Statistical errors in the determination of wind velocities by the spaced antenna technique

This paper is concerned with the statistical errors which are present when wind velocities in the atmosphere are determined by the radar method known as the spaced antenna technique. It is assumed that the (complex) data is processed by the method known as full correlation analysis (FCA). A theory is first developed to give the error in the determination of the position of the maximum of a cross-correlation function and the value of lag such that the auto-correlation falls to a value equal to that of the crosscorrelation at zero lag. These are the basic quantities needed for the application of FCA. These error estimates are tested with a variety of numerically simulated data and shown to be realistic. The results are applied to real data and, using the standard techniques for the propagation of errors, they lead to estimates of the errors in the derived wind velocities. In order to test these estimates, an experiment was carried out in which two independent wind determinations were made simultaneously. The differences were used to obtain experimental estimates of the errors. It was found that the theory overestimates the error in the wind velocities by about 50%. Possible reasons for this are discussed.     

HAM HILL STONE: A MEDIEVAL DISTRIBUTION PATTERN FROM SOMERSET

This paper explores the potential of simple quantitative techniques for elucidating a medieval distribution pattern. The distribution is that of a distinctive building-stone found in parish churches in Somerset and throughout the south-west. Dating is achieved by recognition of different architectural styles and the stone's occurrence is plotted within 25 km of the source quarry at Ham Hill near Yeovil. The study has dual implications in that simple statistical techniques enable new conclusions to be made concerning the mechanisms of the stone's distribution, but some of these conclusions can also be checked against the documentary evidence. Therefore both distribution and techniques come under scrutiny. In this way a complementary archaeological and historical approach united by quantitative techniques and documents is applied to a medieval distribution problem but has implications for the prehistorian also.     

Quantifying Interpolation Errors in Urban Airborne Laser Scanning Models

Airborne laser scanning (ALS) is becoming an increasingly popular data capture technique for a variety of applications in urban surface modeling. Raw ALS data are captured and supplied as a 3D point cloud. Many applications require that these data are interpolated onto a regular grid in order that they may be processed. In this article, we identify and analyze the magnitudes and spatial patterning of residuals from ALS models of urban surfaces, at a range of different scales. Previous research has demonstrated the effects of interpolation method and scale upon the nature of error in digital surface models (DSMs), but the size and spatial patterning of such errors have not hitherto been investigated for urban surfaces. The contribution of this analysis is thus to investigate the ways in which different methods may introduce error, and to understand the uncertainty that characterizes urban surface models that are devised for a wide range of applications. The importance of the research is shown using examples of how the different methods may introduce different amounts of error and how the uncertainty information may benefit users of ALS height models. Our analysis uses a range of validation techniques, including split-sample, cross-validation, and jackknifing, to estimate the error created in DSMs of urban areas.     

A SPATIAL HEDONIC APPROACH ON LAND USE CHANGE ANTICIPATIONS*

ABSTRACT This paper estimates land use conversion anticipation when zoning is the primary tool of land use regulation. Extending the Capozza and Helsey model (1989) to the case of uncertainty in future land use zoning, a spatialized hedonic model is proposed to estimate such anticipation phenomena at a fine level (cadastral unit). Estimations use Mixed Geographically Weighted Regression (MGWR) techniques with a two‐stage model that links agricultural and developable land markets. This allows for mapping varying spatial parameters that measure anticipation effects within the theoretical framework. Results confirm the influence of anticipation on agricultural land prices in the Provence region. Moreover, the level of data spatialization allows us to take into account intra‐municipalities' heterogeneity of land use conversion anticipation.     

A Comparison of Spatially Varying Regression Coefficient Estimates Using Geographically Weighted and Spatial‐Filter‐Based Techniques

Geographically weighted regression (GWR) is a technique that explores spatial nonstationarity in data‐generating processes by allowing regression coefficients to vary spatially. It is a widely applied technique across domains because it is intuitive and conforms to the well‐understood framework of regression. An alternative method to GWR that has been suggested is spatial filtering, which it has been argued provides a superior alternative to GWR by producing spatially varying regression coefficients that are not correlated with each other and which display less spatial autocorrelation. It is, therefore, worthwhile to examine these claims by comparing the output from both methods. We do this by using simulated data that represent two sets of spatially varying processes and examining how well both techniques replicate the known local parameter values. The article finds no support that spatial filtering produces local parameter estimates with superior properties. The results indicate that the original spatial filtering specification is prone to overfitting and is generally inferior to GWR, while an alternative specification that minimizes the mean square error (MSE) of coefficient estimates produces results that are similar to GWR. However, since we generally do not know the true coefficients, the MSE minimizing specification is impractical for applied research.     

Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity

Spatial nonstationarity is a condition in which a simple “global” model cannot explain the relationships between some sets of variables. The nature of the model must alter over space to reflect the structure within the data. In this paper, a technique is developed, termed geographically weighted regression, which attempts to capture this variation by calibrating a multiple regression model which allows different relationships to exist at different points in space. This technique is loosely based on kernel regression. The method itself is introduced and related issues such as the choice of a spatial weighting function are discussed. Following this, a series of related statistical tests are considered which can be described generally as tests for spatial nonstationarity. Using Monte Carlo methods, techniques are proposed for investigating the null hypothesis that the data may be described by a global model rather than a non-stationary one and also for testing whether individual regression coefficients are stable over geographic space. These techniques are demonstrated on a data set from the 1991 U.K. census relating car ownership rates to social class and male unemployment. The paper concludes by discussing ways in which the technique can be extended.     

Illicit Drug Production and Supply-side Drugs Policy in Asia and South America

This paper examines the feasibility of current policies of supply limitation as an instrument for the control of dangerous drugs (principally South American cocaine and Asian heroin). The structure of production and distribution is examined, and revenue estimates are made. A range of supply-side policy options are evaluated by means of a simple game-theory approach. In all cases, it is concluded that supply-side policies are likely to prove ineffectual as a means of drug control.     

Modelling of hydrology and potential population levels at Bronze Age Jawa,Northern Jordan: a Monte Carlo approach to cope with uncertainty

An annual water balance model for Wadi Rajil, in Northern Jordan, is used to simulate the ancient water supply system for the Early Bronze Age site of Jawa. The model includes: water delivery from the catchment; local pond storage; and water demand for people, animals and irrigation. A Monte Carlo approach is used to incorporate the uncertainty associated with a range of factors including rainfall, evaporation, water losses and use. The stochastic simulation provides estimates of potential population levels sustainable by the water supply system. Historical precipitation estimates from a Global Circulation Model, with uncertainty bounds, are used to reconstruct the climate at Jawa in the Early Bronze Age (EBA). Model results indicate that the population levels in the predicted wetter conditions during parts of the EBA could have risen to ∼6000 and may have been higher in wet years. However, palaeoclimatic proxies also suggest prolonged droughts in the EBA; and during these periods the water management system was unable to provide adequate supply for a population of 6000. The utility of Monte Carlo based hydrological modelling as a tool within archaeological science is discussed.     

Regional Seismic Risk Assessment of Bridge Network in Charleston,South Carolina

This article presents the results of a seismic risk assessment of the bridge network in Charleston, South Carolina and the surrounding counties to support emergency planning efforts, and for prioritization of bridge retrofit. This study includes an inventory analysis of the approximately 375 bridges in the Charleston area, and convolution of the seismic hazard with fragility curves analytically derived for classes of bridges common to this part of the country. State-of-the-art bridge fragility curves and replacement cost estimates based on region-specific data are used to obtain economic loss estimates. The distribution of potential bridge damage and economic losses are evaluated for several scenario events in order to aid in the identification of emergency routes and assess areas for investment in retrofit. This article also evaluates the effect of uncertainty on the resulting predicted economic losses. The findings reveal that while the risk assessment is very sensitive to both the assumed fragility curves and damage ratios, the estimate of total expected economic losses is more sensitive to the vast differences in damage ratio models considered.     

Spatial Analysis in Physical Geography and the Challenge of Deterministic Uncertainty

The application of complex and nonlinear dynamical systems (NDS) theory in physical geography and geosciences has proceeded through several stages, and has recently entered a phase where field-testable hypotheses and historical or mechanistic explanations are being generated. However, there are some fundamental challenges. It seems clear that chaos and dynamical self-organization are present, and may be common in earth surface systems, and that these phenomena have spatial manifestations in the landscape. However, NDS theory and methods have been formulated primarily in the temporal domain and are typically ill-suited to real-world spatial data. Spatial analytical methods are not generally capable of distinguishing deterministic complexity and uncertainty from noise. Thus, the detection of the signals of complex deterministic dynamics in real landscapes and spatial data is a major challenge. Entropy-based methods of spatial analysis can be directly linked to nonlinear dynamics, and are at present the best available method to approach this problem. However, there is evidence in the spatial analysis literature suggesting that development of techniques to detect deterministic uncertainty is possible. Pending such a break-through, three general approaches are described, based on spatial analysis of chronosequences, the characteriziation of changes in spatial structure over time, and the spatial-domain testing of specific hypotheses relevant to deterministic uncertainty. Current trends generally suggest a shift in mathematical modeling and spatial analysis in physical geography away from traditional determinism toward approaches that incorporate locational, historical, and scale contingency.     

