SCBMLD: a photon signal extraction method for ICESat-2 satellite-derived bathymetry.

The integration of satellite remote sensing imagery with ICESat-2 photons offers an effective, economical, and large-scale approach for mapping shallow seabed topography. However, ICESat-2 photon data are vulnerable to noise from sea surface fluctuations, water quality, and instrument errors, which can compromise the accuracy of bathymetric products. To address this challenge, we propose a scale compression-based machine learning denoising (SCBMLD) method for accurate seafloor photon signal extraction from ICESat-2 data, enhancing bathymetry inversion in multispectral imagery.

Study of full-link on-orbit geometric calibration using multi-attitude imaging with linear agile optical satellite.

We conducted a systematic investigation into independent on-orbit geometric calibration, with the aim of applying it to linear agile optical satellite (AOS). Using a combination of multi-attitude images, a complete full-link independent calibration method chain was achieved, in which both the internal and external systematic parameters could be calibrated using the self-constraint of these images, as distinct from the absolute constraints identified from ground calibration sites. In accordance with the capacity for restraint associated with the self-constraint of the images and the geometric characteristics of the systematic errors in the imaging model, the calibration parameters that were deemed suitable for mathematical estimation under this self-constraint, as well as capable of compensating for the systematic errors, were determined by two equivalent compensations.