Segú Tell, Jordi2018-10-262023-10-012018https://academica-e.unavarra.es/handle/2454/31249The management of forest resources is essential for the development of our society. This requires a forest management planning based on innovative studies, according to new technologies and seeking to lower costs. In this project, a methodology has been developed for the extraction of predictive regression models to determine the main dasometric variables of the beech forest layer with over 70% of the forest cover density in Navarre. For this purpose, data mining techniques and Python as programming language have been used. The inputs of the work are: data from the plots of the national forest inventory (dependent variables) and statistics derived from the LIDAR-PNOA flight for these same plots (independent variables) obtained with the LasTools software. The output is the model that best fits the input data, determined by the methodology used.application/pdfspaLIDARIFNPythonData miningFagus sylvaticainfo:eu-repo/semantics/masterThesis2018-10-23info:eu-repo/semantics/openAccessIngeniería cartográfica, geodésica y fotogrametría