A classification method of building structures based on multi-feature fusion of UAV remote sensing images  

作　　者：Haoguo Du Yanbo Cao Fanghao Zhang Jiangli Lv Shurong Deng Yongkun Lu Shifang He Yuanshuo Zhang Qinkun Yu 

机构地区：[1]Yunnan Earthquake Agency,Kunming,650224,Yunnan,China

出　　处：《Earthquake Research Advances》2021年第4期38-47,共10页地震研究进展（英文）

基　　金：sponsored by National Key R&D Program of China(2018YFC1504504);Youth Foundation of Yunnan Earthquake Agency(2021K01);Project of Yunnan Earthquake Agency“Chuan bang dai”(CQ3-2021001).

摘　　要：In order to improve the accuracy of building structure identification using remote sensing images,a building structure classification method based on multi-feature fusion of UAV remote sensing image is proposed in this paper.Three identification approaches of remote sensing images are integrated in this method:object-oriented,texture feature,and digital elevation based on DSM and DEM.So RGB threshold classification method is used to classify the identification results.The accuracy of building structure classification based on each feature and the multi-feature fusion are compared and analyzed.The results show that the building structure classification method is feasible and can accurately identify the structures in large-area remote sensing images.

关 键 词：Remote sensing image Building structure classification Multi-feature fusion Object-oriented classification method Texture feature classification method DSM and DEM elevation classification method RGB threshold classification method 

分 类 号：P237[天文地球—摄影测量与遥感]