Selection of Potential Pseudoinvariant Calibration Sites in Australia Based on Pixel-Level Cloud Cover and Rainfall Probabilities

Significant work has been done to select on Pseudo- Invariant Calibration Sites (PICS) over the past 20 years. However, regional cloud cover and rainfall factors were not fully considered in previous PICS selection work. Australia has large arid areas where PCIS are not fully explored. This paper proposed a novel method for selecting potential PICSs in Australia by utilizing cloud cover and rainfall probabilities. MOD09GA, and Global Satellite Mapping of Precipitation products from 2016 to 2022, along with the Smoothed Digital Elevation Model are utilized to identify flat areas with minimal cloud cover and rainfall. Coefficient of variation (CV) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&lt; $</tex-math></inline-formula> 0.03 and Geits statistics (Gi<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{*}$</tex-math></inline-formula>) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&gt;$</tex-math></inline-formula> 0 based on MOD09GA, Landsat Operational Land Imager (OLI), and Sentinel MultiSpectral Instrument (MSI) are used to characterize potential PICSs. Finally, we identified three potential PICSs, namely PICS1 (0.51 km<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>), PICS2 (0.35 km<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>), and PICS3 (0.23 km<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>), with annual probability of cloud- or rainfall-free exceed 80%. The feasibility of using these three PICSs for radiometric performance monitoring of satellites sensors were also verified. Results indicate that the selected PICSs were effective since the sensor annual degradation rates (%/year<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>2-sigma) of OLI and MSI over the selected PICSs range from -0.68%<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>0.35 to 0.57%<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>0.43, which are consistent with LCFR (from -0.48%<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>0.35 to 0.28%<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>0.71), except for Red band. The proposed method extends the PICS network in Australia, and introduces new ideas for potential PICS selection.