Multiple Point Metrics to Assess Categorical Variable Models

Geostatistical models should be checked to ensure consistency with conditioning data and statistical inputs. These are minimum acceptance criteria. Often the first and second-order statistics such as the histogram and variogram of simulated geological realizations are compared to the input parameters to check the reasonableness of the simulation implementation. Assessing the reproduction of statistics beyond second-order is often not considered because the “correct” higher order statistics are rarely known. With multiple point simulation (MPS) geostatistical methods, practitioners are now explicitly modeling higher-order statistics taken from a training image (TI). This article explores methods for extending minimum acceptance criteria to multiple point statistical comparisons between geostatistical realizations made with MPS algorithms and the associated TI. The intent is to assess how well the geostatistical models have reproduced the input statistics of the TI; akin to assessing the histogram and variogram reproduction in traditional semivariogram-based geostatistics. A number of metrics are presented to compare the input multiple point statistics of the TI with the statistics of the geostatistical realizations. These metrics are (1) first and second-order statistics, (2) trends, (3) the multiscale histogram, (4) the multiple point density function, and (5) the missing bins in the multiple point density function. A case study using MPS realizations is presented to demonstrate the proposed metrics; however, the metrics are not limited to specific MPS realizations. Comparisons could be made between any reference numerical analogue model and any simulated categorical variable model.     

Comparison of existing methods for building triangular irregular network,models of terrain from grid digital elevation models

Abstract

Triangulated irregular networks (TINs) are increasingly popular for their efficiency in data storage and their ability to accommodate irregularly spaced elevation points for many applications of geographical information systems. This paper reviews and evaluates various methods for extracting TINs from dense digital elevation models (DEMs) on a sample DEM. Both structural and statistical comparisons show that the methods perform with different rates of success in different settings. Users of DEM to TIN conversion methods should be aware of the strengths and weaknesses of the methods in addition to their own purposes before conducting the conversion.     

Comparison of statistical algorithms for detecting homogeneous river reaches along a longitudinal continuum

Seven methods designed to delineate homogeneous river segments, belonging to four families, namely — tests of homogeneity, contrast enhancing, spatially constrained classification, and hidden Markov models — are compared, firstly on their principles, then on a case study, and on theoretical templates. These templates contain patterns found in the case study but not considered in the standard assumptions of statistical methods, such as gradients and curvilinear structures. The influence of data resolution, noise and weak satisfaction of the assumptions underlying the methods is investigated. The control of the number of reaches obtained in order to achieve meaningful comparisons is discussed. No method is found that outperforms all the others on all trials. However, the methods with sequential algorithms (keeping at order n + 1 all breakpoints found at order n) fail more often than those running complete optimisation at any order. The Hubert-Kehagias method and Hidden Markov Models are the most successful at identifying subpatterns encapsulated within the templates. Ergodic Hidden Markov Models are, moreover, liable to exhibit transition areas.     

COMPARISON OF MEASUREMENT METHODS BASED ON A MODEL FOR THE ERROR STRUCTURE

Comparison of methods is a technique often used for investigation of systematic errors of measurementmethods.As concerns the design and analysis of such comparisons,much variety of opinion and practiceexists.In one approach a few specimens are measured several times by different operators in differentlaboratories(reproducibility conditions)and in another approach several specimens are measured on oneor a few occasions by one operator in the same laboratory(repeatability conditions).In this paper amodel for the error structure of measurements is formulated and it is emphasized that one has todistinguish between two types of systematic errors:the first type depends only on the level of themeasured quantity and the second type is specific for the separate specimens.On the basis of this modelthe information which can be obtained from the different designs of method comparisons is discussed.A new approach for the analysis of method comparisons with many specimens is also proposed.     

Comparative study of probable maximum precipitation and isohyetal maps for mountainous regions, Pakistan

Probable maximum precipitation (PMP) is widely used by hydrologists for appraisal of probable maximum flood (PMF) used for soil and water conservation structures, and design of dam spillways. A number of methods such as empirical, statistical and dynamic are used to estimate PMP, the most favored being statistical and hydro-meteorological. In this paper, PMP estimation in mountainous regions of Pakistan is studied using statistical as well as physically based hydro-meteorological approaches. Daily precipitation, dew point, wind speed and temperature data is processed to estimate PMP for a one-day duration. Maximum precipitation for different return periods is estimated by using statistical approaches such as Gumble and Log-Pearson type-III (LP-III) distribution. Goodness of fit (GOF) test, chi-square test, correlation coefficient and coefficient of determination were applied to Gumble and LP-III distributions. Results reveal that among statistical approaches, Gumble distribution performed the best result compared to LP-III distribution. Isohyetal maps of the study area at different return periods are produced by using the GIS tool, and PMP in mountainous regions varies from 150 to 320 mm at an average value of 230.83 mm. The ratio of PMP for one-day duration to highest observed rainfall (HOR) varied from 1.08 to 1.29 with an average value of 1.18. An appropriate frequency factor (K_m) is very important which is a function of mean for observed precipitation and PMP for 1-day duration, and K_m values varies from 2.54 to 4.68. The coefficient of variability (C_v) varies from minimum value of 28% to maximum value of 43.35%. It was concluded that the statistical approach gives higher results compared to moisture maximization (MM) approach. In the hydro-meteorological approach, moisture maximization (MM) and wind moisture maximization (WMM) techniques were applied and it was concluded that wind moisture maximization approach gives higher results of PMP as compared to moisture maximization approach as well as for Hershfield technique. Therefore, it is suggested that MM approach is the most favored in the study area for PMP estimation, which leads to acceptable results, compared to WMM and statistical approaches.     