Investigating Global and Local Categorical Map Configuration Comparisons Based on Coincidence Matrices

The simple and intuitive nature of the coincidence matrix has not only made it the current "gold standard" for accuracy assessment (based on a sample of map pixels), but also a common tool for describing difference between two categorical maps (when all pixels are enumerated). It is this latter case of map comparison that this article explores. Coincidence matrices, although providing significant information regarding thematic agreement between two categorical maps (composition), can lack significantly in terms of conveying information about differences or similarities in the spatial arrangement (configuration) of those map categories in geographic space. This article introduces means for distilling the available configuration information from a coincidence matrix while demonstrating some simple categorical map comparisons. Specifically, while the coincidence matrix summarizes per-pixel compositional persistence or change, the introduced technique further quantifies the global and local configurational uncertainty between compared maps. I demonstrate how this quantification of configurational uncertainty can be used to gauge which thematic mismatch types are most significant and how to measure/present local configurational uncertainty in a spatial context. Implementation is through a straightforward mathematical algorithm in R that is illustrated by several examples.     

Radiocarbon dates as data: quantitative strategies for estimating colonization front speeds and event densities

Archaeological analysis of large-scale prehistoric population history requires us to estimate rates of spatial spread during dispersals, and rates and magnitudes of temporal contraction during crashes. Using OxCal’s MCMC sampling routine, I introduce and demonstrate a simple and easily implemented method of estimating front speeds that takes due account of the uncertainty in the archaeological data (in both dates and distances), and argue that this method is more appropriate than those most often used in front speed estimation at present. I also propose a simple and easily implemented method of estimating event densities as a demographic proxy, as an alternative to summed calibrated probability distributions. I argue that this alternative is a significantly better technique, and show that its use also enables us to identify individual archaeological dates that are exerting particularly strong influence on the results, so that we can efficiently allocate our attention when assessing the possible effects of exogenous sampling uncertainty. To illustrate these methods I re-analyse two published datasets relating to the early Paleoindian colonization of North America. My results with the new technique indicate that even with a very noisy dataset, there was clear evidence in the framework of the INTCAL04 calibration curve for a drastic reduction in archaeological event densities following the Younger Dryas onset, followed by a prolonged period of reduced human activity, and a possible renewed phase of rapid growth after the Younger Dryas termination and onset of the Holocene. However, the revised estimate of the Younger Dryas marine reservoir offset in the INTCAL09 calibration curve for ∼12,550–12,900 cal BP changes the picture significantly, by flattening the peak in Clovis-age events and pushing it forward in time into the early Younger Dryas itself.     

TESTING THE SPATIAL SCALE AND THE DYNAMIC STRUCTURE IN REGIONAL MODELS (A CONTRIBUTION TO SPATIAL ECONOMETRIC SPECIFICATION ANALYSIS)*

This article addresses the problem of specification uncertainty in modeling spatial economic theories in stochastic form. It is ascertained that the traditional approach to spatial econometric modeling does not adequately deal with the type and extent of specification uncertainty commonly encountered in spatial economic analyses. Two alternative spatial econometric modeling procedures proposed in the literature are reviewed and shown to be suitable for analyzing systematically two sources of specification uncertainty, viz., the level of aggregation and the spatio-temporal dynamic structure in multiregional econometric models. The usefulness of one of these specification procedures is illustrated by the construction of a simple multiregional model for The Netherlands.     

COUNTERFACTUAL SPATIAL DISTRIBUTIONS

Recent contributions provide researchers with a useful toolbox to estimate counterfactual distributions of scalar random variables. These techniques have been widely applied in the literature. Typically, the dependent variable of interest has been a scalar and little consideration has been given to spatial factors. In this paper we propose a simple method to construct the counterfactual distribution of the location of a variable across space. We apply the spatial counterfactual technique to assess how much changes in individual characteristics of Hispanics in the Washington DC area account for changes in the distribution of their residential location choices.     

A review of trepanations in Anatolia with new cases

In this study, trepanations in ancient Anatolia were discussed from a historical perspective. Trepanations were studied in respect to temporal and spatial distribution, sex and age distribution, techniques and reasons, completeness, healing and number of holes. Forty individuals from 23 different Anatolian settlements are identified to have undergone trepanations. Cranial trepanations in Anatolia show a distribution over a period of 10 000 years ranging from the Aceramic Neolithic period to the Late Ottoman period and spread to whole Anatolia. The greater majority of the individuals had single trepanation orifices while only four individuals were identified with multiple holes. It is observed that the surgical procedure was predominantly carried out on males in Anatolia. Main techniques of trepanations used in Anatolia are drilling and cutting. Early cases of trepanation were made by drilling; however, this technique has been used for cranial surgery until the Ottoman period. Scraping and rectangular sawing techniques first applied in the Early Bronze Age. The boring‐and‐cutting technique was only applied in the Iron Age. More than half of the trepanations practiced due to cranial trauma. Training and treatment besides of cranial trauma are also considered as likely causes of trepanations in Anatolia. It is concluded that trepanation techniques are similar to South America and the Mediterranean region rather than Europe. Copyright © 2010 John Wiley & Sons, Ltd.     

