Automatic reference image selection and preparation for empirical model-based atmospheric corrections

Tun-Yu Liao; Li-Yu Chang

doi:10.1117/12.3041613

20 December 2024 Automatic reference image selection and preparation for empirical model-based atmospheric corrections

Tun-Yu Liao, Li-Yu Chang

Author Affiliations +

Proceedings Volume 13266, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII; 132660Q (2024) https://doi.org/10.1117/12.3041613
Event: Asia-Pacific Remote Sensing, 2024, Kaohsiung, Taiwan

Conference Poster

Abstract

High-quality reference images are crucial for empirical model-based atmospheric corrections. The Taiwan Space Agency (TASA) has developed an approach that uses Surface Reflectance (SR) from Sentinel-2 as a reference for these corrections. To enhance efficiency, the selection and preparation of reference images must be automated. Therefore, a procedure for optimal reference image selection has been developed. This procedure includes three main steps: First, Setting the search criteria based on input images, such as acquisition date and geographic locations. Second, using remote servers to search for all available reference images within the given period and calculating cloud cover over land. Third, retrieving the top three cloudless reference images as candidates for atmospheric corrections. After applying atmospheric corrections, the result with the most Pseudo-Invariant Features (PIFs) will be selected as the final output.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Tun-Yu Liao and Li-Yu Chang "Automatic reference image selection and preparation for empirical model-based atmospheric corrections", Proc. SPIE 13266, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII, 132660Q (20 December 2024); https://doi.org/10.1117/12.3041613

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