Forthcoming events

Spatial data uncertainty models (SDUM) are necessary tools that quantify the reliability of results from geographical information system (GIS) applications. One technique used by SDUM is Monte Carlo simulation, a technique that quantifies spatial data and application uncertainty by determining the possible range of application results. A complete Monte Carlo SDUM for generalized continuous surfaces typically has three components: an error magnitude model, a spatial statistical model defining error shapes, and a heuristic that creates multiple realizations of error fields added to the generalized elevation map. This paper introduces a spatial statistical model that represents multiple statistics simultaneously and weighted against each other. This paper's case study builds a SDUM for a digital elevation model (DEM). The case study accounts for relevant shape patterns in elevation errors by reintroducing specific topological shapes, such as ridges and valleys, in appropriate localized positions. The spatial statistical model also minimizes topological artefacts, such as cells without outward drainage and inappropriate gradient distributions, which are frequent problems with random field-based SDUM. Multiple weighted spatial statistics enable two conflicting SDUM philosophies to co-exist. The two philosophies are ‘errors are only measured from higher quality data’ and ‘SDUM need to model reality’. This article uses an automatic parameter fitting random field model to initialize Monte Carlo input realizations followed by an inter-map cell-swapping heuristic to adjust the realizations to fit multiple spatial statistics. The inter-map cell-swapping heuristic allows spatial data uncertainty modelers to choose the appropriate probability model and weighted multiple spatial statistics which best represent errors caused by map generalization. This article also presents a lag-based measure to better represent gradient within a SDUM. This article covers the inter-map cell-swapping heuristic as well as both probability and spatial statistical models in detail.     

Modeling stream flow and sediment yield using the SWAT model: a case study of Ankara River basin,Turkey

The Soil and Water Assessment Tool (SWAT) was tested for prediction of stream flow and sediment yield in the Ankara basin, Turkey. The overall objective of this study was to evaluate the performance and applicability of the SWAT and generate a soil erosion map. Thirteen years of daily/monthly flow and monthly sediment data were used for calibration and validation. Model performance was evaluated using statistical measures to assess the applicability of the model in simulating stream flow and sediment yield during calibration (1989–1996) and validation (1982–1984) periods. Nash Sutcliffe efficiency (NSE), relative error (RE), and R² (coefficient of determination) for daily flow were computed as 0.61, ?0.55, and 0.78, respectively; and as 0.79, ?0.58, and 0.89 for monthly flow during the calibration. Statistical comparisons of sediment yield produced values for NSE, RE, and R² of 0.81, ?1.55, and 0.93, respectively, during the calibration. The resulting map suggests that significant portions of urbanized and highly cultivated areas in the vicinity of stream channels are particularly vulnerable to soil erosion. SWAT satisfactorily simulated hydrology and sediment yield and can be used as a tool in decision-making for water resources planning in a basin with similar characteristics.     

Evaluation and comparison of landslide susceptibility mapping methods: a case study for the Ulus district,Bartın,northern Turkey

The purpose of this study was to investigate the capabilities of different landslide susceptibility methods by comparing their results statistically and spatially to select the best method that portrays the susceptibility zones for the Ulus district of the Bart?n province (northern Turkey). Susceptibility maps based on spatial regression (SR), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression (LR) method, and artificial neural network method (ANN) were generated, and the effect of each geomorphological parameter was determined. The landslide inventory map digitized from previous studies was used as a base map for landslide occurrence. All of the analyses were implemented with respect to landslides classified as rotational, active, and deeper than 5 m. Three different sets of data were used to produce nine explanatory variables (layers). The study area was divided into grids of 90 m × 90 m, and the ‘seed cell’ technique was applied to obtain statistically balanced population distribution over landslide inventory area. The constructed dataset was divided into two datasets as training and test. The initial assessment consisted of multicollinearity of explanatory variables. Empirical information entropy analysis was implemented to quantify the spatial distribution of the outcomes of these methods. Results of the analyses were validated by using success rate curve (SRC) and prediction rate curve (PRC) methods. Additionally, statistical and spatial comparisons of the results were performed to determine the most suitable susceptibility zonation method in this large-scale study area. In accordance with all these comparisons, it is concluded that ANN was the best method to represent landslide susceptibility throughout the study area with an acceptable processing time.     

