利用 GIS地理统计模块预测海南岛植被指数季节性变化趋势

虽然采用遥感图像提取的植被指数在空间上能较好的反映作物的状况,但其不能预测植被指数在空间上的变化范围,如果能从整体上了解不同市县在不同季节的平均植被指数值,就可以对该区域整体植被状态进行量化分析,也就可以从大范围内进行植被指数的预测分析.利用地理信息系统(GIS)和地统计学相结合的地理统计分析模块(ArcGIS Geostatistical Analyst),根据MODIS遥感数据提取的每季度不同市县平均NDVI植被指数,采用Kriging插值的方法分析了海南岛归一化植被指数(NDVI)季节性变化趋势,并     

On the physical geometry concept at the basis of space/time geostatistical hydrology

The objective of this paper is to show that the structure of the spatiotemporal continuum has important implications in practical stochastic hydrology (e.g., geostatistical analysis of hydrologic sites) and is not merely an abstract mathematical concept. We propose that the concept of physical geometry as a spatiotemporal continuum with properties that are empirically defined is important in hydrologic analyses, and that the elements of the spatiotemporal geometry (e.g., coordinate system and space/time metric) should be selected based on the physical properties of the hydrologic processes. We investigate the concept of space/time distance (metric) in various physical spaces, and its implications for hydrologic modeling. More specifically, we demonstrate that physical geometry plays a crucial role in the determination of appropriate spatiotemporal covariance models, and it can affect the results of geostatistical operations involved in spatiotemporal hydrologic mapping.     

Hydrogeological modeling of radionuclide transport in low permeability media: a comparison between Boom Clay and Ypresian Clay

Deep low-permeability clay layers are considered as suitable environments for disposal of high-level radioactive waste. In Belgium, the Boom Clay is the reference host formation and the Ypresian Clay an alternative host formation for research and safety and feasibility assessment of deep disposal of nuclear waste. In this study, two hydrogeological models are built to calculate the radionuclide fluxes that would migrate from a potential repository through these two clay formations. Transport parameter heterogeneity is incorporated in the models using geostatistical co-simulations of hydraulic conductivity, diffusion coefficient and diffusion accessible porosity. The calculated radionuclide fluxes in the two clay formations are compared. The results show that in the Ypresian Clay larger differences between the fluxes through the lower and the upper clay boundary occur, larger total output radionuclide amounts are calculated and a larger effect of parameter heterogeneity on the calculated fluxes is observed, compared to the Boom Clay.     

乌鲁木齐市米东区农田土壤重金属含量的空间分布特征

利用地理信息系统（GIS）及地统计学方法,对乌鲁木齐米东区农田土壤中重金属（Hg、Cu、Zn、Pb、Ni、Cd及Cr）的含量进行空间变异性分析。结果表明：除Cu、Zn、Pb和Hg超过土壤背景值外,7种重金属的平均含量均未超过国家环境质量二级标准（GB15618-1995）;7种重金属均具有较好的空间变异结构,可以用指数模型、球状模型和高斯模型拟合,且具有不同程度的块金效应;Cd、Cr具有强烈的空间自相关性,Pb、Ni、Cu、Zn和Hg属中等强度空间相关, 说明其含量受外源污染的影响较大;采用普通克里格插值法得出7种重金属的空间分布图,除Cd空间分布规律不明显外,其它6种重金属均存在显著的空间分布规律。     

Optimization tools and simulation methods for designing and evaluating a mining operation

Some of the major advances in the field of mining in the last three decades have referred to the development of new design and planning techniques for optimizing open-pit mining and the inclusion of a stochastic perspective in economic models that is more revealing than a purely deterministic perspective. These advances include the use of parametric techniques in the design and planning process, the formulation of criteria for establishing an optimum cut-off grade policy when the economic goal is to optimize net present value (NPV), and the introduction of economic risk analysis. This paper examines some of the difficulties involved in applying these techniques—arising largely as a result of a lack of knowledge of the spatial location and distribution of the deposit grades—and analyses how these difficulties can be tackled with the help of geostatistical simulation techniques that take probabilistic criteria into consideration during the optimization process. These techniques enable equally likely representations of the deposit to be obtained that reproduce the main dispersion features for the starting experimental data (covariance or variogram, as well as the histogram). Consequently, the uncertainty in regard to the deposit as well as its influence on the economic assessment of the deposit in risk terms can be evaluated. This paper also describes a simple method for introducing price and cost increases into the risk analysis via the Monte Carlo method and shows how geological, technical and economic uncertainty can be integrated in risk analyses. Although it is true that the relationship between prices and costs is maintained constant in mining planning based on using parametric techniques, it is no less true that the risk analysis requires the use of models in which the main parameters with a bearing on deposit economics are considered as stochastic variables. The proposed methodology simplifies the calculations and easily integrates the different sources of uncertainty.

