Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake event.However,a variety of ground objects,including roads and bare land,have spectral characteristics simila...Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake event.However,a variety of ground objects,including roads and bare land,have spectral characteristics similar to those of co-seismic landslides,making it difficult to gather information and assess their impact rapidly and accurately.Therefore,an automatic detection method based on a deep learning model,named ENVINet5,with multiple features(ENVINet5_MF)was proposed to solve this problem and improve the detection accuracy of co-seismic landslides.The ENVINet5_MF method is advantageous for co-seismic landslide detection because it features a landslide gain index(LGI)that effectively eliminates the spectral interference of bare land and roads.We conducted two experiments using multi-temporal PlanetScope images acquired in Hokkaido,Japan,and Mainling,China.The accuracy evaluation and rationality analysis show that ENVINet5_MF performed better than comparative methods and that the co-seismic landslide areas detected by ENVINet5_MF were the most consistent with ground reference data.The findings of this study suggest that ENVINet5_MF can provide an efficient and accurate method for coseismic landslide detection to ensure a rapid response to co-seismic landslide disasters.展开更多
In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system （MEMS） gyroscope are analyzed in principle. A novel drive circuit for...In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system （MEMS） gyroscope are analyzed in principle. A novel drive circuit for the MEMS gyroscope in digital closed-loop control is proposed, which utilizes a digital phase-locked loop （PLL） in frequency control and an automatic gain control （AGC） method in amplitude control. A digital processing circuit with a field programmable gate array （FPGA） is designed and the experiments are carried out. The results indicate that when the temperature changes, the drive frequency can automatically track the resonant frequency of gyroscope in drive mode and that of the oscillating amplitude holds at a set value. And at room temperature, the relative deviation of the drive frequency is 0.624 ×10^-6 and the oscillating amplitude is 8.0 ×10^-6, which are 0. 094% and 18. 39% of the analog control program, respectively. Therefore, the control solution of the digital PLL in frequency and the AGC in amplitude is feasible.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.42271078)the Key Research and Development Program of Shaanxi(Grant No.2024SF-YBXM669)the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(Grant No.2019QZKK0902)。
文摘Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake event.However,a variety of ground objects,including roads and bare land,have spectral characteristics similar to those of co-seismic landslides,making it difficult to gather information and assess their impact rapidly and accurately.Therefore,an automatic detection method based on a deep learning model,named ENVINet5,with multiple features(ENVINet5_MF)was proposed to solve this problem and improve the detection accuracy of co-seismic landslides.The ENVINet5_MF method is advantageous for co-seismic landslide detection because it features a landslide gain index(LGI)that effectively eliminates the spectral interference of bare land and roads.We conducted two experiments using multi-temporal PlanetScope images acquired in Hokkaido,Japan,and Mainling,China.The accuracy evaluation and rationality analysis show that ENVINet5_MF performed better than comparative methods and that the co-seismic landslide areas detected by ENVINet5_MF were the most consistent with ground reference data.The findings of this study suggest that ENVINet5_MF can provide an efficient and accurate method for coseismic landslide detection to ensure a rapid response to co-seismic landslide disasters.
基金The National Natural Science Foundation of China(No. 60974116 )the Research Fund of Aeronautics Science (No.20090869007)Specialized Research Fund for the Doctoral Program of Higher Education (No. 200902861063)
文摘In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system （MEMS） gyroscope are analyzed in principle. A novel drive circuit for the MEMS gyroscope in digital closed-loop control is proposed, which utilizes a digital phase-locked loop （PLL） in frequency control and an automatic gain control （AGC） method in amplitude control. A digital processing circuit with a field programmable gate array （FPGA） is designed and the experiments are carried out. The results indicate that when the temperature changes, the drive frequency can automatically track the resonant frequency of gyroscope in drive mode and that of the oscillating amplitude holds at a set value. And at room temperature, the relative deviation of the drive frequency is 0.624 ×10^-6 and the oscillating amplitude is 8.0 ×10^-6, which are 0. 094% and 18. 39% of the analog control program, respectively. Therefore, the control solution of the digital PLL in frequency and the AGC in amplitude is feasible.
