The extraction of plantation with texture feature in high resolution remote sensing image

Abstract

Remote sensing technology is widely used in land cover survey. In this experiment, firstly VSVI (vegetation sample-based vegetation index) method is used to extract the forests in experiment area, and then adding texture feature to distinguish the natural forest and plantation in forests class. Then average contrast of objects (ACO) method is used to determine the best scale of chessboard segmentation when classify, and classification accuracy of different scales is compared. It is proved that the optimal segmentation scale through ACO and the best classification results have certain consistency, and achieved high classification accuracy.