Showing papers by "Geophysical Survey published in 2018"

Coupled inverted pendulums: stabilization problem

Abstract: A mathematical model of an unstable system in the form of inverted coupled pendulums is developed and simulated. Dynamics of such a system is investigated, and the stability zones are identified in the explicit form. The algorithm of stabilization of the pendulums near the vertical position is constructed and verified.

Nonlinear Damping: From Viscous to Hysteretic Dampers

Abstract: This paper is dedicated to a brief discussion on the nonlinear damping. We present the particular results for linear and nonlinear viscous dampers, for fractional damper and for the hysteretic damper . As a main purpose we consider the mathematical model of damper with hysteretic properties on the basis of the Ishlinsky-Prandtl model. The numerical results for the observable characteristics such as the force transmission function and the “force-displacement” transmission function are obtained and analyzed both for the cases of the periodic affection as well as for the impulse affection (in the form of \(\delta \)-function). The comparison of the efficiency of nonlinear viscous damper and hysteretic damper is also presented and discussed.

The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach.

Abstract: The neural network approach is proposed for studying very-low- and low-frequency (VLF and LF) subionospheric radio wave variations in the time vicinities of magnetic storms and earthquakes, with the purpose of recognizing anomalies of different types We also examined the days with quiet geomagnetic conditions in the absence of seismic activity, in order to distinguish between the disturbed signals and the quiet ones To this end, we trained the neural network (NN) on the examples of the representative database The database included both the VLF/LF data that was measured during four-year monitoring at the station in Petropavlovsk-Kamchatsky, and the parameters of seismicity in the Kuril-Kamchatka and Japan regions It was shown that the neural network can distinguish between the disturbed and undisturbed signals Furthermore, the prognostic behavior of the VLF/LF variations indicative of magnetic and seismic activity has a different appearance in the time vicinity of the earthquakes and magnetic storms

Sensitivity analysis about FLAASH model parameters

Abstract: When using FLAASH model to process a large number of image data automatically, it is hard to determine model parameters’ values exactly. To solve this problem, this paper analyze the sensitivity of mainly 8 model parameters. The simulated GF2 satellite multispectral dataset based on four type land cover was used as input data. These parameters are assumed to be independent and irrelevant, therefore sensitivity analysis is performed using the local analysis method. Variation coefficient was introduced into this paper to quantitatively analyze the effect of these parameters on FLAASH model. Atmosphere model, ground elevation, view zenith angle, and visibility value have dramatic effect on FLAASH model’s accuracy, the aerosol model and water column multiplier have little effect on the model. In addition, frequency resolution and view azimuth angle have no effect on the model in all four bands and four land types.

Seismotectonic Deformations of the Kuril Island Arc during Different Phases of the Seismic Cycle: The Simushir Earthquakes

Abstract: Multiyear satellite geodetic measurements along the Kuril island arc provided data for studying the condition of the Benioff seismic zone and the occurrence of various deformation mechanisms that are responsible for surface displacements. Factors have been determined whose combination can explain the diverse character of observed movements: space–time variations in interplate sliding, viscoelastic postseismic relaxation in the asthenosphere, stationary backward mantle flow, the keyboard structure of the frontal part of the subduction zone. The stationary displacement components have been detected against the background of transient processes. These components can be associated with interplate coupling and sublithospheric currents and they can be employed in order to characterize the interseismic condition of various parts along the Kuril isalnd arc. In particular, the special character of seismicity in the Middle Kuril area, which consists in long intervals of seismic quiescence interrupted by large double earthquakes, can be caused by a zone of hypothetical transition from strong interplate coupling in the southwest to poor coupling combined with a backward sublithospheric current in the northeast.

Depth Estimation and Ray Tracing Model Selection of Buried Utilities on Ground Penetrating Radar Data

Abstract: When assessing a target depth from a Ground Penetrating Radar (GPR) image, one typically assumes a certain wave propagation model as well as the model parameters (typically the dielectric of the medium). While much work has been conducted on the automatic inference of the model parameters, not much work has been performed testing the validity of the model itself. The work presented here closes this gap for a low-frequency GPR system (350 MHz center frequency). It compares the measurement, taken from known targets at known depths, with different ray propagation models. It also presents a novel method for efficiently estimating the depth of a target without using any knowledge of the medium's wave propagation speed, or even the time of the signal's emission from the transmitter (time zero). Experiments on 26 targets of varying depths showed an averaged estimation error of less than 0.5%, with a standard deviation of 3% using this robust and efficient method.

Remote Sensing Monitoring of Wetland of Sanya and Lingshui in Hainan Province, Based on gf Data

Abstract: . Wetland is an important land and natural resources with many functions. It is closely related to the survival, reproduction and development of human beings, as well as one of the most important living environments of human beings. Hainan Province, which is located in the northern edge of the tropics with the tropical monsoon climate and covers a variety of wetland types. In this paper, in order to investigate the change of wetland distribution and the variations of area in study region, the remote sensing data of GF-1 and GF-2 from 2009 to 2015 were used. The method used in this study was automatic information extraction and human-computer interaction. The wetland types in study area mainly was divided into three level-1 classes, including coastal wetland, river wetland and lake wetland, and was also divided into eight level-2 classes at the same time. The results showed that the total area of wetland increased 9.13 km2 in study area from 2009 to 2015, in which the area of constructed wetland increased 6.29 km2, the natural wetland increased only 2.83 km2. The area of natural wetland has not changed much, but its proportion has been reduced. This reflected that the wetland in the research area has been more artificially intervened since 2009, which caused the increasing of the area of constructed wetland. As the wetland resources can coordinate the sustainable benefit of the society, the protection of natural wetland should be strengthened and valued.

Comparison of water extraction methods in Tibet based on GF-1 data

Abstract: In this study, we compared four different water extraction methods with GF-1 data according to different water types in Tibet, including Support Vector Machine (SVM), Principal Component Analysis (PCA), Decision Tree Classifier based on False Normalized Difference Water Index (FNDWI-DTC), and PCA-SVM. The results show that all of the four methods can extract large area water body, but only SVM and PCA-SVM can obtain satisfying extraction results for small size water body. The methods were evaluated by both overall accuracy (OAA) and Kappa coefficient (KC). The OAA of PCA-SVM, SVM, FNDWI-DTC, PCA are 96.68%, 94.23%, 93.99%, 93.01%, and the KCs are 0.9308, 0.8995, 0.8962, 0.8842, respectively, in consistent with visual inspection. In summary, SVM is better for narrow rivers extraction and PCA-SVM is suitable for water extraction of various types. As for dark blue lakes, the methods using PCA can extract more quickly and accurately.