This research is interested in active sustainable management of forest, by using various remote sensing techniques to acquire relevant information for the decision making process. Once raw data is collected, we develop, improve or test existing algorithms to supply the needed data for developing management plans or forecast forest dynamics. Our focus is in modeling forest understood in a broad sense using modern techniques, such as computer vision, fractals, or abstract algebra. The main instruments used for data acquisition are unnamed aerial systems equipped with lidar, RGB, and multispectral sensors.

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