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

Abstract

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.

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

“…Pseudo invariant calibration sites have been proven as the least expensive method of on-orbit calibration. Over the last 14 years, a significant expansion in PICS use has been observed to monitor the long-term top-of-atmosphere (TOA) reflectance trends from different sensors [9][10][11]. These PICS sites are known for their spatial uniformity by manifesting stable spectral characteristics over time, higher reflectance, and negligible atmospheric impact on upward radiance [12].…”

“…Optimal regions within Libya 4, Niger 1, Sudan 1, Niger 2, Egypt 1, and Libya 1 contemplated less temporal uncertainty. Among them, Libya 4 demonstrated as the most temporally stable site with a temporal variation of less than 3% and could be broadly used in radiometric calibration work [1,3,10,16].…”

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

“…For many years, numerous researchers exploited six CEOS-endorsed PICS to monitor the calibration trend of the remote sensing satellite. Among all the PICS, Libya 4 appears to be the most stable site, with from 1% to 1.5% temporal uncertainty [116]. Consequently, Libya 4 is the most frequently used PICS.…”

Analysis of Spatial and Temporal Variability in Libya-4 with Landsat 8 and Sentinel-2 Data for Optimized Ground Target Location

“…The use of an AOI with an optimal size reduces the possible uncertainty generated by the dune effect, improving the stability of the indirect calibration [17]. Tuz Zafrin Tuli [18] showed that there is a long-term temporal variability in some PICS.The purpose of this work is to support PICS-based calibration methodologies for medium to high-resolution sensors by locating an Optimized Ground Target location (OGT) within Libya-4 with the highest possible spatial and temporal stability, based on the study of the variability of Libya-4 from a wide temporal series of combined Landsat 8 OLI (L8-OLI) (Operational Land Imager) and Sentinel 2 Multispectral Instrument MSI (S2-MSI) data using a novel numeric methodology. We use the Coefficient of Variation (CV) and a quasi-Newton optimization algorithm [19][20][21] combined with a global optimization technique [22] to constrain a search area small enough to perform a final brute-force refinement in order to define the zone with the size and optimal space-time stability.…”

“…The use of an AOI with an optimal size reduces the possible uncertainty generated by the dune effect, improving the stability of the indirect calibration [17]. Tuz Zafrin Tuli [18] showed that there is a long-term temporal variability in some PICS.…”