Rock Joint Surfaces Measurement and Analysis of Aperture Distribution under Different Normal and Shear Loading using GIS

Summary The geometry of the rock joint is a governing factor for joint mechanical and hydraulic behaviour. A new method for evaluating the aperture distribution, based on measurement of joint surfaces and three dimensional characteristics of each surface, is developed. This method allows one to determine and visualize the aperture distribution under different normal stresses and shear displacements, which is difficult to observe experimentally. A new laser scanner system is designed and developed for joint surface measurements. Special attention is paid to both surfaces’ data gained by measurements and processing, such as x-y coordinate table modification, data referencing, and matching between upper and lower surfaces. The surfaces of an artificial joint in granite are measured, processed, analyzed and three dimensional approaches are carried out for surface characterization. Parameters such as “asperity’s heights”, “slope angles”, and “aspects” distribution at micro scale, local concentration of elements and their spatial localization at local scale are determined by Geographic Information System (GIS). These parameters are used for joint surfaces matching and its real behavior quantitative analysis. The upper surface is brought down to make contact with the lower surface and the distance between the two surfaces is evaluated from the joint mean experimental aperture, which is obtained from normal and shear tests. Changes of aperture distribution at different normal stresses and various shear displacements are visualized and interpreted. Increasing normal load causes negative changes in aperture frequency distribution which indicates high joint matching. However, increasing shear displacement causes a rapid increase in the aperture and positive changes in the aperture frequency distribution, which could be due to un-matching, surface anisotropy and spatial localization of contact points with proceeding shear. Author’s address: Mostafa Sharifzadeh, Department of Mining, Metallurgy and Petroleum Engineering, Amirkabir University of Technology, Hafez 424, Tehran 15875-4413, Iran     

Influence of the ore block model estimation on the determination of the mining cutoff grade policy for sustainable mine production

Strategic mine planning includes different cut-off grade policy depending on economic parameters of mining projects and grade–tonnage distribution of the deposit. Minimizing incorrect classification of ore and waste during grade–tonnage distribution is of critical importance for a mining operation. This article reviews the influence of the ore grade–tonnage distribution over the cut-off grade policy in a given mining operation. In this study, firstly, the interpolation parameters used to characterize the grade–tonnage distribution in the orebody are given. The resulting distribution of ore and waste is used to analyze uncertainty, risk impact, and to justify mine-planning decisions, according to the interpolation technique used and the number of geological settings and sampling scenarios being considered. Then, the working scheme of the cut-off grade policy and economic parameters are compared according to the resulting estimation from the inverse distance and the nearest neighbor methods.     

Fish Predation on Juvenile Penaeid Shrimp: Examining Relative Predator Impact and Size-Selective Predation

Predation is likely the primary source of mortality for juvenile penaeid shrimp and, therefore, a key factor driving their population dynamics. We sampled juvenile penaeids and their potential predators in a salt marsh from July to August 2012 to examine the impact of these predators and possible size-selective predation on the shrimp population. We quantified predator impact using the frequency of occurrence (FO) index and a relative predation index (RPI) that accounts for predator abundance and the number of shrimp consumed per individual predator. Size selectivity was assessed by comparing the size distribution of shrimp in the study area to the size distribution of shrimp removed from predator stomachs. Two penaeid species, white shrimp Litopenaeus setiferus and brown shrimp Farfantepenaeus aztecus, were collected, and most (86%) were juvenile white shrimp ≤?12 mm carapace length. Spotted seatrout Cynoscion nebulosus, which consumed relatively large shrimp, was the most important predator based on the FO index. Bay whiff Citharichthys spilopterus, which ate the smallest shrimp, was the most important predator based on the RPI. The size distribution of shrimp removed from predator stomachs differed from those collected in the study area; the smallest shrimp were disproportionally more abundant in predator stomachs. Using the RPI, we identified some potentially important predators (e.g., bay whiff) that may impact shrimp populations by consuming the smallest shrimp in estuarine nurseries. Our approach could be useful for examining predator impacts on other populations of juvenile penaeids and more generally for any prey consumed by fish predators.     

