At most scales and environments, a generic term like DEM can be used because the differentiation between the bare-earth and a surface object is not significant, with DEMs commonly having spatial resolutions of 20 m or more.
Above left: The pulse of light emitted from the aircraft during LIDAR collection returns different information about the surface that it encounters. Source: USDA Natural Resources Conservation Service. Above right: Pulse backscatter sensed in the aircraft helps to classify return rank and eventually to aid creation of bare-earth terrain and first-return surfaces. Source: Gatziolis & Anderson (2008).
Cinema 4d Dem Earth 350
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Bare-earth refers to the fact that vegetation and human-made features such as trees and power lines are filtered out with DEMs. Each cell has a value corresponding to its elevation (z-values at regularly spaced intervals) in a DEM.
Although earthquake-induced gravity perturbations are frequently observed, numerical modeling of this phenomenon has remained a challenge. Due to the lackof reliable and versatile numerical tools, induced-gravity data have not been fullyexploited to constrain earthquake source parameters. From a numerical perspective, the main challenge stems from the unbounded Poisson/Laplace equation thatgoverns gravity perturbations. Additionally, the Poisson/Laplace equation must becoupled with the equation of conservation of linear momentum that governs particledisplacement in the solid. Most existing methods either solve the coupled equationsin a fully spherical harmonic representation, which requires models to be (nearly)spherically symmetric, or they solve the Poisson/Laplace equation in the sphericalharmonics domain and the momentum equation in a discretized domain, a strategythat compromises accuracy and efficiency. We present a spectral-infinite-elementapproach that combines the highly accurate and efficient spectral-element methodwith a mapped-infinite-element method capable of mimicking an infinite domainwithout adding significant memory or computational costs. We solve the completecoupled momentum-gravitational equations in a fully discretized domain, enablingus to accommodate complex realistic models without compromising accuracy or efficiency. We present several coseismic and post-earthquake examples and benchmarkthe coseismic examples against the Okubo analytical solutions. Finally, we considergravity perturbations induced by the 1994 Northridge earthquake in a 3D modelof Southern California. The examples show that our method is very accurate andefficient, and that it is stable for post-earthquake simulations.
Most earthquake location methods require phase identification and arrival-time measurements. These methods are generally fast and efficient but not always applicable to microearthquake data with low signal-to-noise ratios because the phase identification might be very difficult. The migration-based source location methods, which do not require an explicit phase identification, are often more suitable for such noisy data. Whereas some existing migration-based methods are computationally intensive, others are limited to a certain type of data or make use of only a particular phase of the signal. We have developed a migration-based source location method especially applicable to data with relatively low signal-to-noise ratios. We projected seismograms on to the ray coordinate system for each potential source-receiver configuration and subsequently computed their envelopes. The envelopes were time shifted according to synthetic P- and S-wave arrival times (computed using an eikonal solver) and stacked for a predefined time window centered on the arrival time of the corresponding phase. This was done for each component and phase individually, and the squared sum of the stacks was defined as the objective function. We applied a robust global optimization routine called differential evolution to maximize the objective function and thereby locate the seismic event. Our source location method provides a complete algorithm with only a few control parameters, making it suitable for automatic processing. We applied this method to single and multicomponent data using P and/or S phases. We conducted controlled tests using synthetic seismograms contaminated with a minimum of 30% white noise. The synthetic data were computed for a complex and heterogeneous model of the Pyhäsalmi ore mine in Finland. We also successfully applied the method to real seismic data recorded with the in-mine seismic network of the Pyhäsalmi mine.
Accurate and efficient simulations of coseismic and post-earthquake deformation areimportant for proper inferences of earthquake source parameters and subsurfacestructure. These simulations are often performed using a truncated halfspace modelwith approximate boundary conditions. The use of such boundary conditions introduces inaccuracies unless a sufficiently large model is used, which greatly increasesthe computational cost. To solve this problem, we develop a new approach by combining the spectral-element method with the mapped infinite-element method. Inthis approach, we still use a truncated model domain, but add a single outer layerof infinite elements. While the spectral elements capture the domain, the infiniteelements capture the far-field boundary conditions. The additional computationalcost due to the extra layer of infinite elements is insignificant. Numerical integrationis performed via Gauss-Legendre-Lobatto and Gauss-Radau quadrature in the spectral and infinite elements, respectively. We implement an equivalent moment-densitytensor approach and a split-node approach for the earthquake source, and discussthe advantages of each method. For post-earthquake deformation, we implement ageneral Maxwell rheology using a second-order accurate and unconditionally stablerecurrence algorithm. We benchmark our results with the Okada analytical solutionsfor coseismic deformation, and with the Savage & Prescott analytical solution andthe PyLith finite-element code for post-earthquake deformation.
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