Mapping the HIV/AIDS epidemic in Nigeria using exploratory spatial data analysis

This paper examines the spatial variation of HIV/AIDS prevalence rates in Nigeria. It uses Exploratory Spatial Data Analytical (ESDA) techniques to provide insight into the pattern. The overriding objective is to determine if there is a significant spatial clustering of HIV/AIDS. The calculated and mapped Global and Local Moran’s I, and Getis and Ord G _i * values reveal certain states such as Benue, Nassarawa, Federal Capital Territory (FCT) and Cross River have significant spatial clusters of HIV/AIDS rates in Nigeria. The spatial analysis enables policy makers to identify states most affected, and design effective and culturally acceptable preventive measures. Specific policies targeted at states are a more appropriate approach in tackling the epidemic rather than the usual universal cookie-cut HIV reduction strategies that may not be applicable to the different cultural milieu.     

Estimation of volcanic hazards based on Cox stochastic processes

Assessments of the probability and the consequences of future volcanic activity can be critical aspects when evaluating the safety of the population and of industrial plants. A new methodology has been developed for the probabilistic modelling of volcanic hazards based on regional volcanic data that facilitates the production of probabilistic hazard maps for various volcanic scenarios (lava flows, tephra). The stochastic model is based on Cox processes and allows account to be taken of the observed temporal and spatial correlation inherent in volcanic eruptions. The model is applied to the Quaternary field of the Osteifel region where the forecast number of future eruptions and the probabilities related to the different scenarios are estimated using a Monte Carlo approach. The obtained hazard maps of future volcanic events are part of a comprehensive hazard analysis and serve as a major input for the risk analysis that will determine the consequences of forecast volcanic activity at the site.     

A tale of Asia’s world ports: The spatial evolution in global hub port cities

Globalization and transport revolutions, logistics integration, and the consequent expansion of port area and hinterland in the maritime industry have redefined the functional role of ports in supply chains and have generated a new pattern of freight distribution. This phenomenon again requires a new approach towards port development and related urban planning. Such changes have inevitably influenced the spatial structure of hub port cities. As existing models on spatial and functional evolution of ports and cities are mainly derived from European and American cases, this paper attempts to introduce evidence from an Asian perspective, focusing on the particular case of global hub port cities such as Hong Kong and Singapore.     

Hybrid Model for Urban Air Pollution Forecasting: A Stochastic Spatio-Temporal Approach

Air pollution is usually driven by a complex combination of factors in which meteorology, physical obstacles, and interactions between pollutants play significant roles. Considering the characteristics of urban atmospheric pollution and its consequent impacts on human health and quality of life, forecasting models have emerged as an effective tool to identify and forecast air pollution episodes. The overall objective of the present work is to produce forecasts of pollutant concentrations with high spatio-temporal resolution and to quantify the uncertainty in those forecasts. Therefore, a new approach was developed based on a two-step methodology. Firstly, neural network models were used to generate short-term temporal forecasts based on air pollution and meteorology data. The accuracy of those forecasts was then evaluated against an independent set of historical data. Secondly, local conditional distributions of the observed values with respect to the predicted values were used to perform spatial stochastic simulations for the entire geographic area of interest. With this approach the spatio-temporal dispersion of a pollutant can be predicted, while accounting for both the temporal uncertainty in the forecast (reflecting the neural networks efficiency at each monitoring station) and the spatial uncertainty as revealed by the spatial variograms. Based on an analysis of the results, our proposed method offers a highly promising alternative for the characterization of urban air quality.     

HIV and AIDS in Africa: a geographic analysis at multiple spatial scales

This study offers an alternative method rooted in GIS techniques and spatial analysis to estimate HIV/AIDS prevalence over space from an incomplete surveillance data set and explain the variation of those estimates. The results clearly show that the HIV/AIDS epidemic is complex and that it is interconnected with other geographic, historical, economic and cultural phenomena which help explain its spatial spread and variation. The regression models which were developed in this paper illustrated that variables which measure the historical context of colonialism such as resource exploitation and labor migration, gender, culture, contemporary global forces, poverty and disease burden have all contributed variously to the rapid spread of this disease both in space and time. The policy implication is that concentrating on behavior change or therapy alone may not turn the epidemic around. The attack needs to be multifaceted and interdisciplinary taking into consideration the context and the economic and social realities at multiple spatial scales.     

