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

New Approach for Temporal Stability Evaluation of Pseudo-Invariant Calibration Sites (PICS)

Pseudo-Invariant Calibration Sites (PICS) are one of the most popular methods for in-flight vicarious radiometric calibration of Earth remote sensing satellites. The fundamental question of PICS temporal stability has not been adequately addressed. However, the main purpose of this work is to evaluate the temporal stability of a few PICS using a new approach. The analysis was performed over six PICS (Libya 1, Libya 4, Niger 1, Niger 2, Egypt 1 and Sudan 1). The concept of a Virtual Constellation was developed to provide greater temporal coverage and also to overcome the dependence limitation of any specific characteristic derived from one particular sensor. TOA reflectance data from four sensors consistently demonstrating stable calibration to within 5%the Landsat 7 ETM+ (Enhanced Thematic Mapper Plus), Landsat 8 OLI (Operational Land Imager), Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and Sentinel-2A MSI (Multispectral Instrument)were merged into a seamless dataset. Instead of using the traditional method of trend analysis (Students T test), a nonparametric Seasonal Mann-Kendall test was used for determining the PICS stability. The analysis results indicate that Libya 4 and Egypt 1 do not exhibit any monotonic trend in six reflective solar bands common to all of the studied sensors, indicating temporal stability. A decreasing monotonic trend was statistically detected in all bands, except SWIR 2, for Sudan 1 and the Green and Red bands for Niger 1. An increasing trend was detected in the Blue band for Niger 2 and the NIR band for Libya 1. These results do not suggest abandoning PICS as a viable calibration source. Rather, they indicate that PICS temporal stability cannot be assumed and should be regularly monitored as part of the sensor calibration process

Vicarious Calibration of EO-1 Hyperion

The Hyperion imaging spectrometer on the Earth Observing-1 satellite is the first high-spatial resolution imaging spectrometer to routinely acquire science-grade data from orbit. Data gathered with this instrument needs to be quantitative and accurate in order to derive meaningful information about ecosystem properties and processes. Also, comprehensive and long-term ecological studies require these data to be comparable over time, between coexisting sensors and between generations of follow-on sensors. One method to assess the radiometric calibration is the reflectance-based approach, a common technique used for several other earth science sensors covering similar spectral regions. This work presents results of radiometric calibration of Hyperion based on the reflectance-based approach of vicarious calibration implemented by University of Arizona during 2001 2005. These results show repeatability to the 2% level and accuracy on the 3 5% level for spectral regions not affected by strong atmospheric absorption. Knowledge of the stability of the Hyperion calibration from moon observations allows for an average absolute calibration based on the reflectance-based results to be determined and applicable for the lifetime of Hyperion

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

Absolute Radiometric Calibration of Narrow-Swath Imaging Sensors with Reference to Non-Coincident Wide-Swath Sensors

An inter-calibration method is developed to provide absolute radiometric calibration of narrow-swath imaging sensors with reference to non-coincident wide-swath sensors. The method predicts at-sensor radiance using non-coincident imagery from the reference sensor and knowledge of spectral reflectance of the test site. The imagery of the reference sensor is restricted to acquisitions that provide similar view and solar illumination geometry to reduce uncertainties due to directional reflectance effects. Spectral reflectance of the test site is found with a simple iterative radiative transfer method using radiance values of a well-understood wide-swath sensor and spectral shape information based on historical ground-based measurements. At-sensor radiance is calculated for the narrow-swath sensor using this spectral reflectance and atmospheric parameters that are also based on historical in situ measurements. Results of the inter-calibration method show agreement on the 2 5 percent level in most spectral regions with the vicarious calibration technique relying on coincident ground-based measurements referred to as the reflectance-based approach. While the variability of the inter-calibration method based on non-coincident image pairs is significantly larger, results are consistent with techniques relying on in situ measurements. The method is also insensitive to spectral differences between the sensors by transferring to surface spectral reflectance prior to prediction of at-sensor radiance. The utility of this inter-calibration method is made clear by its flexibility to utilize image pairings with acquisition dates differing in excess of 30 days allowing frequent absolute calibration comparisons between wide- and narrow-swath sensors

Directional Reflectance Studies in Support of the Radiometric Calibration Test Site (RadCaTS) at Railroad Valley

The Radiometric Calibration Test Site (RadCaTS) is a suite of commercial and custom instruments used to make measurements of the surface reflectance and atmosphere throughout the day at Railroad Valley, Nevada. It was developed in response to the need for daily radiometric calibration data for the vast array of Earth-observing sensors on orbit, which is continuously increasing as more nations and private companies launch individual environmental satellites as well as large constellations. The current suite of instruments at RadCaTS includes five ground-viewing radiometers (GVRs), four of which view the surface in a nadir-viewing configuration. Many sensors such as those on Landsat-7 and Landsat-8 view Railroad Valley within 3 of nadir, while others such as those on Sentinel-2A and -2B, RapidEye, Aqua, Suomi NPP, and Terra can view Railroad Valley at off-nadir angles. Past efforts have shown that the surface bidirectional reflectance distribution function (BRDF) has minimal impact on vicarious calibration uncertainties for views <10, but the desire to use larger view angles has prompted the effort to develop a BRDF correction for data from RadCaTS. The current work investigates the application of Railroad Valley BRDF data derived from a BRF camera developed at the University of Arizona in the 1990s (but is no longer in use) to the current RadCaTS surface reflectance measurements. Also investigated are early results from directional reflectance studies using a mobile spectro-goniometer system during a round-robin field campaign in 2018. This work describes the preliminary results, the effects on current measurements, and the approach for future measurements

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

New Approach for Temporal Stability Evaluation of Pseudo-Invariant Calibration Sites (PICS)

Pseudo-Invariant Calibration Sites (PICS) are one of the most popular methods for in-flight vicarious radiometric calibration of Earth remote sensing satellites. The fundamental question of PICS temporal stability has not been adequately addressed. However, the main purpose of this work is to evaluate the temporal stability of a few PICS using a new approach. The analysis was performed over six PICS (Libya 1, Libya 4, Niger 1, Niger 2, Egypt 1 and Sudan 1). The concept of a “Virtual Constellation” was developed to provide greater temporal coverage and also to overcome the dependence limitation of any specific characteristic derived from one particular sensor. TOA reflectance data from four sensors consistently demonstrating “stable” calibration to within 5%—the Landsat 7 ETM+ (Enhanced Thematic Mapper Plus), Landsat 8 OLI (Operational Land Imager), Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and Sentinel-2A MSI (Multispectral Instrument)–were merged into a seamless dataset. Instead of using the traditional method of trend analysis (Student’s T test), a nonparametric Seasonal Mann-Kendall test was used for determining the PICS stability. The analysis results indicate that Libya 4 and Egypt 1 do not exhibit any monotonic trend in six reflective solar bands common to all of the studied sensors, indicating temporal stability. A decreasing monotonic trend was statistically detected in all bands, except SWIR 2, for Sudan 1 and the Green and Red bands for Niger 1. An increasing trend was detected in the Blue band for Niger 2 and the NIR band for Libya 1. These results do not suggest abandoning PICS as a viable calibration source. Rather, they indicate that PICS temporal stability cannot be assumed and should be regularly monitored as part of the sensor calibration process