SPIDER—an interactive statistical tool for the analysis of spatially distributed data

Interactive statistical graphics are reviewed in the contexts of spatial data and geographical information systems (GIS). GIS provide the user with an active geographical view of the data—a map that can be used as an entry point to the data base. Prototype software—SPIDER—illustrates the possibilities of using statistical graphics as further views of the data, which can be made active and thus provide alternative means of querying the data. These views can be cross-referenced by 'linking'. It is argued that such a system can provide a very rich environment for pursuing exploratory statistical analysis of spatial data.     

Source ambiguity from an estimation of the scaling exponent of potential field power spectra

An analysis of the field scaling power spectrum yields useful information about the source distribution, but it is uncertain whether deterministic, random, fractal or mixed approaches have to be used for the interpretation. To this end, the scaling properties of potential field spectra are analysed for a number of different source models of geological interest. Besides the models of Naidu (purely random sources) and Spector and Grant (gross block statistical ensembles) we consider other types of density and magnetization distributions with spectral exponents in the fractal range, such as a single homogeneous body with a random white source distribution. Spectral slopes in the fractal range are obtained.
We also study the effects of important natural sources, such as salt domes and sedimentary basins, representing them with simple Gaussians or combinations of Gaussian signals. The same spectral slopes as for gravity signals generated by 3-D fractal source distributions are found for them. Hence the power law decay of the field is not a characteristic only of fractal source models.
If a 3-D fractal source distribution is assumed a priori , a way of verifying the goodness of the model is to examine the whitened field at source level. The probability that the whitened field derives from a random white population is estimated for synthetic and real anomalies by applying the usual statistical tests.     

风化花岗岩崩岗灾害的成因机理

测定了广东珠海大镜山剖面(DJS)、增城剖面(ZC-1、ZC-2)、阳江飞鹅岭和圆周岭剖面(FEI、YZL)的物性指标,通过建立崩岗数学模型,设定不同的坡面参数条件,计算了坡面和稳定临界深度,当坡度＜43°时,坡体的稳定临界深度＞2m。根据雨水在花岗岩风化剖面的渗透特点,计算了一定强度的降雨在不同时间内的湿润前锋,由临界深度与湿润前锋的对比,说明了降雨与崩岗的关系。此外,还结合文献中日本和香港地区崩岗灾害的统计资料结果,探讨了不同时间的降雨对坡体稳定性的影响。     

Stochastic model-based methods for handling uncertainty in areal interpolation

Handling of uncertainty in the estimation of values from source areas to target areas poses a challenge in areal interpolation research. Stochastic model-based methods offer a basis for incorporating such uncertainty, but to date they have not been widely adopted by the GIS community. In this article, we propose one use of such methods based in the problem of interpolating count data from a source set of zones (parishes) to a more widely used target zone geography (postcode sectors). The model developed also uses ancillary statistical count data for a third set of areas nested within both source and target zones. The interpolation procedure was implemented within a Bayesian statistical framework using Markov chain Monte Carlo methods, enabling us to take account of all sources of uncertainty included in the model. Distributions of estimated values at the target zone level are presented using both summary statistics and as individual realisations selected to illustrate the degree of uncertainty in the interpolation results. We aim to describe the use of such stochastic approaches in an accessible way and to highlight the need for quantifying estimation uncertainty arising in areal interpolation, especially given the implications arising when interpolated values are used in subsequent analyses of relationships.     

Categorization of Mineral Resources Based on Different Geostatistical Simulation Algorithms: A Case Study from an Iron Ore Deposit

Mineral resource classification plays an important role in the downstream activities of a mining project. Spatial modeling of the grade variability in a deposit directly impacts the evaluation of recovery functions, such as the tonnage, metal quantity and mean grade above cutoffs. The use of geostatistical simulations for this purpose is becoming popular among practitioners because they produce statistical parameters of the sample dataset in cases of global distribution (e.g., histograms) and local distribution (e.g., variograms). Conditional simulations can also be assessed to quantify the uncertainty within the blocks. In this sense, mineral resource classification based on obtained realizations leads to the likely computation of reliable recovery functions, showing the worst and best scenarios. However, applying the proper geostatistical (co)-simulation algorithms is critical in the case of modeling variables with strong cross-correlation structures. In this context, enhanced approaches such as projection pursuit multivariate transforms (PPMTs) are highly desirable. In this paper, the mineral resources in an iron ore deposit are computed and categorized employing the PPMT method, and then, the outputs are compared with conventional (co)-simulation methods for the reproduction of statistical parameters and for the calculation of tonnage at different levels of cutoff grades. The results show that the PPMT outperforms conventional (co)-simulation approaches not only in terms of local and global cross-correlation reproductions between two underlying grades (Fe and Al₂O₃) in this iron deposit but also in terms of mineral resource categories according to the Joint Ore Reserves Committee standard.