Direct forecasting of reservoir performance using production data without history matching

The conventional paradigm for predicting future reservoir performance from existing production data involves the construction of reservoir models that match the historical data through iterative history matching. This is generally an expensive and difficult task and often results in models that do not accurately assess the uncertainty of the forecast. We propose an alternative re-formulation of the problem, in which the role of the reservoir model is reconsidered. Instead of using the model to match the historical production, and then forecasting, the model is used in combination with Monte Carlo sampling to establish a statistical relationship between the historical and forecast variables. The estimated relationship is then used in conjunction with the actual production data to produce a statistical forecast. This allows quantifying posterior uncertainty on the forecast variable without explicit inversion or history matching. The main rationale behind this is that the reservoir model is highly complex and even so, still remains a simplified representation of the actual subsurface. As statistical relationships can generally only be constructed in low dimensions, compression and dimension reduction of the reservoir models themselves would result in further oversimplification. Conversely, production data and forecast variables are time series data, which are simpler and much more applicable for dimension reduction techniques. We present a dimension reduction approach based on functional data analysis (FDA), and mixed principal component analysis (mixed PCA), followed by canonical correlation analysis (CCA) to maximize the linear correlation between the forecast and production variables. Using these transformed variables, it is then possible to apply linear Gaussian regression and estimate the statistical relationship between the forecast and historical variables. This relationship is used in combination with the actual observed historical data to estimate the posterior distribution of the forecast variable. Sampling from this posterior and reconstructing the corresponding forecast time series, allows assessing uncertainty on the forecast. This workflow will be demonstrated on a case based on a Libyan reservoir and compared with traditional history matching.     

Tailoring spatial reference in early warning systems to administrative units

This paper presents a novel approach for early warning systems to transform the spatial reference of dispersion models into addressable administrative units enabling an intelligible warning message reception and spatial awareness. The spatial reference along the entire information chain from sensor measurements via dispersion model to warning dissemination is discussed. Core concept behind this approach is the application of the Egenhofer-Model for analysis of binary topologic relations. It is used to identify topologic relations between dispersion model forecasts and administrative units. The result set of intersection matrices defines the relations that are counted for area classification with hazard specific parameters. Following the design for a generic and hazard-independent web service based on Open Geospatial Consortium (OGC) standards is presented in combination with results of the reference implementation.     

Applying GIS to assess the vulnerability of the Päijänne water-conveyance tunnel in Finland

Using GIS, relevant hydrogeological, geological and technical data on the Päijänne Tunnel in Finland were assembled with regional environmental datasets for spatial analysis of vulnerability and environmental risk. This 120-km rock tunnel conveys potable water to the Helsinki metropolitan area. It is connected to local groundwater circulation through fractures and, consequently, it is at risk from contaminant transport. The observed heterogeneity in the occurrence of superficial deposits, in fracturing in the rock mass and in hydraulic activity are used to recommend alternatives for (1) focusing the assessment and eventual protective measures; and (2) for delineating the recommended zone of caution for protection of tunnel water. Central criteria in identifying vulnerable locations are the spatial distribution of interlinked highly localized groundwater inflows measured inside the tunnel and the iteratively interpreted fracture zones. Among the relevant considerations for assessing risk are the large volume of flow in the tunnel, the irregular distribution of potentially hazardous human activities, and the interplay of natural and human-influenced factors. The study demonstrates a visual and expressive approach using GIS to support sound land-use planning and water resource protection, based on the geology and taking into account of the dynamics of the underground construction.     

