Land subsidence caused by compression of clay layers in Ojiya City, Japan was measured by global positioning system (GPS) between 1 April 1996 and 31 December 1998.
Three baselines were selected in and around the city, and height difference on a WGS-84 ellipsoid was measured by GPS on each baseline. The ground at the GPS station in the city subsides and rebounds 7 cm every winter and spring, respectively. Measurement accuracy was 9.5 mm standard deviation. Ground water level was observed at a well near the GPS station. Regression analysis between total strain, calculated as ratio of the height difference displacement to the total thickness of the clay layers, and the layers' effective stress change with ground water level change gave good correlation. The slope of regression line 7.0×10−11 m2/N was obtained as an average apparent coefficient of volume compressibility of the layers. 相似文献
This paper estimates the coefficients of volume compressibility from variation in compressible layer thickness and changes in piezometric heads by using detail ground surface surveys and a multilayer monitoring well at a selected site (Shigang) within the Choshui River alluvial fan in west Taiwan. The paper integrates various types of in situ monitoring tools, including leveling surveys, continuous global position system (GPS) stations, multilevel layer compression and groundwater pressure head-monitoring wells, to investigate the situation and progress of the subsidence problem in the region. The results from the cross-analyses of the measured data show that surface settlement caused by the compression of strata is between the depths of 60 and 210 m where the clayey stratum within 120-180 m was most pronounced and contributes up to 53% of the total compression. The results indicate that the clayey stratum is under normal consolidation. The results also reflect the fact that 20% of settlement contribution comes from the sandy stratum within 90-120 m; the elasto-plastic behavior of this sandy stratum is clear. The coefficients of volume compressibility of the clayey and sandy stratum analysed from the stratum's compression records; they were 6.38×10−8 and 5.71×10−9 m2/N, respectively. Ultimately, this parameter estimation would permit to control and predict land subsidence based on change in pressure head which are related to groundwater extraction. 相似文献
This paper analyzes the backscatter of the microwave signal in a boreal forest environment based on a Ku -band airborne Frequency-Modulated Continuous Waveform (FMCW) profiling radar—Tomoradar. We selected a half-managed boreal forest in the southern part of Finland for a field test. By decomposing the waveform collected by the Tomoradar, the vertical canopy structure was achieved. Based on the amplitude of the waveform, the Backscattered Energy Ratio of Canopy-to-Total (BERCT) was calculated. Meanwhile, the canopy fraction was derived from the corresponding point cloud recorded by a Velodyne VLP-16 LiDAR mounted on the same platform. Lidar-derived canopy fraction was obtained by counting the number of the first/ the strongest returns versus the total amount of returns. Qualitative and quantitative analysis of radar-derived BERCT on lidar-derived canopy fraction and canopy height are investigated. A fitted model is derived to describe the Ku-band microwave backscatter in the boreal forest to numerically analyze the proportion contributed by four factors: lidar-derived canopy fraction, radar-derived canopy height, the radar-derived distance between trees and radar sensor and other factors, from co-polarization Tomoradar measurements. The Root Mean Squared Error (RMSE) of the proposed model was 0.0958, and the coefficient of determination R2 was 0.912. The fitted model reveals that the correlation coefficient between radar-derived BERCT and lidar-derived canopy fraction is 0.84, which illustrates that lidar surface reflection explains the majority of the profiling /waveform radar response. Thus, vertical canopy structure derived from lidar can be used for the benefit of radar analysis. 相似文献
A general framework for manipulating spectra as functions in traditional multivariate methods such asPCA and PLS is described.The functional representation is very convenient for compression,ensuringsmoothness and continuity.There are two fundamentally different types of representations:(a)byfunctions and(b)by function coefficients.The use of coefficients is the most practical way of analysis. 相似文献