Kalman filter method for generating time-series synthetic Landsat images and their uncertainty from Landsat and MODIS observations

摘要

The Landsat program, since its commencement in 1972, has acquired millions of images of our planet. Those images are one of the most valuable Earth Observation resources for local, regional and global land surface monitoring and study due to their moderate spatial resolution and rich spectral information. However, their applications are impeded largely by their relatively low revisit frequency and cloud contamination on images. In order to improve their usability, a number of studies have been conducted to blend Landsat images with Moderate Resolution Imaging Spectroradiometer (MODIS) images to take merits of the two sensors. All blending models reported that they can predict synthetic Landsat images with various degrees of accuracy. However, only a couple of models reported that they can explicitly estimate uncertainty for their blended images.