Developing Geostatistical Space–Time Models to Predict Outpatient Treatment Burdens from Incomplete National Data

Basic health system data such as the number of patients utilizing different health facilities and the types of illness for which they are being treated are critical for managing service provision. These data requirements are generally addressed with some form of national Health Management Information System (HMIS), which coordinates the routine collection and compilation of data from national health facilities. HMIS in most developing countries are characterized by widespread underreporting. Here we present a method to adjust incomplete data to allow prediction of national outpatient treatment burdens. We demonstrate this method with the example of outpatient treatments for malaria within the Kenyan HMIS. Three alternative modeling frameworks were developed and tested in which space–time geostatistical prediction algorithms were used to predict the monthly tally of treatments for presumed malaria cases (MC) at facilities where such records were missing. Models were compared by a cross-validation exercise and the model found to most accurately predict MC incorporated available data on the total number of patients visiting each facility each month. A space–time stochastic simulation framework to accompany this model was developed and tested in order to provide estimates of both local and regional prediction uncertainty. The level of accuracy provided by the predictive model, and the accompanying estimates of uncertainty around the predictions, demonstrate how this tool can mitigate the uncertainties caused by missing data, substantially enhancing the utility of existing HMIS data to health-service decision makers.     

An analysis of population and social change in London wards in the 1980s

"This paper discusses the estimation and projection of small area populations in London, [England] and considers trends in intercensal social and demographic indices which can be calculated using these estimates. Information available annually on vital statistics and electorates is combined with detailed data from the Census Small Area Statistics to derive demographic component based population estimates for London's electoral wards over five year periods. The availability of age disaggregated population estimates permits derivation of small area social indicators for intercensal years, for example, of unemployment and mortality. Trends in spatial inequality of such indicators during the 1980s are analysed and point to continuing wide differentials. A typology of population and social indicators gives an indication of the small area distribution of the recent population turnaround in inner London, and of its association with other social processes such as gentrification and ethnic concentration."     

Spatial Variability of Controls on Downstream Patterns of Sediment Storage: a Case Study in the Lane Cove Catchment,New South Wales,Australia

This study uses GIS techniques to examine the spatial distribution of stream power along major streamlines in the Lane Cove catchment in northern Sydney, Australia. Channel gradient estimates derived from a 5 m resolution digital elevation model (DEM) are combined with streamflow data to estimate stream power along river courses. Stream power and its constituent components are then related to a detailed field‐based assessment of sediment storage along the trunk stream and primary tributaries. At the catchment scale, sediment storage per unit length decreases as channel gradient and gross stream power increase. However, local controls such as variability in valley width and occurrence of confluence zones exert a greater influence upon sediment storage, disrupting systematic catchment‐wide relationships. The total volume of storage along each streamline has a strong linear relationship to the area of the subcatchment, but the distribution of sediment along streamlines varies between subcatchments. The GIS framework employed in this project allows generation of continuous, empirical data, thereby providing catchment‐specific predictive capacity that can accompany theoretical approaches to stream power modelling.     

Solving mixture problems in archaeology: Analysis of ceramic materials for dating and demographic reconstruction

Mixed collections are ubiquitous in archaeology. Multiple linear regression provides one means for partitioning mixed archaeological collections into their constituent components. The technique estimates the best combination of specified sets of sources in the composition of a mixed whole. As applied to ceramic collections, this technique has proven successful in solving complex dating problems. Used in conjunction with sherd collections obtained through probabilistic sampling, the technique can be extended to demographic reconstruction. Under certain conditions, the techniques described in this paper provide important ancillary data for detecting seasonality, duration, and nature of occupations.     

山东新泰出土同心圆剑首连接技术研究

山东新泰周家庄出土了东周时期大量带有吴国特征的兵器,其中尤以青铜剑最具特色。为探讨东周同心圆剑首与剑茎的连接方式和连接结构,采用X射线探伤机、CT检测了3把同心圆首剑。检测结果显示3把同心圆首剑采用了2种铸造技术,即浑铸技术、铸接技术。其中2把铸接的同心圆首剑分别用2段式和3段式铸接成形。文章首次用CT清晰地展示了2把铸接的同心圆首上设置的榫头形状及分布状况。讨论了古代同心圆剑首连接技术的多样性、灵活性,说明了当时青铜连接技术已经非常娴熟、高超。