A method for determining medium quality factor is developed on the basis of analyzing the attenuation dispersion of the arrived first period P wave. In order to enhance signal to noise ratio, improve the resolution in...A method for determining medium quality factor is developed on the basis of analyzing the attenuation dispersion of the arrived first period P wave. In order to enhance signal to noise ratio, improve the resolution in measurement and reduce systematic error we applied the data resampling technique. The group velocity delay of P wave was derived by using an improved multi-filtering method. Based on a linear viscoelastic relaxation model we deduced the medium quality factor Qm, and associated error with 95% confidence level. Applying the method to the seismic record of the Xiuyan M=5.4 earthquake sequences we obtained the following result: 1 High Qm started to appear from Nov. 9, 1999. The events giving the deduced high Qm value clustered in a region with their epicenter dis- tances being between 32 and 46 km to the Yingkou station. This Qm versus distance observation obviously deviates from the normal trend of Qm linearly increasing with distance. 2 The average Qm before the 29 Dec. 1999 M=5.4 earthquake is 460, while the average Qm between the M=5.4 event and the 12 Jan. 2000 M=5.1 earthquake is 391, and the average Qm after the M=5.1 event is 204.展开更多
Direction-dependence,or anisotropy,of spatial distribution patterns of vegetation is rarely explored due to neglect of this ecological phenomenon and the paucity of methods dealing with this issue.This paper proposes ...Direction-dependence,or anisotropy,of spatial distribution patterns of vegetation is rarely explored due to neglect of this ecological phenomenon and the paucity of methods dealing with this issue.This paper proposes a new approach to anisotropy analysis of spatial distribution patterns of plant populations on the basis of the data resam-pling technique(DRT)combined with Ripley’s L index.Using the ArcView Geographic Information System(GIS)platform,a case study was carried out by selecting the popula-tion of Pinus massoniana from a needle-and broad-leaved mixed forest community in the Heishiding Nature Reserve,Guangdong Province.Results showed that the spatial pattern of the P.massoniana population was typically anisotropic with different patterns in different directions.The DRT was found to be an effective approach to the anisotropy analysis of spatial patterns of plant populations.By employing resam-pling sub-datasets from the original dataset in different direc-tions,we could overcome the difficulty in the direct use of current non-angular methods of pattern analysis.展开更多
基金State Key Project of Science and Technology during the Tenth Five-year Plan (2004BA601B01-03-01).
文摘A method for determining medium quality factor is developed on the basis of analyzing the attenuation dispersion of the arrived first period P wave. In order to enhance signal to noise ratio, improve the resolution in measurement and reduce systematic error we applied the data resampling technique. The group velocity delay of P wave was derived by using an improved multi-filtering method. Based on a linear viscoelastic relaxation model we deduced the medium quality factor Qm, and associated error with 95% confidence level. Applying the method to the seismic record of the Xiuyan M=5.4 earthquake sequences we obtained the following result: 1 High Qm started to appear from Nov. 9, 1999. The events giving the deduced high Qm value clustered in a region with their epicenter dis- tances being between 32 and 46 km to the Yingkou station. This Qm versus distance observation obviously deviates from the normal trend of Qm linearly increasing with distance. 2 The average Qm before the 29 Dec. 1999 M=5.4 earthquake is 460, while the average Qm between the M=5.4 event and the 12 Jan. 2000 M=5.1 earthquake is 391, and the average Qm after the M=5.1 event is 204.
基金This paper was supported by the National Natural Science Foundation of China(Grant No.30370254).
文摘Direction-dependence,or anisotropy,of spatial distribution patterns of vegetation is rarely explored due to neglect of this ecological phenomenon and the paucity of methods dealing with this issue.This paper proposes a new approach to anisotropy analysis of spatial distribution patterns of plant populations on the basis of the data resam-pling technique(DRT)combined with Ripley’s L index.Using the ArcView Geographic Information System(GIS)platform,a case study was carried out by selecting the popula-tion of Pinus massoniana from a needle-and broad-leaved mixed forest community in the Heishiding Nature Reserve,Guangdong Province.Results showed that the spatial pattern of the P.massoniana population was typically anisotropic with different patterns in different directions.The DRT was found to be an effective approach to the anisotropy analysis of spatial patterns of plant populations.By employing resam-pling sub-datasets from the original dataset in different direc-tions,we could overcome the difficulty in the direct use of current non-angular methods of pattern analysis.