The source-based calibration is used as the basis for a radiance-based calibration of the Landsat-8 Operational Land Imager that agrees with the OLI calibration to within the uncertainties of the methods

Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability

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

Aqua and Terra MODIS RSB Calibration Comparison Using BRDF Modeled Reflectance

The inter-comparison of MODIS reflective solar bands onboard Aqua and Terra is very important for assessment of each instrument's calibration. One of the limitations is the lack of simultaneous nadir overpasses. Their measurements over a selected Earth view target have significant differences in solar and view angles, which magnify the effects of atmospheric scattering and Bidirectional Reflectance Distribution Function (BRDF). In this work, an intercomparison technique is formulated after correction for site's BRDF and atmospheric effects. The reflectance measurements over Libya desert sites 1, 2, and 4 from both the Aqua and Terra MODIS are regressed to a BRDF model with an adjustable coefficient accounting for calibration difference. The ratio between Aqua and Terra reflectance measurements are derived for bands 1 to 9 and the results from different sites show good agreement. For year 2003, the ratios are in the range of 0.985 to1.010 for band 1 to 9. Band 3 shows the lowest ratio 0.985 and band 1 shows the highest ratio 1.010. For the year 2014, the ratio ranges from approximately 0.983 for bands 2 and 1.012 for band 8. The BRDF corrected reflectance for the two instruments are also derived for every year from 2003 to 2014 for stability assessment. Bands 1 and 2 show greater than 1 differences between the two instruments. Aqua bands 1 and 2 show downward trends while Terra bands 1 and 2 show upward trends. Bands 8 and 9 of both Aqua and Terra show large variations of reflectance measurement over time

Evaluation of an Extended PICS (EPICS) for Calibration and Stability Monitoring of Optical Satellite Sensors

Pseudo Invariant Calibration Sites (PICS) have been increasingly used as an independent data source for on-orbit radiometric calibration and stability monitoring of optical satellite sensors. Generally, this would be a small region of land that is extremely stable in time and space, predominantly found in North Africa. Use of these small regions, referred to as traditional PICS, can be limited by: i) the spatial extent of an individual Region of Interest (ROI) and/or site; ii) and the frequency of how often the site can be acquired, based on orbital patterns and cloud cover at the site, both impacting the time required to construct a richly populated temporal dataset. This paper uses a new class of continental scaled PICS clusters (also known as Extended PICS or EPICS), to demonstrate their capability in increasing temporal frequency of the calibration time series which ultimately allows calibration and stability assessment at a much finer scale compared to the traditional PICSbased method while also reducing any single location’s potential impact to the overall assessment. The use of EPICS as a calibration site was evaluated using data from Landsat- 8 Operational Land Imager (OLI), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Sentinel-2A&B Multispectral Instrument (MSI) images at their full spatial resolutions. Initial analysis suggests that EPICS, at its full potential and with nominal cloud consideration, can significantly decrease the temporal revisit interval of moderate resolution sensors to as much as of 0.33 day (3 collects/day). A traditional PICS is expected to have a temporal uncertainty (defined as the ratio of temporal standard deviation and temporal mean) of 2-5% for TOA reflectance. Over the same time period EPICS produced a temporal uncertainty of 3%. But the advantage to be leveraged is the ability to detect sensor change quicker due to the denser dataset and reduce the impact of any potential ‘local’ changes. Moreover, this approach can be extended to any on-orbit sensor. An initial attempt to quantify the minimum detectable change (a threshold slope value which must be exceeded by the reflectance trend to be considered statistically significant) suggests that the use of EPICS can decrease the time period up to approximately half of that found using traditional PICS-based approach

The Use of Landsat 8 for Monitoring of Fresh and Coastal Waters

The most interaction between humankind and water occurs in coastal and inland waters (Case 2 waters) at a scale of tens or hundred of meters, but there is not yet an ocean color product (e.g. chlorophyll-a product) at this spatial scale. Landsat 8 could potentially address the remote sensing of these kinds of waters due to its improved features. This work presents an approach to obtain the color producing agents (CPAs) chlorophyll-a, colored dissolved organic material (CDOM) and suspended material (SM) from water bodies using Landsat 8. Adequate atmospheric correction becomes an important first step to accurately retrieving water parameters since the sensor-reaching signal due to water is very small when compared to the signal due to the atmospheric effects. We developed the model-based empirical line method (MoB-ELM) atmospheric correction method. The Mob-ELM employs pseudo invariant feature (PIF) pixels extracted from a reflectance product along with the in-water radiative transfer model HydroLight. We used a look-up-table-based (LUT-based) inversion methodology to simultaneously retrieve CPAs. The LUT of remote-sensing reflectance spectra was created in Hydrolight using inherent optical properties (IOPs) measured in the field. The retrieval algorithm was applied over three Landsat 8 scenes. The CPA concentration maps exhibit expected trends of low concentrations in clear waters and higher concentrations in turbid waters. We estimated a normalized root mean squared error (NRMSE) of about 14% for Chlorophyll-a, 11% for the total suspended solid (TSS), and 7% for colored dissolved organic matter (CDOM) when compared with in situ data. These results demonstrate that the developed algorithm allows the simultaneous mapping of concentration of all CPAs in Case 2 waters and over areas where the standard algorithms are not available due to spatial resolution. Therefore, this study shows that the Landsat 8 satellite can be utilized over Case 2 waters as long as a careful atmospheric correction is applied and IOPs are known

