EXTRACTING VEGETATIONAL FEATURES FROM LANDSAT MAPS: USING A DELAY AND SUM BEAMFORMING FOR IMAGE PROCESSING

Remote sensing has been performing a robust help in addressing issues related to extract information from satellite, and airbome-based platforms. This extraction is certainly a way for making quality and quantity analysis, hence measurements. This paper intends to illustrate the application of the delay and sum beamforming (DSB) approach to characterize satellite maps, in particular Landsat ones, for classifying different soil/land characteristics. The algorithm has been tested to detect the vegetation index from Lansat images of the city of Kinshasa (DR Congo). The DSB has demonstrated to exhibit better results than traditional techniques because of its accurate and reliable results.