     

AN ASSESSMENT OF CLAST MACROFABRICS IN GLACIGENIC SEDIMENTS BASED ON A/B PLANE DATA

Previous studies of clast macrofabrics in glacigenic deposits have concentrated on A‐axis orientations and dips, and a variety of control samples are available based upon such measurements. Like clast A‐axes, A/B planes will also tend to rotate to parallelism with the direction of shear and therefore should also provide meaningful data on the direction and cumulative impact of shear by the depositing/deforming medium (i.e. glacier ice). The measurement of A/B plane dip and orientation avoids the potential problem of the transverse orientations observed for clast A‐axes and provides poles‐to‐plane data, thereby strengthening the modality of samples and providing clear visual impressions of stress directions. Such data also enable more significant inter‐sample comparisons of fabric strength and clast dip angles, which are significant when assessing the impact of shearing in sediment genesis. We present data on clast A/B plane dip directions and angles from subglacial tills, glacitectonite continuums, subglacially lodged clasts and glacimarine/glacilacustrine deposits using traditional methods of statistical and graphical macrofabric analysis. These sample sets will serve as control data for future macrofabric analyses that utilize A/B planes. The separation of the unequivocally lodged clast component from subglacial till samples allows us to demonstrate the influence of deformation and ploughing in the relative weakening of till fabrics as proposed by some researchers. High angles of A/B plane dip in glacigenic subaqueous deposits appear to be well developed in the glacilacustrine setting investigated here, confirming previous studies based on A‐axis dips, but less convincing in the glacimarine sediments of the Canadian Arctic, thereby widening the range of fabric strengths in subaqueous glacigenic deposits. Significant overlaps of A/B plane fabric shape envelopes reflect the strain history of subglacial and subaqueous depositional environments, which is unsurprising given the hybrid nature of glacigenic deposits, but the statistical isolation of the lodgement component from subglacial traction tills strongly suggests that the continuum of sample plots on modality/isotropy graphs reflects the range of strain histories in glacitectonites and subglacial traction till.     

Declining towns in Russia, 1989-1993

This "article based on data for the last census of the former USSR and population estimates for 1993 for urban places of over 15,000 population in the Russian Federation surveys the regional distribution, economic functions, and size characteristics of urban settlements in Russia with declining population over the period 1989-93. Interesting comparisons are drawn with patterns prevailing during previous periods, revealing recent increases in the number of such towns in major manufacturing regions and the North and an increase in the number of large cities. Towns experiencing the very greatest percentage declines (-10.0 percent or more) also are investigated."     

中国地理学期刊编辑出版研究的综述

通过全面收集和系统整理中国地理学类期刊编辑发表的编辑出版研究成果,总结分析中国地理期刊在期刊发展方面的特点,包括地理期刊的总体发展、主要期刊的发展历程、英文期刊的发展、中外期刊发展对比等。概括分析了中国主要地理期刊载文、人文地理学科刊文、主要期刊引文分析等方面的统计结果。最后,对中国地理期刊编辑在期刊与学科发展关系、期刊选题和办刊思路、提高期刊编辑质量、防止稿件重复发表、电脑与网络使用方法等5方面的研究做出了全面总结。     

Female Farmers in Canada, 1971–1986*

The discussion of agricultural restructuring has often failed to include farm women, particularly those who own and operate their own enterprises. Accordingly, this research presents an overview of Canadian female farm operators, who are a growing component of the farm operator population. Using previously untabulated data from the 1971, 1981, and 1986 censuses of agriculture and population, the study draws comparisons to male farmers in Canada and female farmers in the United States. The census data show that the socioeconomic and farming profile of Canadian female farmers differs from that of their male colleagues, and that the differences in certain key characteristics (such as farm size, sales, and commodity type) are becoming more noticeable over time. This raises questions about whether female operators are in danger of becoming marginalized from mainstream production, and whether their needs as a minority group among agricultural producers are being recognized.     

基于GIS的陇东南非物质文化遗产旅游资源潜力评价

基于甘肃省第一至第四批国家级和省级非遗名录(包括扩展名录在内)和2018年《甘肃统计年鉴》相关数据,在AHP法和专家打分法的支持下,将陇东南31个县级地区非遗旅游资源潜力评价划分为资源质量、旅游社会经济环境、保护与传承3个评价单元,并用ArcGIS10.2叠加分析对综合旅游潜力评价分析。研究表明:秦州区、西峰区等7个地区非遗旅游开发潜力最大;甘谷县、清水县、镇原县等12个县次之;礼县、静宁县、华池县等12个地区最低。