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 thi...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.展开更多
Up to now, there have been many indistinctive points in the image interpretation of scanning tunnelhng microscopy (STM) system, and the problems have attracted almost all STM scientists’ attention. In 1992, Kenkre pr...Up to now, there have been many indistinctive points in the image interpretation of scanning tunnelhng microscopy (STM) system, and the problems have attracted almost all STM scientists’ attention. In 1992, Kenkre proposed the new programme which describes the behaviour of the electrons moving in the STM tunnelling by the method of exciton dynamics, and the programme not only breaks through the restrictions of Tersoff-Hamann theory, but also can be applied conveniently to discussing the effects of the tip structure, adsorbate structure, substrate structure, temperature, tunneling voltage, and the degree of coherence of elec-展开更多
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).
文摘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.
文摘Up to now, there have been many indistinctive points in the image interpretation of scanning tunnelhng microscopy (STM) system, and the problems have attracted almost all STM scientists’ attention. In 1992, Kenkre proposed the new programme which describes the behaviour of the electrons moving in the STM tunnelling by the method of exciton dynamics, and the programme not only breaks through the restrictions of Tersoff-Hamann theory, but also can be applied conveniently to discussing the effects of the tip structure, adsorbate structure, substrate structure, temperature, tunneling voltage, and the degree of coherence of elec-