中国SARS疫情的探索性空间数据分析

运用空间统计学手段对中国省级SARS疫情的空间分布格局做了探索性的空间数据分析(exploratory spatial data analysis)。Moran I统计分析表明SARS疫情的分布具有很强的空间自相关，Moran Scatterplot进一步揭示了这一空间关系的地域差异及其各区位SARS疫情分布对总体趋势的偏移，[WTBX]Gi*[WTBZ] 统计则确定了疫情分布的空间集聚模式及其随时空转移轨迹。分析表明中国省级SARS疫情的发展并非一个相互独立的过程,而是存在着统计学意义上可测度的空间关系，且这种关系在空间相邻时最为显著。     

水文响应单元空间离散化及SWAT模型改进

水文响应单元(Hydrological Response Units,HRU)是SWAT模型模拟的基本单元,传统方法划分的水文响应单元在空间分布上不连续且难以确定其明确的空间位置,不能反映HRU间的相互作用和进行精确空间分析。利用GIS工具对土地利用和土壤类型数据进行概化处理,提出了HRU空间离散化的方法,实现了水文响应单元在空间上的准确定位。在此基础上,针对SWAT模型中同一子流域所有HRU采取相同延迟的弱点进行改进,并选择太湖地区西苕溪流域对改进的SWAT模型进行水文模拟验证。改进后,校正期港口站Nash效率系数E_NS(Nash-Sutcliffe Efficiency)从0.64提高到0.67,验证期E_NS系数从0.70提高到0.76。研究表明:修正后的SWAT模型更能反映流域的水文特征,可以达到非常好的效果,考虑到HRU距离因素的径流延迟更为准确地刻画径流过程。实现HRU空间离散化将为模型改进和更小尺度的空间分析提供数据基础。     

The typology of Irish hard-rock aquifers based on an integrated hydrogeological and geophysical approach

Groundwater flow in hard-rock aquifers is strongly controlled by the characteristics and distribution of structural heterogeneity. A methodology for catchment-scale characterisation is presented, based on the integration of complementary, multi-scale hydrogeological, geophysical and geological approaches. This was applied to three contrasting catchments underlain by metamorphic rocks in the northern parts of Ireland (Republic of Ireland and Northern Ireland, UK). Cross-validated surface and borehole geophysical investigations confirm the discontinuous overburden, lithological compartmentalisation of the bedrock and important spatial variations of the weathered bedrock profiles at macro-scale. Fracture analysis suggests that the recent (Alpine) tectonic fabric exerts strong control on the internal aquifer structure at meso-scale, which is likely to impact on the anisotropy of aquifer properties. The combination of the interpretation of depth-specific hydraulic-test data with the structural information provided by geophysical tests allows characterisation of the hydrodynamic properties of the identified aquifer units. Regionally, the distribution of hydraulic conductivities can be described by inverse power laws specific to the aquifer litho-type. Observed groundwater flow directions reflect this multi-scale structure. The proposed integrated approach applies widely available investigative tools to identify key dominant structures controlling groundwater flow, characterising the aquifer type for each catchment and resolving the spatial distribution of relevant aquifer units and associated hydrodynamic parameters.     

Interpolation by regularized spline with tension: II. Application to terrain modeling and surface geometry analysis

A general approach to the computation of basic topographic parameters independent of the spatial distribution of given elevation data is developed. The approach is based on an interpolation function with regular first and second order derivatives and on application of basic principles of differential geometry. General equations for computation of profile, plan, and tangential curvatures are derived. A new algorithm for construction of slope curves is developed using a combined grid and vector approach. Resulting slope curves better fulfill the condition of orthogonality to contours than standard grid algorithms. Presented methods are applied to topographic analysis of a watershed in central Illinois.     

基于面向服务体系结构（SOA）的钾盐资源潜力系统

为了对中国钾盐矿产资源潜力进行全面预测,建立了全国性的钾盐矿产资源潜力预测系统。对收集的钾盐信息进行系统地整理,在Oracle空间数据库中建立面向对象的空间数据模型,基于面向服务体系结构进行系统的框架设计,将属性数据和空间数据的操作发布为Web服务,客户端通过网络调用服务实现空间与属性数据的一体化管理及分析,采用面向对象语言C#和ArcObjects二次开发具体实现本系统。系统可通过Web服务与其他地学系统有机集成,对地学数据基于服务集成与共享及一站式服务具有重要参考价值。     

