Worldwide Optimal PICS Search

Abstract

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