Tasks of land use and land cover change analysis according to remote sensing data are confined to the need of on-line processing of large and constantly growing volumes of satellite information. These tasks require quite complex stages, among which, three are needed to be focused on. First, storage and transmission satellite information along communication channels with the application of the specialized compression methods with and without losses. Second, automated interpretation of time series remote sensing data, a high accuracy of which is achieved via texture analysis, parametric and non-parametric statistical and artificial neural network approaches. Third, land cover and land use change modeling with the time series thematic maps allowing one to make the results of short-term and long-term forecasting on an investigated area. The solution of the specified tasks with the high precision requires the development of advanced processing data approaches as well as a considerable increase of its productivity via new methods of high-performance parallel data processing based on both the expensive supercomputer equipment and the clusters of inexpensive personal computers.