基于GIS的矿产预测地质解译空间信息集成

利用我国海量地质标准基础数据库中的数字地质图和矿产图,通过基于GIS的地质解译空间集成地质信息,将其用于综合信息矿产预测。以地质解译系统对内蒙大兴安岭南段1∶20万成矿预测的应用为案例,阐述地质信息的空间提取与集成过程：首先在建立地质字典库实现地质空间信息共享的基础上,通过矿化密集区对地质模型的分类图层进行空间分析,建立地质成矿空间信息库和图库;然后,基于典型矿床圈定模型单元,通过模型单元与地质成矿空间信息库和图库的空间分析,建立地质找矿模型;最后,基于地质单元对地质成矿空间信息库和图库的二次空间集成,完成预测模型的地质空间信息提取与集成。将本方法应用在银矿案例的综合信息矿产预测靶区评价上,得到可供进一步查证的新增靶区比已知靶区增加了近5倍。     

全球变化与地表参数的定量遥感

从全球变化研究对遥感获取地表时空多变要素信息的需求 ,论述定量遥感中对地表多尺度空间信息作地学描述的新思路和新方法。在分析了变差图描述方法的特点及其不足的基础上 ,提出了直方变差图的概念 ,通过定义驻点和边界点 ,尝试采用直方变差图分解的方法分析地物空间分布规律 ,并通过一个实验对此方法进行了说明。进而基于对地表空间分布信息的提取 ,将可见光、近红外波段遥感信息用于热红外遥感的地温反演 ,利用地表空间结构和大气温度空间分布模式的差异 ,将热红外遥感图像分为地表贡献和大气贡献两部分 ,通过空间相关性分析 ,寻求从热红外遥感图像中直接分离出大气的空间分布模式的方法 ,以解决地温反演中面临的困难。已有的研究结果说明了在全球变化和定量遥感研究中 ,对地表多尺度空间变化信息作简洁的地学描述的必要性及其重要的应用意义。     

Estimating the indices of inter-transmissibility magnitude of active surficial hydrogeologic units in Itu,Akwa Ibom State,southern Nigeria

Itu Local Government Area is prone to groundwater contamination occasioned by saltwater due to the geographical location and the aquifer unit inter-transmissibility between the communicating/interconnected pores of the water-bearing units. This inter-transmissibility causes the continuous distribution of contamination among interconnected aquifer repositories. The study integrated the surface electric mapping and laboratory analysis of geologic samples and their corresponding water samples in estimating the transmissibility-dependent petrophysical parameters. The functional relationships between parameters have been determined. Maps of the spatial distribution of the estimated geohydraulic parameters have been drawn. Quantitative links of measured parameters to transmissibility have established. The resulting inferences based on the indices or magnitudes of the parameters measured helped in delineating the directions of water transmission within and across the hydrogeological units under study. The inferred result of permeability serves as a guide in identifying the southern zone of the area under study as having relatively reduced hydraulic pressure gradient differential, while the northern region has on the average, high hydraulic gradient differentials. The results of directions of inter-transmissibility of hydrodynamic properties in aquifer units are promising and capable of increasing the depth of knowledge on groundwater contamination and hence provide substantial input parameters that can enhance groundwater modelling within and near the study location.     

Estimation of weathering rates for critical load calculations in Finland

 The formation of base cations through mineral weathering in forest soils is one of the key parameters in calculating critical loads. Weathering rates in Finland have been estimated using a variety of methods. In the first approach, three weathering rate categories were assigned to soils according to the bedrock type. The second approach was based on an empirical relationship obtained from Swedish field studies. Changes in zirconium content through the soil profile were used to estimate element losses in soil after deglaciation. These calculated losses correlated well with the total calcium and magnesium concentrations in till C-horizons and the effective temperature sum (ETS). Comprehensive geochemical data for the parent till fine fraction (<0.06 mm) was available through the reconnaissance scale till geochemical mapping program of the Geological Survey of Finland (GSF). The equations obtained from Swedish studies were based on the use of the coarse (<2.0 mm) till fraction, and the differences in element concentrations between the fine and coarse size fractions remained a potential source of uncertainty estimating overall weathering rates. In the third approach, new geochemical data from the <2.0 mm till fraction from southern Finland were used to make new weathering rate estimates. The use of soil geochemistry instead of bedrock map classification clearly led to an improvement in the estimates of soil weathering rates in glacied terrains. The use of the fine till fraction (<0.06 mm) in the zirconium approach generally resulted in overestimations of the weathering rate. The new geochemical data for the coarse till fraction (<2 mm) are now consistent with the input requirements of the zirconium method, although the results still require further evaluation. Finnish soil profiles have a shorter weathering history than most of the Swedish ones and the uppermost layer in Finnish podsols has in some cases developed in a different till layer than the C-horizon. Received: 15 October 1995 · Accepted: 8 March 1996     

