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

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

Multitemporal Cross-Calibration of the Terra MODIS and Landsat 7 ETM+ Reflective Solar Bands

In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between MODIS and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A MODIS split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the MODIS precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing

Worldwide Optimal PICS Search

Pseudo Invariant Calibration Sites (PICS) have proven to be a dependable calibration source for determining degradation of visible and infrared sensor response due to their temporal stability and spatial uniformity. One limit of PICS is that only a handful have been identified, primarily in desert areas of North Africa, Saudi Arabia, and elsewhere. A large number of PICS would not only facilitate calibration of existing and future sensors, but also provide an alternative to internal on-board calibrator data, resulting in significant cost savings and simplification in sensor design. As a result, the process to efficiently identify additional PICS is highly desirable. A relatively straightforward algorithm and processing flow to identify candidate PICS throughout the world has been developed. One goal of the algorithm is to identify PICS with reflectance levels covering more of the sensor dynamic range. As currently implemented, the algorithm makes use of Google Earth Engine to simplify the required image data pre-processing, analysis, and storage, and implements a filtering technique to enhance contiguity of pixels identified as invariant. Application of the proposed algorithm identified not only existing North Africa and Middle East sites with 2% to 2.5% temporal uncertainty, but also sites on other continents with 5% to 6% uncertainty, which can be improved with application of BRDF correction. In general, the algorithm shows potential in providing a means for automated PICS identification

Suomi NPP VIIRS DNB and RSB M Bands Detector-To-Detector and HAM Side Calibration Differences Assessment Using a Homogenous Ground Target

Near-nadir observations of the Libya 4 site from the S-NPP VIIRS Day-Night Band (DNB) and Moderate resolution Bands (M bands) are used to assess the detector calibration stability and half-angle mirror (HAM) side differences. Almost seven years of Sensor Data Records products are extracted from the Libya 4 site center over an area of 3232 pixels. The mean values of the radiance from individual detectors per HAM side are computed separately. The comparison of the normalized radiance between detectors indicates that the detector calibration differences are wavelength dependent and the differences have been slowly increasing with time for short wavelength bands, especially for M1-M4. The maximum annual average differences between DNB detectors are 0.77% in 2017 at HAM-A. For the M bands, the maximum detector differences in 2017 are 1.7% for M1, 1.8% for M2, 1.3% for M3, 1.2% for M4, 0.67% for M5, 0.75% for M7, 0.57% for M8, 13% for M9, 0.63% for M10, and 0.66% for M11. The average HAM side A to B difference in 2017 are 0.00% for DNB, 0.22% for M1, 0.17% for M2, 0.15% for M3, 0.09% for M4, -0.07% for M5, 0.02% for M7, 0.01% for M8, 1.4% for M9, 0.01% for M10, and 0.03% for M11. Results for M6 are not available due to the signal saturation and M9 results are not accurate because of the low reflectance from the desert site and the strong atmospheric absorption in this channel. The results in this study help scientists better understand each detectors performance and HAM side characteristics. Additionally, they provide evidence and motivation for future VIIRS calibration improvements

Normalization of Pseudo-invariant Calibration Sites for Increasing the Temporal Resolution and Long-Term Trending

Given their low level of temporal, spatial, and spectral variability, Pseudo-Invariant Calibration Sites (PICS) have been increasingly desired as data sources for radiometric calibration of Earth imaging satellite sensors. The temporal resolution for PICS data acquired by any sensor is limited by the amount of time required for it to make subsequent passes over the site. Consequently, for any given PICS, it can take many years of imaging to develop a sufficient amount of cloud-free data to perform radiometric calibration; this can be especially problematic for sensors in their early years after launch. This thesis presents techniques to combine Landsat-8; normally acquiring data for every 16 days, image data from multiple PICS into a single dataset with increased temporal resolution and is called “PICS Normalization Process” or PNP. Landsat-8 Operational Land Imager (OLI) data from six Saharan desert sites were normalized to the Libya-4 reference. The normalized data were then merged into a “Super PICS” dataset, and the estimation of calibration drift was derived. The results of the Super PICS dataset show that the temporal resolution of the calibration dataset can be increased by approximately a factor of three to four times. The normalization process was performed on radiometrically and geometrically corrected image data (“L1T” product), and also on the same image data corrected for BRDF effects using a quadratic function of the solar zenith angle and TOA reflectance over a region of interest. An additional uncertainty analysis was performed using the BRDF corrected image data based on the following parameters which are involved in this whole BRDF PICS Normalization Process: Worst-case histogram bin analysis, Temporal Uncertainty of each PICS, BRDF Super PICS uncertainty. The resulting uncertainties are within the currently accepted satellite calibration range, within 3% for all spectral bands. Overall, the process indicates a calibration drift for OLI within 0.15% per year, agreeing quite well with the calibration drift derived from the on-board calibrators

Initial Stability Assessment of S-NPP VIIRS Reflective Solar Band Calibration Using Invariant Desert and Deep Convective Cloud Targets

The latest CERES FM-5 instrument launched onboard the S-NPP spacecraft will use the VIIRS visible radiances from the NASA Land Product Evaluation and Analysis Tool Elements (PEATE) product for retrieving the cloud properties associated with its TOA flux measurement. In order for CERES to provide climate quality TOA flux datasets, the retrieved cloud properties must be consistent throughout the record, which is dependent on the calibration stability of the VIIRS imager. This paper assesses the NASA calibration stability of the VIIRS reflective solar bands using the Libya-4 desert and deep convective clouds (DCC). The invariant targets are first evaluated for temporal natural variability. It is found for visible (VIS) bands that DCC targets have half of the variability of Libya-4. For the shortwave infrared (SWIR) bands, the desert has less variability. The brief VIIRS record and target variability inhibits high confidence in identifying any trends that are less than 0.6yr for most VIS bands, and 2.5yr for SWIR bands. None of the observed invariant target reflective solar band trends exceeded these trend thresholds. Initial assessment results show that the VIIRS data have been consistently calibrated and that the VIIRS instrument stability is similar to or better than the MODIS instrument

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

Hyperspectral Empirical Absolute Calibration Model Using Libya 4 Pseudo-Invariant Calibration Site

The objective of this paper is to find an empirical hyperspectral absolute calibration model using Libya 4 pseudo-invariant calibration site (PICS). The approach involves using the Landsat 8 (L8) Operational Land Imager (OLI) as the reference radiometer and using Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm as a hyperspectral source. This model utilizes data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the Libya 4 PICS. It uses an improved, simple, empirical, hyperspectral Bidirectional Reflectance Distribution function (BRDF) model accounting for four angles: solar zenith and azimuth, and view zenith and azimuth angles. This model can perform absolute calibration in 1 nm spectral resolution by predicting TOA reflectance in all existing spectral bands of the sensors. The resultant model was validated with image data acquired from satellite sensors such as Landsat 7, Sentinel 2A, and Sentinel 2B, Terra MODIS, Aqua MODIS, from their launch date to 2020. These satellite sensors differ in terms of the width of their spectral band-pass, overpass time, off-nadir viewing capabilities, spatial resolution, and temporal revisit time, etc. The result demonstrates the efficacy of the proposed model has an accuracy of the order of 3% with a precision of about 3% for the nadir viewing sensors (with view zenith angle up to 5°) used in the study. For the off-nadir viewing satellites with view zenith angle up to 20°, it can have an estimated accuracy of 6% and precision of 4%