GIS-based stochastic modeling of physical accessibility using GPS-based floating car data and Monte Carlo simulation

The term physical accessibility has long been used by geographers, economists, and urban planners and reflects the relative ease of access to/from several urban/rural services by considering the traveling costs. Numerous accessibility measures, ranging from simple to sophisticated, can be observed in the geographical information systems (GIS)-based accessibility modeling literature. However, these measures are generally calculated from a constant catchment boundary (a most likely or average catchment boundary) based on constant deterministic transportation costs. This is one of the fundamental shortcomings of the current GIS-based accessibility modeling and creates uncertainty about the accuracy and reliability of the accessibility measures, especially when highly variable speeds in road segments are considered. The development of a new stochastic approach by using global positioning system (GPS)-based floating car data and Monte Carlo simulation (MCS) technique could enable handling the variations in transportation costs in a probabilistic manner and help to consider all possible catchment boundaries, instead of one average catchment boundary, in accessibility modeling process. Therefore, this article proposes a stochastic methodology for GIS-based accessibility modeling by using GPS-based floating car data and MCS technique. The proposed methodology is illustrated with a case study on medical emergency service accessibility in Eskisehir, Turkey. Moreover, deterministic and stochastic accessibility models are compared to demonstrate the differences between the models. The proposed model could provide better decision support for the decision-makers who are supposed to deal with accessibility, location/allocation, and service/catchment area related issues.     

An integrated fuzzy-stochastic modeling approach for assessing health-impact risk from air pollution

High concentrations of air pollutants in the ambient environment can result in breathing problems with human communities. Effective assessment of health-impact risk from air pollution is important for supporting decisions of the related detection, prevention, and correction efforts. However, the quality of information available for environmental/health risk assessment is often not satisfactory enough to be presented as deterministic numbers. Stochastic method is one of the methods for tackling those uncertainties, by which uncertain information can be presented as probability distributions. However, if the uncertainties can not be presented as probabilities, they can then be handled through fuzzy membership functions. In this study, an integrated fuzzy-stochastic modeling (IFSM) approach is developed for assessing air pollution impacts towards asthma susceptibility. This development is based on Monte Carlo simulation for the fate of SO₂ in the ambient environment, examination of SO₂ concentrations based on the simulation results, quantification of evaluation criteria using fuzzy membership functions, and risk assessment based on the combined fuzzy-stochastic information. The IFSM entails (a) simulation for the fate of pollutants in ambient environment, with the consideration of source/medium uncertainties, (b) formulation of fuzzy air quality management criteria under uncertain human-exposure pathways, exposure dynamics, and SPG-response variations, and (c) integrated risk assessment under complexities of the combined fuzzy/stochastic inputs of contamination level and health effect (i.e., asthma susceptibility). The developed IFSM is applied to a study of regional air quality management. Reasonable results have been generated, which are useful for evaluating health risks from air pollution. They also provide support for regional environmental management and urban planning.     

Simplified formulae for the BIQUE estimation of variance components in disjunctive observation groups

 General rigorous and simplified formulae are reported for the best invariant quadratic unbiased estimates of the variance–covariance components, which can be applied to all least-squares adjustments with the general linear stochastic model. Simplified procedures are given for two cases frequently recurring in geodetic applications: uncorrelated groups of correlated or uncorrelated observations, with more than one variance component in each group. Received: 19 November 1998 / Accepted: 21 March 2000     

Mobile layer thickness in sheet flow beneath random waves

The erosion depth and the sheet flow layer thickness represent two characteristic parameters for transport processes in oscillatory sheet flow. Formulas for these parameters under regular waves have been applied to obtain characteristic statistical values under random waves. The applicability of the method for practical purposes is illustrated by two examples using data typical for field conditions at water depths of 70 m (Ekofisk location in the North Sea) and 15 m, respectively. Two fictive storms based on the Dohmen-Janssen and Hanes [Dohmen-Janssen, C.M., Hanes, D.M., 2005. Sheet flow and suspended sediment due to wave groups in a large wave flume. Cont. Shelf Res. 25, 333–347] data from large scale wave flume tests have also been utilized to demonstrate how the return period of the sheet flow layer thickness observed in their experiments can be estimated.     

3D finite-difference simulations of strong ground motions in the Yanhuai area, Beijing, China during the 1720 Shacheng earthquake (Ms 7.0) using a stochastic finite-fault model

Three-dimensional finite-difference (3D-FD) simulations of earthquake wave propagations in the Yanhuai area were performed for the 1720 Shacheng earthquake (M_s 7.0) using a stochastic finite-fault model, running on a parallel supercomputer Hitachi-SR8000 (http://www.lrz-muenchen.de). A stochastic finite-fault model was implemented into the 3D-FD program. The basic idea of the stochastic finite-fault model is that the fault plane can be subdivided into several subfaults (or elements, sources). Radiation from a large earthquake is the sum of contributions from all subfaults with proper time delays, each of which acts as a small independent double-couple point source. Heterogeneity of the fault rupture process was modeled by randomizing the location of initial rupture (hypocenter), slip vectors (slip, rake), and rise-times of subfaults in this study. A 3D velocity model of the Yanhuai area was constructed based on studies that analyzed available geological and geophysical information. A grid increment of 75 m in three directions was used in the 3D-FD simulation, which made it possible to capture the short period information with a resolution as low as 0.5 s in sediment regions. The uncertainties of simulated results caused by the stochastic finite-fault model were studied with a homogeneous 3D model. We found that the effects of the randomness of source on simulated ground motions are only limited in near-fault-region including the surface exposure of the fault and its vicinities, which occupies about 5% of the whole study area. This article presents an integrated approach for simulating the strong ground motions for engineering purpose using the 3D-FD method. Such simulations would be useful for hazard mapping, land using planning, insurance rate assessment, particularly in planning, preparedness, and coordinating emergency response, which must be based on realistic situations induced by concrete (historic or scenario) earthquakes.     

