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High-resolution paleoenvironmental data from a peat profile with a small pollen source area are used to reconstruct the impacts of landnám on vegetation and soils at a Norse farm complex (∅2 at Tasiusaq) comprising two farms in the Eastern Settlement of Greenland. Analyses include the AMS 14C dating of plant macrofossil samples and the use of Bayesian radiocarbon calibration to construct improved age-depth models for Norse cultural horizons. The onset of a regional landnám may be indicated by the clearance of Betula pubescens woodland immediately prior to local settlement. The latter is dated to AD 950-1020 (2σ) and is characterised by possible burning of Betula glandulosa scrub to provide grassland pasture for domestic stock. Clearance and grazing resulted in accelerated levels of soil erosion at a westerly farm. This was followed by an easterly migration of settlement and agriculture. Site constraints prevent an assessment of the demise of the easterly farm, but pressures of overgrazing and land degradation may have been the major factors responsible for the abandonment of the earlier farm. 相似文献
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1 .IntroductionNondestructiveinspection (NDI)isveryimportantforensuringthereliabilityofoffshorestructuresintheirservicelives (Lauraetal.,1 996 ) .Itiswellknownthatdetectionofflawsinvolvesconsider ablestatisticaluncertainties.Asaresult,theprobabilityofdetection (POD)forallflawsofagivensizehasbeenusedintheliteraturetodefinethecapabilityofaparticularNDItechniqueinagivenen vironment.SincethedataofPODusuallyscatterlargely ,itisdifficulttodeterminewhichmodelfitstheavailabledatabest.Thismodelun… 相似文献
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Statistics of nonlinear wave crests and groups 总被引:1,自引:0,他引:1
Groups of large nonlinear waves with sharper higher crests can pose hazards to ships, induce harbor resonance and cause wave-overtopping of fixed and floating structures. Past interest in wave groups has mostly been focused on the statistics and modeling of linear wave groups. Studies on nonlinear wave groups are surprisingly few, and address deep water waves only. Here, statistics of nonlinear wave crests and wave-crest groups in deep and transitional water depths are considered, using an appropriate second-order representation for crest heights and the continuous wave-envelope approach. In particular, theoretical expressions describing the statistics of nonlinear wave crests and their groups are posed in the form of a simple second-order transformation of well-known results on linear waves. Predictions from the transformation so posed compare well with nonlinear wave data gathered in the North Sea, and demonstrate that nonlinearities do affect the statistics of large wave crests and their groups significantly. 相似文献
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The Bayesian detection of discontinuities in a polynomial regression and its application to the cycle-slip problem 总被引:4,自引:1,他引:3
Maria Clara de Lacy Mirko Reguzzoni Fernando Sansò Giovanna Venuti 《Journal of Geodesy》2008,82(9):527-542
This paper deals with the problem of detecting and correcting cycle-slips in Global Navigation Satellite System (GNSS) phase
data by exploiting the Bayesian theory. The method is here applied to undifferenced observations, because repairing cycle-slips
already at this stage could be a useful pre-processing tool, especially for a network of permanent GNSS stations. If a dual
frequency receiver is available, the cycle-slips can be easily detected by combining two phase observations or phase and range
observations from a single satellite to a single receiver. These combinations, expressed in a distance unit form, are completely
free from the geometry and depend only on the ionospheric effect, on the electronic biases and on the initial integer ambiguities;
since these terms are expected to be smooth in time, at least in a short period, a cycle-slip in one or both the two carriers
can be modelled as a discontinuity in a polynomial regression. The proposed method consists in applying the Bayesian theory
to compute the marginal posterior distribution of the discontinuity epoch and to detect it as a maximum a posteriori (MAP)
in a very accurate way. Concerning the cycle-slip correction, a couple of simultaneous integer slips in the two carriers is
chosen by maximazing the conditional posterior distribution of the discontinuity amplitude given the detected epoch. Numerical
experiments on simulated and real data show that the discontinuities with an amplitude 2 or 3 times larger than the noise
standard deviation are successfully identified. This means that the Bayesian approach is able to detect and correct cycle-slips
using undifferenced GNSS observations even if the slip occurs by one cycle. A comparison with the scientific software BERNESE
5.0 confirms the good performance of the proposed method, especially when data sampled at high frequency (e.g. every 1 s or
every 5 s) are available. 相似文献
8.
Erik Rüttener Juan José Egozcue Dieter Mayer-Rosa Stephan Mueller 《Natural Hazards》1996,14(2-3):165-178
Seismic hazard analysis is based on data and models, which both are imprecise and uncertain. Especially the interpretation of historical information into earthquake parameters, e.g. earthquake size and location, yields ambiguous and imprecise data. Models based on probability distributions have been developed in order to quantify and represent these uncertainties. Nevertheless, the majority of the procedures applied in seismic hazard assessment do not take into account these uncertainties, nor do they show the variance of the results. Therefore, a procedure based on Bayesian statistics was developed to estimate return periods for different ground motion intensities (MSK scale).Bayesian techniques provide a mathematical model to estimate the distribution of random variables in presence of uncertainties. The developed method estimates the probability distribution of the number of occurrences in a Poisson process described by the parameter . The input data are the historical occurrences of intensities for a particular site, represented by a discrete probability distribution for each earthquake. The calculation of these historical occurrences requires a careful preparation of all input parameters, i.e. a modelling of their uncertainties. The obtained results show that the variance of the recurrence rate is smaller in regions with higher seismic activity than in less active regions. It can also be demonstrated that long return periods cannot be estimated with confidence, because the time period of observation is too short. This indicates that the long return periods obtained by seismic source methods only reflects the delineated seismic sources and the chosen earthquake size distribution law. 相似文献
9.
Gamma ray logging is a method routinely employed by geophysicists and environmental engineers in site geology evaluations. Modelling of gamma ray data from individual boreholes assists in the local identification of major lithological changes; modelling these data from a network of boreholes assists with lithological mapping and spatial stratigraphic correlation. In this paper we employ Bayesian spatial partition models to analyse gamma ray data spatially. In particular, a spatial partition is defined via a Voronoi tessellation and the mean intensity is assumed constant in each cell of the partition. The number of vertices generating the tessellation as well as the locations of vertices are assumed unknown, and uncertainty about these quantities is described via a hierarchical prior distribution. We describe the advantages of the spatial partition modelling approach in the context of smoothing gamma ray count data and describe an implementation that may be extended to the fitting of a more general model than a constant mean within each cell of the partition. As an illustration of the methodology we consider a data set collected from a network of eight boreholes, which is part of a geophysical study to assist in mapping the lithology of a site. Gamma ray logs are linked with geological information from cores and the spatial analysis of log data assists with predicting the lithology at unsampled locations. 相似文献
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