Non-uniqueness of inverse transmissivity field calibration and predictive transport modeling

Recent work with stochastic inverse modeling techniques has led to the development of efficient algorithms for the construction of transmissivity (T) fields conditioned to measurements of T and head. Small numbers of calibration targets and correlation between model parameters in these inverse solutions can lead to a relatively large region in parameter space that will produce a near optimal calibration of the T field to measured heads. Most applications of these inverse techniques have not considered the effects of non-unique calibration on subsequent predictions made with the T fields. Use of these T fields in predictive contaminant transport modeling must take into account the non-uniqueness of the T field calibration. A recently developed ‘predictive estimation’ technique is presented and employed to create T fields that are conditioned to observed heads and measured T values while maximizing the conservatism of the associated predicted advective travel time. Predictive estimation employs confidence and prediction intervals calculated simultaneously on the flow and transport models, respectively. In an example problem, the distribution of advective transport results created with the predictive estimation technique is compared to the distribution of results created under traditional T field optimization where model non-uniqueness is not considered. The predictive estimation technique produces results with significantly shorter travel times relative to traditional techniques while maintaining near optimal calibration. Additionally, predictive estimation produces more accurate estimates of the fastest travel times.     

基于协同克里金方法的重力梯度全张量三维约束反演

随着重力梯度全张量测量技术的日趋成熟,重力梯度全张量数据的三维反演技术日益受到重视与关注.全张量数据反演与重力数据反演一样仍然面临着严重的多解性问题.本文将基于地质统计学的协同克里金方法应用于重力梯度全张量数据三维反演,建立了密度约束下的多变量协同克里金联合反演方程,以降低反演的多解性.模型试验表明密度信息的加入能够有效降低反演的多解性,提高反演结果的分辨率,尤其是纵向分辨率能够得到显著提高.最后对美国德克萨斯州一个岩丘区所获得实际资料的应用表明了本文方法的实用性.     

The hydrochemical facies and anomalous fluoride content in the Serra Geral aquifer system,southern Brazil: a GIS approach with tectonic and principal component analysis

Groundwater with high fluoride content and water mixture patterns were studied in Serra Geral aquifer system (SGAS) using three aspects, principal component analysis (PCA), tectonic scenery and hydrochemical interpretation from 309 groundwater chemical data information from deep wells. A four-component model is suggested and explains 81% of total variance in the PCA. Six hydrochemical facies were identified. These facies suggest two different fluoride sources. Tectonic approach shows the relationship between defined hydrochemical facies and regional fracture control. The applied methodology reveals a minimum level to understand hydrochemical mixtures. The fluoride enrichment mechanisms into the groundwater are comprised in advance to guide the future uses of SGAS to the public supply.     

Combining categorical and continuous spatial information within the Bayesian maximum entropy paradigm

Due to the fast pace increasing availability and diversity of information sources in environmental sciences, there is a real need of sound statistical mapping techniques for using them jointly inside a unique theoretical framework. As these information sources may vary both with respect to their nature (continuous vs. categorical or qualitative), their spatial density as well as their intrinsic quality (soft vs. hard data), the design of such techniques is a challenging issue. In this paper, an efficient method for combining spatially non-exhaustive categorical and continuous data in a mapping context is proposed, based on the Bayesian maximum entropy paradigm. This approach relies first on the definition of a mixed random field, that can account for a stochastic link between categorical and continuous random fields through the use of a cross-covariance function. When incorporating general knowledge about the first- and second-order moments of these fields, it is shown that, under mild hypotheses, their joint distribution can be expressed as a mixture of conditional Gaussian prior distributions, with parameters estimation that can be obtained from entropy maximization. A posterior distribution that incorporates the various (soft or hard) continuous and categorical data at hand can then be obtained by a straightforward conditionalization step. The use and potential of the method is illustrated by the way of a simulated case study. A comparison with few common geostatistical methods in some limit cases also emphasizes their similarities and differences, both from the theoretical and practical viewpoints. As expected, adding categorical information may significantly improve the spatial prediction of a continuous variable, making this approach powerful and very promising.