Environmental study for pollution in the area of Megalopolis power plant (Peloponnesos,Greece)

The main purpose of the present study is to investigate the suitability of magnetic properties in correlation to geochemical measurements as a pollution-monitoring tool and study the metal transmission factors in an area around a major local source, namely a lignite-burning power plant. Surface soil samples were collected in the wide area of the power plant of Megalopolis (Peloponnesos, Greece). The magnetic susceptibility and other magnetic properties of the surface soils were originally measured and mapped. Loci of high values of magnetic susceptibility within the study area gave rise to further analyze the soil samples for metal concentrations. GIS techniques were used for mapping all the chemical constituent concentrations and the magnetic measurements on the various topographic and geological features of the area. Maps were created through interpolation algorithms indicating the spatial distribution of the above measurements. Spatial tools and statistical analysis through the calculation of Pearson’s coefficients proved the correlation between magnetic properties, metal concentrations and the terrain attributes (especially the geological structure and the wind currents) of the region.     

Breadth and depth in research on health disparities: commentary on the work of Nancy Krieger

Geocoding and spatial analysis of data describing populations and health events are important methods in health social science now carried out using GIS technology. This commentary considers Nancy Krieger’s work on health disparities in light of the various ways individuals and organizations use geocoded population and health data: analyzing spatial patterns of health and disease including health disparities, aggregating data spatially, assessing health status of individuals based on characteristics of aggregates, modeling neighborhood contextual factors affecting health, designing observation and intervention studies, and delivering health interventions and services. The extent to which her work addresses each of these purposes is considered. The strengths and limitations of the research including choice of spatial analytic units and techniques as reported in the published work are discussed. Krieger’s work, with her colleagues, has used standard methods of spatial analysis to raise the profile of GIS and spatial analysis in the public health community.     

Markov Chain Random Fields for Estimation of?Categorical Variables

Multi-dimensional Markov chain conditional simulation (or interpolation) models have potential for predicting and simulating categorical variables more accurately from sample data because they can incorporate interclass relationships. This paper introduces a Markov chain random field (MCRF) theory for building one to multi-dimensional Markov chain models for conditional simulation (or interpolation). A MCRF is defined as a single spatial Markov chain that moves (or jumps) in a space, with its conditional probability distribution at each location entirely depending on its nearest known neighbors in different directions. A general solution for conditional probability distribution of a random variable in a MCRF is derived explicitly based on the Bayes’ theorem and conditional independence assumption. One to multi-dimensional Markov chain models for prediction and conditional simulation of categorical variables can be drawn from the general solution and MCRF-based multi-dimensional Markov chain models are nonlinear.     

Relationship between subcellular cadmium distribution in prey and cadmium trophic transfer to a predator

We tested the hypothesis that exposure-related alterations in the subcellular Cd distribution in prey relate to changes in Cd absorption by a predator. Oligochaete worms,Limnodrilus hoffmeisteri were exposed for 1 wk or 6 wk to 0.5 μg Cd 1^?1, 47 μg Cd 1^?1, or 140 μg Cd 1^?1 (including¹⁰⁹Cd as a tracer) and relationships between oligochaete subcellular Cd distribution and Cd absorption by a predator, the grass shrimp (Palaemonetes pugio), were determined. Concentration and duration of Cd exposure had direct effects on oligochaete subcellular Cd distribution. Changes in oligochaete subcellular Cd distribution were characterized by increases in both the amount and proportion of Cd bound to the cytosolic fraction. The induction of Cd-binding proteins (e.g., metallothioneins) were suspected to be responsible for these changes. We found 1∶1 relationships between the amount and percentage of Cd in oligochaete cytosol and the amount and percentage of Cd adsorbed by shrimp. These results demonstrate that only metal bound to the soluble fraction of prey is available to higher trophic levels, and that factors influencing subcellular metal distribution in prey will directly alter metal trophic transfer to predators.     

Grid interpolation algorithm based on nearest neighbor fast search

The nearest neighbor search algorithm is one of the major factors that influence the efficiency of grid interpolation. This paper introduces a KD-tree that is a two-dimensional index structure for use in grid interpolation. It also proposes an improved J-nearest neighbor search strategy based on ??priority queue?? and ??neighbor lag?? concepts. In the strategy, two types of J-nearest neighbor search algorithms can be used; these algorithms correspond to the consideration of a fixed number of points and a fixed radius. By using the KD-tree and proposed strategy, interpolation can be performed with methods such as Inverse Distance Weighting and Kriging. Experimental results show that the proposed algorithms has high operating efficiency, especially when the data amount is enormous, and high practical value for increasing the efficiency of grid interpolation.     

