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

Abstract

Pseudo-Invariant Calibration Sites (PICS) have been widely used by the remote sensing community in recent decades for post-launch absolute calibration, cross-calibration, and the monitoring of radiometric stability. The Committee on Earth Observation Satellites (CEOS) has established several official PICS for these purposes. Of these, Libya-4 is the most commonly used, due to its high uniformity and stability. The site was chosen as a large-area site for medium resolution sensors, and with high-resolution sensors now common, smaller sites are being identified. This work has identified an improved area of interest (AOI) within Libya-4 by using combined Landsat 8 and Sentinel 2 data. The Optimized Ground Target (OGT) was determined by calculating the coefficient of variation along with the use of a quasi-Newton optimization algorithm combined with the Basin–Hopping global optimization technique to constrain a search area small enough to perform a final brute-force refinement. The Coefficient of Variation CV of the proposed OGT is significantly lower than that in the original CEOS area, with differences between the CV of both zones in the order of 1% in the visible near-infrared (VNIR) bands. This new AOI has the potential to improve the cross-calibration between high-resolution sensors using the PICS methodology through an OGT with more homogeneous and stable characteristics.

Research Progress on Models, Algorithms, and Systems for Remote Sensing Spatial-Temporal Big Data Processing

“…Intelligent computing of RS-STBD involves information extraction theories such as target detection [31] and image segmentation [32], target classification and recognition [33], target location [34], path tracking [35], path prediction, target information extraction [36], information fusion [37], information retrieval [38], and other information extraction theories. Spatial-temporal analysis aims to quantitatively analyze and mine spatial-temporal semantic relations and patterns of RS-STBD including observation objects by means of machine learning, artificial intelligence, and mathematics statistics and analysis.…”

An Empirical Radiometric Intercomparison Methodology Based on Global Simultaneous Nadir Overpasses Applied to Landsat 8 and Sentinel-2

“…Using the CV, an algorithm searched for spatially homogeneous areas [32,33] on each S2 band, and extracted TOA reflectance statistics for each individual area. The same areas were used to extract statistics on the corresponding bands of the L8 dataset.…”