A review of geostatistical simulation models applied to satellite remote sensing: Methods and applications

Despite an ever-increasing number of spaceborne, airborne, and ground-based data acquisition platforms, remote sensing are still often spatially incomplete or temporally irregular. While deterministic interpolation techniques used, they tend to create unrealistic spatial patterns generally do not provide uncertainty quantification. Geostatistical simulation models effective in generating ensemble realistic equally probable realizations unmeasured phenomenon, allowing be propagated. These commonly used several fields earth science, recent years, have been applied widely remotely sensed data. This study provides the first review applications geostatistical We relevant satellite discuss characteristics advantages each approach. Finally, model categorized different domains natural sciences, including soil, vegetation, topography, atmospheric science.