Classification of Eucalyptus Plantation Based on Multiple Remote Sensing Data

High resolution Quickbird images in April 2014, that of Landsat 8 during the year of 2014 and digital elevation model in 2013 in Heyuan, Guangdong province were selected as the data sources for classification of eucalyptus plantation, with decision tree and object-oriented classification method. Region of interest was selected in multidate Landsat 8, the optimal segmentation scale was calculated by estimate of scale parameter, and analysis on the high resolution remote sensing images by gray level co-occurrence matrix, best texture parameters were selected. Classification decision tree was selected by parameters from spectrum, DEM and SLOPE information, and eucalyptus plantation was classified by object-oriented method. The classification accuracy reached 89.7%.