陕西省志丹县黄土滑坡空间分布规律与形态特征研究

滑坡空间分布与形态特征能够反映滑坡发育程度,为区域内滑坡灾害防治提供依据.本研究以志丹县黄土滑坡为研究对象,基于GIS空间分析选取最邻近指数与核密度估计分析志丹县滑坡空间分布规律,通过统计分析的方法研究滑坡形态特征.结果表明,志丹县滑坡最邻近指数约为0.177,在空间上呈聚集型分布;核密度估计最大值出现在周河两岸的斜坡地带且呈带状分布,具有多个高密度聚集区域;滑坡面密度与点密度的计算结果分别为0.26%和0.19个/km²;滑坡坡度多集中于70°以上,坡向多集中于南和南东方向,坡高则集中于40 m以下的斜坡.通过聚类分析将研究区滑坡划分为不同类别的角度特征、高度特征、地质环境特征.     

Spatial operations in a GIS-based karst feature database

This paper presents the spatial implementation of the karst feature database (KFD) of Minnesota in a GIS environment. ESRI’s ArcInfo and ArcView GIS packages were used to analyze and manipulate the spatial operations of the KFD of Minnesota. Spatial operations were classified into three data manipulation categories: single layer operation, multiple layer operation, and other spatial transformation in the KFD. Most of the spatial operations discussed in this paper can be conducted using ArcInfo, ArcView, and ArcGIS. A set of strategies and rules were proposed and used to build the spatial operational module in the KFD to make the spatial operations more efficient and topographically correct.     

基于空间插值的工程岩体RQD预测方法

作为工程实际中评价岩体性质的重要指标,RQD的应用已相当广泛。但工程岩体中RQD值的分布存在一定的结构性和随机性,因此,通过对特定位置钻探获取的RQD值无法很到位地表达整个空间区域的实际岩石质量。为了弥补这方面的不足,统计学中的空间插值法为此提供了有力的手段。考虑到空间RQD分布存在各向异性,以及在工程坐标系中很难描述RQD分布的结构性,首先计算工程坐标系下已获取RQD值的主要黑塞方向（pHd）;然后构建空间旋转与比例缩放矩阵对其进行坐标标准化处理。在标准化的空间中,引入Kriging插值法,采用变异函数描述RQD在标准空间结构上的变化,建立其空间变异规律的数学模型,并对其进行插值计算;最后将标准空间进行坐标逆变换,实现了对工程坐标系下RQD分布的预测。利用R语言编程将该方法应用于工程实例,结果表明,这种空间插值法能够有效地预测工程岩体中RQD值的分布规律,弥补了局部钻探的局限性。     

Seasonal and interannual patterns of distribution and diet of bluefish within a Middle Atlantic bight estuary in relation to abiotic and biotic factors

Seasonal and interannual patterns in the spatial distribution of bluefish (Pomatomus saltatrix) within a Middle Atlantic Bight estuary were examined using multipanel gillnets fished biweekly at 14 fixeds stations in the Sandy Hook Bay-N avesink River estuary during May–November of 1998 and 1999. To characterize habitats along the estuarine gradient, we measured several abiotic and biotic variables concurrently with gillnet sampling. Juvenile (age-0 and age-1+) bluefish were captured regularly during both years along with large numbers of Atlantic menhaden (Brevoortia tyrannus), which were confirmed by diet analyses to be bluefish’s primary forage species. The date of initial appearance of age-0 bluefish and menhaden in the estuary varied between years and may have been related to interannual differences in seawater temperatures on the continental shelf during spring. Delayed estuarine arrival of prey fishes may have contributed to variability in bluefish diets between years. Within the estuary, bluefish spatial distribution were consistent across seasons and years: bluefish were most common in areas associated with high concentrations of suspended materials and the presence of menhaden. Community analyses also indicated habitat overlap between bluefish and menhaden. Spatial distribution patterns revealed the consistent occurrence of piscivorous bluefish in shallow estuarine habitats that retained suspended materials and aggregated prey fishes. Foraging success of bluefish and other estuarine piscivores may be closely linked with the availability of these productive habitat, highlighting the need for future study of biological interactions and the governing physical processes.     

