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Binary tree genetic algorithm with Quadtree for land cover classifications

Enhanced binary tree genetic algorithm (BTGA+) has been successfully applied to land cover classification problems. However, the execution time of BTGA+ is quite long on large datasets. In this paper, a novel decision tree algorithm, called binary tree genetic algorithm with Quadtree (BTGA with quadtree), is proposed by extending BTGA+. In the proposed algorithm, a generalized Quadtree is constructed when a new node of a linear decision tree is created. The proposed algorithm runs faster than BTGA+ on datasets with sufficiently large number of samples, without sacrificing the quality of decision trees constructed by BTGA+