Innovative landslide susceptibility mapping supported by geomorphon and geographical detector methods

Landslides are among the most common and dangerous natural hazards in mountainous regions that can cause damage to properties and loss of lives. Landslide susceptibility mapping (LSM) is a critical tool for preventing or mitigating the negative impacts of landslides. Although many previous studies have employed various statistical methods to produce quantitative maps of the landslide susceptibility index (LSI) based on inventories of past landslides and contributing factors, they are mostly ad hoc to a specific area and their success has been hindered by the lack of a methodology that could produce the right mapping units at proper scale and by the lack of a general framework for objectively accounting for the differing contribution of various preparatory factors. This paper addresses these issues by integrating the geomorphon and geographical detector methods into LSM to improve its performance. The geomorphon method, an innovative pattern recognition approach for identifying landform elements based on the line of sight concept, is adapted to delineate ridge lines and valley lines to form slope units at self-adjusted spatial scale suitable for LSM. The geographical detector method, a spatial variance analysis method, is integrated to objectively assign the weights of contributing factors for LSM. Applying the new integrated approach to I-Lan, Taiwan produced very significant improvement in LSI mapping performance than a previous model, especially in highly susceptible areas. The new method offers a general framework for better mapping landslide susceptibility and mitigating its negative impacts.     

Comparison of mineralization pattern of geochemical data in spatial and position-scale domain using new DWT- PCA approach

In the current research to determine the mineralization pattern and discuss the mineralization components, the information of position - scale domain of geochemical data has been analyzed. A new method is proposed based on coupling discrete wavelet transforms (DWT) and principal component analysis (PCA) for mineralization elements forecasting applications. The results of this study indicate the potential of DWT–PCA method for geochemical data processing. Wavelet transform (WT), as a multi-spectral analysis method, can decompose the spatial and temporal signals into different frequencies. The features of mineralization can be identified using the position - scale domain of geochemical data that may not be achievable in spatial domain. The geochemical data from the Dalli region have been processed in the spatial domain using PCA. The surface geochemical data of 30 elements have been transformed to position–scale domain using two-dimensional discrete wavelet transform (2DDWT). Wavelet functions (WFs) of Haar, Coiflet2, Biorthogonal3.3 and Symlet7 have been applied separately to decompose the geochemical data to high and low frequencies in one level. To obtain more accurate and complete information of mineralization, a new index has been presented based on wavelet coefficients. Based on this new index, significant results have been obtained by using PCA of the index. The coefficients distribution map (CDM) as a new exploratory criterion has been generated based on 2DDWT to show the geochemical distribution map (GDM). Finally, the results of WT have been compared with the results of spatial domain and the best method of wavelet for interpretation of geochemical data has been introduced. The results of geochemical data analysis by DWT–PCA approach have been confirmed by the exploratory drillings in the study area.     

利用相控模型进行井间参数预测

储层物性参数在空间的展布，一直是储层非均质性研究的难点，利用分形和蒙特卡洛方法，在精细的沉积微相及小层对比研究基础之上，预测了井间的岩石相分布，并根据取心井资料，建立了各种岩石相的渗透率相控模型，从而预测出井间渗透率的分布。该方法以地质特征为基础，将地质资料与数学方法相结合，充分体现了渗透率在井间既具有连续性，同时变化又非常剧烈的特点，为储层物性空间预测提供了新的思路。