Review of Data mining applications in forestry sector

Modern technology makes possible to collect large amount of data that can be processed and transformed invaluable information for several human activities. Forest industry particularly can take advantage of suchtechnology because of modern forest harvesters are equipped with a system for data collection and communicationcalled StanForD. Data mining allows users to process large databases to determine trends and patterns. In thisextended abstract we present a brief revision of the literature dedicated to the issue and, also, we indicatesynthetically future research directions that could be useful for forest operations management. Some DMtechniques are artificial neural network and decision tree and they are used to perform association, classificationand clustering. Nonetheless, data mining techniques have been successfully applied to several fields, e.g. industry,marketing, sociology, economy, agriculture and environmental sciences. ; Fil: Broz, Diego Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Misiones. Facultad de Ciencias Forestales; Argentina ; Fil: Olivera, Alejandro. Universidad de la República; Uruguay ; Fil: Viana Céspedes, Víctor. Universidad de la República; Uruguay ; Fil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina ; First International Conference on Agro Big Data and Decision Support Systems in Agriculture ; Montevideo ; Uruguay ; Universidad de la República