Dynamical post-processing of environmental electronic maps extracted from large scale remote sensing imagery

A new intelligent computational paradigm based on the use of dynamical filtering techniques modified to enhance the quality of reconstruction of physical characteristics of environmental electronic maps extracted from the large scale remote sensing imagery is proposed. A robust Kalman filterbased algorithm is developed for the analysis of the dynamic behavior of hydrological indexes extracted from the real-world remotely sensed scenes. The simulation results verify the efficiency of the proposed approach as required for decision support in environmental resources management.