PAGrid: A probabilistic area-weighted gridding method for seamless mapping of sentinel-3 swath data

Swath-based remote sensing data often exhibit spatial discontinuities after mapping to latitude-longitude grids at a regular spacing due to uneven sampling caused by varying viewing angles and limitations of the conventional center point-based gridding method (CPGrid). A more complex area-weighted gridding method can enhance spatial continuity, but it requires geometric calculations for each grid and is computationally intensive, especially for large-scale satellite imagery. To balance accuracy and efficiency, we proposed a probabilistic area-weighted gridding method (PAGrid), which approximates area-weighting by aggregating results from multiple randomized spatial perturbations. The performance of PAGrid was evaluated using all available Sentinel-3A and 3B observations in 2022 over Germany. Using the canopy absorption coefficient by chlorophyll in the red-edge band ( α RE ) as a test variable, we generated 8-day composites and compared results from CPGrid and PAGrid methods. PAGrid increased the median percentage of valid grid cells from 85% to 93% and reduced temporal fluctuations by 21% compared to CPGrid. Additionally, PAGrid improved the correlation (R 2 ) between Sentinel-3A and 3B α RE from 0.73 to 0.84, indicating enhanced data consistency. These improvements indicate that PAGrid is a practical and efficient approach for generating consistent and continuous gridded time series from swath-based satellite observations. • A novel gridding method (PAGrid) mimics area-weighting without geometry modeling. • PAGrid reduces gaps in Sentinel-3 swath data via randomized perturbations. • PAGrid improves Sentinel-3A/B consistency with R 2 increased from 0.73 to 0.84. • PAGrid increases valid grid coverage from 85 % to 93 % in 8-day composites. • PAGrid reduces temporal noise by mitigating artifacts from pixel-grid mismatch.