Author:
Dmitriev Egor,Sokolov Anton,Zotov Sergey,Kondranin Timophey,Melnik Petr
Abstract
Statistical texture features are frequently used for the thematic processing of very high spatial resolution satellite images. The assessment of information content of 1st and 2nd order statistics is carried out based on processing WorldView-2 images of test areas located on the territory of the Savvatyevskoe forestry and employing the corresponding ground-based data. The comparison of the accuracy and computational efficiency of traditional and ensemble classifiers in the problem of pattern recognition of various natural and man-made objects reveals the high performance of the error correcting output codes method. The estimates obtained in this study demonstrate the advantage of using ensemble classification and 2nd order statistical texture features.
Reference10 articles.
1. Dmitriev E.V., Sokolov A.A., Kozoderov V.V., Delbarre H., Melnik P.G., Donskoi S.A., Proc. SPIE 11149, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI, 111491J, (2019)
2. Franklin S.E., Remote sensing for sustainable forest management (CRC press, 2001).
3. Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis
4. Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery
5. Chaki J., Dey N., Texture Feature Extraction Techniques for Image Recognition (Springer Singapore, 2020)