基于GIS的吉林省地下水水质模糊评价

研究利用GIS空间分析与地统计分析工具,采用模糊综合评价方进行地下水水质评价。以吉林省为研究区域,选取10项具有代表性的水质指标进行评价。利用GIS生成吉林省矢量网格地图,由克里格插值估算出研究区域内的评价指标值,得到以网格为单位的各单项指标的预测分布图。根据模糊综合评价模型,评价吉林省地下水水质状况,并绘制吉林省地下水水质类别图。结果表明:区域内Ⅲ类水分布最为广泛,其次为Ⅴ类水;东部、南部城市延边、白山、通化、辽源等水质状况良好,达到Ⅲ类以上,其中白山及延边部分地区地下水类别达到Ⅱ类;白城、松原、长春及吉林市的部分地区地下水环境质量状况较差,属于Ⅴ类水质,其原因在于氟化物与氨氮污染较重。     

基于网格与GIS的油气资源空间分布与定量评价系统及其应用

论述了基于网格与GIS的油气资源空间分布与定量评价系统的建立方法.该系统能够根据离散的钻井数据和等值线数据进行插值分析,以网格单元为基础进行油气资源的计算与评价;可以用GIS来管理空间数据和属性数据,生成并制作特定地层的油气资源量空间分布专题图和油气藏形态模拟图.以四川盆地川东北地区二叠系气源岩的油气资源评价为例,模拟了其生烃史,计算了其累积生气强度、累计生气量和天然气资源量.     

Phytoplankton community composition and size distribution in the Langat River estuary,Malaysia

Phytoplankton patchiness, as expressed by community composition and size distribution, during the rainy season in the Langat River estuary (Malaysia) is described. Four sites in the estuary were sampled on two different occasions. The sampling area covered a stretch of the river from upstream to downstream of aquaculture activities (shrimp farms). Water samples from a shrimp farm outlet were also analyzed for nutrient and phytoplankton content. Differences in community structure between stations were found by means of multivariate procedures. Genera composition and total biomass were related to environmental factors, revealing salinity, light, and nutrients as important explaining factors. Elevated phytoplankton biomass and total phosphorus concentration, as well as lower inorganic nitrogen: phosphorus ratios, were found downstream of the shrimp farming activities. The size distribution spectrum of the phytoplankton population downstream of the shrimp farms was significantly different from that at the other stations but not different than that found in the sampled effluent from the shrimp farms, where phytoplankton biomass was also high. Twenty-two of the 24 recorded genera from the shrimp farm outlet were also found downstream of the farming activities. A number of different environmental factors potentially alter conditions for phytoplankton in the lower reaches of the estuary as compared to the upper regions. A cause and effect relationship explaining the differences noted between the upper and lower reaches of the estuary cannot be established. This study suggests that nutrient enrichment from the shrimp farming activities is of a magnitude that may contribute to the phytoplankton community changes observed in the lower reaches of the estuary.     

土壤重金属地球化学特征及环境评价——以张北县二台镇为例

张家口北部坝上草原地区属于典型的半干旱草原牧区,近年来受到人为活动影响,土地荒漠化加剧,草原生态系统受损严重。本研究依据张北县二台镇土地利用现状边界布设了136个土壤采样点,测定了土壤21个指标。运用主成分分析法与GIS空间插值(IDW)方法来分析土壤中重金属元素的空间迁移富集与分异机理,并采用地累积指数法、潜在生态危害指数法对表层土壤9种重金属元素(Cd、Hg、Mn、Cr、Cu、Pb、Zn、Ni和As)污染程度、生态风险进行评价。结果显示:研究区9种重金属元素土壤环境质量单指标等级评价以一等、低风险土壤为主。根据因子分析和主成分分析,Hg、Pb受人类活动及成土母质控制,其余7种元素均受成土母质的控制。地累积指数结果显示, 9种重金属元素除Hg以外地累积指数均小于0,总体为无污染等级,Hg为中污染等级。潜在生态危害指数结果显示Hg和Cd为潜在危害元素,其中Hg整体达到很强生态危害程度,Cd达到中等生态危害程度,其他元素为轻微生态危害程度。重金属综合生态危害指数(RI)表明在研究区七间窑村—哈拉勿素村以西地区为中等生态危害风险区,其余地区为轻微生态危害风险区。     

