Binary tree genetic algorithm with quadtree for land cover classifications

Abstract

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+.