Refinement of the method for using pseudo-invariant sites for long term calibration trending of Landsat reflective bands

The long term calibration history of the Landsat 5 TM instrument has recently been defined using a time series of desert sites in Northern Africa. This correction is based on the assumption that the atmosphere is invariant and the reflectance of each site is approximately constant and Lambertian over time. As a result, the top of the atmosphere reflection is assumed constant when corrected for variations in the solar elevation angle and earth-sun distance. While this is true to first order and is the basis for all current temporal calibration, there are multiple known sources of residual error in the data. A methodology is presented for reducing the variation in pseudo-invariant site trending data based on correction for the BRDF. This work establishes a means to use DIRSIG to model the L5 calibration site. It combines a digital elevation map and desert atmosphere with a surface BRDF to reduce the residual errors in the calibration data. A set of Landsat 7 ETM+ calibration days is utilized to optimize the surface reflectance properties used in DIRSIG. These optimized parameters are then used to model the L5 TM calibration days. The results of the DIRSIG modeling are compared to the solar elevation angle and time of year trends of the original data and analyzed for their effectiveness at describing and reducing the residual errors. A major goal of this effort is to understand the contribution that BRDFs make to the current calibration errors and to develop methods that are robust enough to be applicable to a wider range of sites to enable extension of the methodology to earlier data sets (e.g. Landsat MSS). Additionally, while Landsat has a 30 m reflective resolution, the pseudo-invariant site calibration approach is valid for all spatial resolutions. Depending on another instrument\u27s field of view, the BRDF error reduction technique used by L5 TM could either be used on the same desert calibration site or on a subsection of the area

Classification of North Africa for Use as an Extended Pseudo Invariant Calibration Sites (Epics) for Radiometric Calibration and Stability Monitoring of Optical Satellite Sensors

An increasing number of Earth-observing satellite sensors are being launched to meet the insatiable demand for timely and accurate data to help the understanding of the Earth’s complex systems and to monitor significant changes to them. The quality of data recorded by these sensors is a primary concern, as it critically depends on accurate radiometric calibration for each sensor. Pseudo Invariant Calibration Sites (PICS) have been extensively used for radiometric calibration and temporal stability monitoring of optical satellite sensors. Due to limited knowledge about the radiometric stability of North Africa, only a limited number of sites in the region are used for this purpose. This work presents an automated approach to classify North Africa for its potential use as an extended PICS (EPICS) covering vast portions of the continent. An unsupervised classification algorithm identified 19 “clusters” representing distinct land surface types; three clusters were identified with spatial uncertainties within approximately 5% in the shorter wavelength bands and 3% in the longer wavelength bands. A key advantage of the cluster approach is that large numbers of pixels are aggregated into contiguous homogeneous regions sufficiently distributed across the continent to allow multiple imaging opportunities per day, as opposed to imaging a typical PICS once during the sensor’s revisit period. In addition, this work proposes a technique to generate a representative hyperspectral profile for these clusters, as the hyperspectral profile of these identified clusters are mandatory in order to utilize them for performing cross-calibration of optical satellite sensors. The technique was used to generate the profile for the cluster containing the largest number of aggregated pixels. The resulting profile was found to have temporal uncertainties within 5% across all the spectral regions. Overall, this technique shows great potential for generation of representative hyperspectral profiles for any North African cluster, which could allow the use of the entire North Africa Saharan region as an extended PICS (EPICS) dataset for sensor cross-calibration. Furthermore, this work investigates the performance of extended pseudo-invariant calibration sites (EPICS) in cross-calibration for one of Shrestha’s clusters, Cluster 13, by comparing its results to those obtained from a traditional PICS-based cross-calibration. The use of EPICS clusters can significantly increase the number of cross-calibration opportunities within a much shorter time period. The cross-calibration gain ratio estimated using a cluster-based approach had a similar accuracy to the cross-calibration gain derived from region of interest (ROI)-based approaches. The cluster-based cross-calibration gain ratio is consistent within approximately 2% of the ROI-based cross-calibration gain ratio for all bands except for the coastal and shortwave-infrared (SWIR) 2 bands. These results show that image data from any region within Cluster 13 can be used for sensor crosscalibration. Eventually, North Africa can be used a continental scale PICS