Stochastic analysis of the second-order hydrodynamic quantities for offshore structures

The present study considers the prediction of extreme values of the second-order hydrodynamic parameters related to offshore structures in waves, where the application of Gaussian distribution is not valid. Particularly, this study focuses on a characteristic function approach in the frequency domain to estimate the probability distribution of the second-order quantities, and the results are compared with direct simulations in the time domain. The stochastic behaviors of the second-order hydrodynamic quantities are investigated with the characteristic function approach, which involves eigenvalue analyses of Hermitian kernels constructed with quadratic transfer functions. Three different second-order responses are considered: the springing responses of TLP tendons representative of the sum-frequency problem, the slow-drift motions of a semi-submersible platform moored in waves as a representative of the difference-frequency problem, and the wave run-up around a vertical column for regular and irregular waves. The applicability of the present approach in predicting extreme values is assessed by comparing the results with the values obtained from time-domain signals.     

Toward objective rockfall trajectory simulation using a stochastic impact model

The accuracy of rockfall trajectory simulations depends to a large extent on the calculation of the rebound of falling boulders on different parts of a slope where rockfalls could occur. The models commonly used for rebound calculation are based on restitution coefficients, which can only be calibrated subjectively in the field. To come up with a robust and objective procedure for rebound calculation, a stochastic impact model associated with an objective field data collection method was developed and tested in this study. The aims of this work were to assess the adequacy of this approach and to evaluate the minimum amount of field data required to obtain simulation results with a satisfactory level of predictability. To achieve these objectives, the rebound calculation procedure developed was integrated into a three-dimensional rockfall simulation model, and the simulated results were compared with those obtained from field rockfall experiments. For rocky slopes, the simulations satisfactorily predict the experimental results. This approach is advantageous because it combines precise modelling of the mechanisms involved in the rebound and of their related variability with an objective field data collection procedure which basically only requires collecting the mean size of soil rocks. The approach proposed in this study therefore constitutes an excellent basis for the objective probabilistic assessment of rockfall hazard.     

Détection des transitions lithologiques par l'analyse de la composante fractale des diagraphies par transformée continue en ondelettes

The frequency analysis of many log data permits to verify that their stochastic component show ‘power-law-type’ spectral densities, characteristic of $1/f$ noise. They can be modelled by fractional Brownian motions. Continuous Wavelet Transformation (CWT) provides us with very efficient methods to determine the local spectral exponents of these scaling laws. These new attributes are related to the local fractality of these signals. We first present some theoretical results and an application to a fractional Brownian motion. The second application concerns a dataset recorded in the MAR203 borehole. We show that clustering of these new pseudo-logs leads to a good resolution between different lithofacies. To cite this article: N. Zaourar et al., C. R. Geoscience 338 (2006).     

溶蚀岩体随机结构模型建立及其在岩体渗漏评价中的应用

针对中小规模裂隙和溶蚀洞穴造成的溶蚀岩体渗漏 ,本文提出了溶蚀岩体渗漏评价的一种新思路 :首先对现场开挖所揭露的有限的裂隙和溶蚀洞穴观测资料进行统计分析 ,利用统计分析结果建立溶蚀岩体随机结构模型 ;然后根据随机结构模型所反映出的裂隙和溶蚀洞穴有关参数计算渗透参数 ;最后结合区域水力学条件计算岩体渗漏量。多次模拟后可以得到渗漏量的分布规律。其中 ,建立合理的随机结构模型是关系本方法成败的关键 ,文中给出了建立溶蚀岩体随机结构模型的步骤 ,提供了随机模拟的编程思路和程序框图 ,并结合具体的工程实例对该方法的应用前景进行了讨论     

内蒙古退化草原植被对禁牧的动态响应

草原退化是内蒙古生态环境恶化的突出表现。在内蒙古典型草原地带,选定有代表性的羊草＋大针茅草原放牧退化演替变型———冷蒿群落实行封育禁牧,在自然恢复演替过程中（１９８３～１９９４年）进行动态监测。根据连续１１年监测的数据,阐述了植被恢复演替的动态响应,划分了群落恢复进程的四个阶段：冷蒿优势阶段、冷蒿＋冰草阶段、冰草优势阶段、羊草优势阶段。群落生产力由１９８３年的７４ｇ／ｍ２跃升到１９９３年的２１７ｇ／ｍ２,其中羊草是增产最高的种群。退化群落中的土壤水分与养分资源对生产力的恢复没有限制影响。植物种群拓植能力与退化群落资源过剩成为恢复演替的趋动和保证因素。经过１０余年的恢复,虽然群落生产力已接近于原生群落,但是从群落结构和稳定性来看,还未完全达到顶极群落状态。退化群落经过５年封育即可以恢复合理利用。