Creating an advanced backpropagation neural network toolbox within GIS software

An artificial neural network (ANN) toolbox is created within GIS software for spatial interpolation, which will help GIS users to train and test ANNs, perform spatial analysis, and display results as a single process. The performance is compared to that of the open source Fast Artificial Neural Network library and conventional interpolation methods by creating digital elevation models (DEMs) given that nearly exact solutions exist. Simulation results show that the advanced backpropagations such as iRprop speed up the learning, while they can get stuck in a local minimum depending on initial weight sets. Besides, the division of input–output examples into training and test data affects the accuracy, particularly when the distribution of the examples is skewed and peaked, and the number of data is small. ANNs, however, show the similar performance to inversed distance weighted or kriging and outperform polynomial interpolations as a global interpolation method in high-dimensional data. In addition, the neural network residual kriging (NNRK) model, which combines the ANN toolbox and kriging within GIS software, is performed. The NNRK outperforms conventional methods and well captures global trends and local variations. A key outcome of this work is that the ANN toolbox created within the de facto standard GIS software is applicable to various spatial analysis including hazard risk assessment over a large area, in particular when there are multiple potential causes, the relationship between risk factors and hazard events is not clear, and the number of available data is small given its performance for DEM generation.     

Indirect Effects of Salinity and Temperature on Kuwait’s Shrimp Stocks

Discharge of the Shatt Al-Arab is believed to be a dominating component of the northern Arabian Gulf’s ecology and largely responsible for productivity of Kuwait’s fisheries. With major construction of dams on the Tigris and Euphrates Rivers in Turkey, river discharge has been substantially reduced, and flooding essentially eliminated. We attempted to relate river flow and shrimp landings indirectly by correlating 19 years of salinity and temperature data from Kuwait’s waters with corresponding annual shrimp landings. For green tiger prawns (Penaeus semisulcatus), the combination of October salinities and January temperatures provided the best correlation (r = 0.67) with landings in the following shrimping season. For the combined landings of jinga and kiddi shrimps (Metapenaeus affinis and Parapenaeopsis stylifera, respectively), December salinity during season and May temperature prior to season resulted in the best correlation (r = 0.87). Landings of these two species also correlated well with spring and summer temperatures. Under normal conditions, late winter or early spring temperatures prior to fishing season influence recruitment of the green tiger prawn, whereas December salinities during harvest season influence the abundance of jinga–kiddi shrimps. With further reductions in the Shatt Al-Arab discharge and the elimination of flood events, Kuwait’s shrimp landings will most likely decrease over time.     

Combining Areal and Point Data in Geostatistical Interpolation: Applications to Soil Science and Medical Geography

A common issue in spatial interpolation is the combination of data measured over different spatial supports. For example, information available for mapping disease risk typically includes point data (e.g. patients’ and controls’ residence) and aggregated data (e.g. socio-demographic and economic attributes recorded at the census track level). Similarly, soil measurements at discrete locations in the field are often supplemented with choropleth maps (e.g. soil or geological maps) that model the spatial distribution of soil attributes as the juxtaposition of polygons (areas) with constant values. This paper presents a general formulation of kriging that allows the combination of both point and areal data through the use of area-to-area, area-to-point, and point-to-point covariances in the kriging system. The procedure is illustrated using two data sets: (1) geological map and heavy metal concentrations recorded in the topsoil of the Swiss Jura, and (2) incidence rates of late-stage breast cancer diagnosis per census tract and location of patient residences for three counties in Michigan. In the second case, the kriging system includes an error variance term derived according to the binomial distribution to account for varying degree of reliability of incidence rates depending on the total number of cases recorded in those tracts. Except under the binomial kriging framework, area-and-point (AAP) kriging ensures the coherence of the prediction so that the average of interpolated values within each mapping unit is equal to the original areal datum. The relationships between binomial kriging, Poisson kriging, and indicator kriging are discussed under different scenarios for the population size and spatial support. Sensitivity analysis demonstrates the smaller smoothing and greater prediction accuracy of the new procedure over ordinary and traditional residual kriging based on the assumption that the local mean is constant within each mapping unit.     

Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach

Spatial probabilistic modeling of slope failure using a combined Geographic Information System (GIS), infinite-slope stability model and Monte Carlo simulation approach is proposed and applied in the landslide-prone area of Sasebo city, southern Japan. A digital elevation model (DEM) for the study area has been created at a scale of 1/2500. Calculated results of slope angle and slope aspect derived from the DEM are discussed. Through the spatial interpolation of the identified stream network, the thickness distribution of the colluvium above Tertiary strata is determined with precision. Finally, by integrating an infinite-slope stability model and Monte Carlo simulation with GIS, and applying spatial processing, a slope failure probability distribution map is obtained for the case of both low and high water levels.