Multi-Scale Segmentation,Object-Based Extraction of Moso Bamboo Forest from SPOT5 Imagery

Based on SPOT5 remotely sensed imagery,this research focused on delineating moso bamboo forest using object-based method,which provided the advantages of multi-scale segmentation and developing hierarchical structure.The results showed that: 1) The most appropriate window sizes for calculating texture using red( R),green( G) and blue( B) band in SPOT5 image were 9 ×9,7 ×7,9 ×9; 2) Extracting moso bamboo using multi-scale segmentation technique of object-based method was more accurate,with the producer's accuracy reaching 90%,obviously higher than that of the conventional maximum likelihood method( 88. 57%); 3) Multiresolution segmentation with the aid of texture not only ensured the accuracy of moso bamboo,but also provided help to the other forest types. The overall accuracy was 92% and the Kappa coefficient was 88. 14%,both of which were the highest accuracy in the present study.