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Combining ordination techniques and geostatistics to determine the patterns of diatom distributions at Lake Lama, Central Siberia

The patterns of spatial variation of diatom assemblages from surface sediments in Lake Lama were quantified using a combined approach of ordination and geostatistics. The aims were (i) to estimate the amount of variation between diatom assemblages within the lake, (ii) to model the spatial variability of the diatom assemblages and their diversity, and (iii) to map the diatom distributions in the lake. A correspondence analysis (CA) separated the diatom assemblages into a planktonic and a periphytic group. Rheophilic taxa were found within the periphytic group. Variogram analysis showed that only the sample scores of the first CA axis and the Shannon diversity index were spatially structured. The range of spatial correlation was estimated to be 55 km for both variables. The diversity and, to a lesser extent, the sample scores had considerable small-scale variability of about 20 and 3%, respectively. Estimates of the first component of the CA and the Shannon index were derived using block-kriging. The maps of the estimates provided a basis for partitioning Lake Lama according to the spatial structures into an eastern and a western basin, a north–south connection between the basins, and a north–south directed tip at the far eastern end. It was shown that variation in diatom assemblages is mainly spatially structured at the catchment scale and that there is a considerable amount of variation at smaller scales. According to the modeled spatial distribution, the assemblages are most likely affected by the lake size, morphology, and the water and nutrient input introduced by rivers. This has to be taken into account when paleolimnological interpretations are drawn from records of complex lake systems like Lake Lama.     

划分重磁区域异常与局部异常的一种方法泛克立格法

在重（磁）资料的分析处理中,经常需要划分区域异常与局部异常。本文对用于矿床品位预测的方法—泛克立格法加以改进、完善,使其适合于求重（磁）资料的区域异常与局部异常。根据某点周围若干个信息点上的重（磁）观测数据估计出该点处的区域异常值,而且这种估计是在满足线性、无偏、最小估计方差条件下求得的。从重（磁）观测数据中减去区域异常就可得到局部异常,这就是泛克立格法。它比经常用来划分区域异常与局部异常的方法—趋势分析方法有许多优点。趋势分析方法只是泛克立格法的一个特例。在本文中,作者还提出在小范围内,重力区域异常适合于用一次多项式拟合;而磁法区域异常适合于用二次多项式拟合的观点     

Dynamic stochastic estimation of physical variables

A fundamental problem facing the physical sciences today is analysis of natural variations and mapping of spatiotemporal processes. Detailed maps describing the space/time distribution of groundwater contaminants, atmospheric pollutant deposition processes, rainfall intensity variables, external intermittency functions, etc. are tools whose importance in practical applications cannot be overestimated. Such maps are valuable inputs for numerous applications including, for example, solute transport, storm modeling, turbulent-nonturbulent flow characterization, weather prediction, and human exposure to hazardous substances. The approach considered here uses the spatiotemporal random field theory to study natural space/time variations and derive dynamic stochastic estimates of physical variables. The random field model is constructed in a space/time continuum that explicitly involves both spatial and temporal aspects and provides a rigorous representation of spatiotemporal variabilities and uncertainties. This has considerable advantages as regards analytical investigations of natural processes. The model is used to study natural space/time variations of springwater calcium ion data from the Dyle River catchment area, Belgium. This dataset is characterized by a spatially nonhomogeneous and temporally nonstationary variability that is quantified by random field parameters, such as orders of space/time continuity and random field increments. A rich class of covariance models is determined from the properties of the random field increments. The analysis leads to maps of continuity orders and covariances reflecting space/time calcium ion correlations and trends. Calcium ion estimates and the associated statistical errors are calculated at unmeasured locations/instants over the Dyle region using a space/time kriging algorithm. In practice, the interpretation of the results of the dynamic stochastic analysis should take into consideration the scale effects.     

Downscaling in remote sensing

Downscaling has an important role to play in remote sensing. It allows prediction at a finer spatial resolution than that of the input imagery, based on either (i) assumptions or prior knowledge about the character of the target spatial variation coupled with spatial optimisation, (ii) spatial prediction through interpolation or (iii) direct information on the relation between spatial resolutions in the form of a regression model. Two classes of goal can be distinguished based on whether continua are predicted (through downscaling or area-to-point prediction) or categories are predicted (super-resolution mapping), in both cases from continuous input data. This paper reviews a range of techniques for both goals, focusing on area-to-point kriging and downscaling cokriging in the former case and spatial optimisation techniques and multiple point geostatistics in the latter case. Several issues are discussed including the information content of training data, including training images, the need for model-based uncertainty information to accompany downscaling predictions, and the fundamental limits on the representativeness of downscaling predictions. The paper ends with a look towards the grand challenge of downscaling in the context of time-series image stacks. The challenge here is to use all the available information to produce a downscaled series of images that is coherent between images and, thus, which helps to distinguish real changes (signal) from noise.     

中国地质统计学（空间信息统计学）发展的回顾与前景

讨论了地质统计学（空间信息统计学）发展的若干问题，其内容包括４部分：１．地质统计学的理论及方法；２．关于软件系统的现状；３．关于实际应用；４．地质统计学发展前景的若干看法。     

Kriging with imprecise (fuzzy) variograms. I: Theory

Imprecise variogram parameters are modeled with fuzzy set theory. The fit of a variogram model to experimental variograms is often subjective. The accuracy of the fit is modeled with imprecise variogram parameters. Measurement data often are insufficient to create good experimental variograms. In this case, prior knowledge and experience can contribute to determination of the variogram model parameters. A methodology for kriging with imprecise variogram parameters is developed. Both kriged values and estimation variances are calculated as fuzzy numbers and characterized by their membership functions. Besides estimation variance, the membership functions are used to create another uncertainty measure. This measure depends on both homogeneity and configuration of the data.     

各向异性矿化特征的分析与模拟 及其在储量估算中的应用

矿化作用往往是地质事件及局部过程共同作用的结果,导致矿体空间形态复杂多变、矿石品位呈各向异性、尺度不一的非线性空间变异模式.传统方法无论是在矿石量的计算方面还是在矿块内平均品位的确定上都存在多种误差,并且无法实现信息的动态管理及直观表达.文章以安庆铜矿中心矿区为例,采用对数块kriging与三维地学模拟技术相结合的方法...     

基于滑动L2优化准则的GPS坐标时间序列重构

GPS坐标时间序列中不仅包含白噪声,还包含闪烁噪声、随机漫步噪声等有色噪声,这些噪声将影响GPS应用的可靠性,甚至可能对一些地球物理现象做出错误的解释,因此降低GPS坐标时间序列中有色噪声的影响、提高GPS精度是一个重要和基本的问题。提出了一种滑动L₂优化估计方法(ML₂),通过选取合适的窗口建立L₂优化模型,再利用交替迭代乘子法求解每段时间序列的优化问题,并逐年滑动得到整段GPS坐标时间序列的估计。实验结果表明,ML₂方法与奇异谱分析、小波分解、滑动普通最小二乘法相比具有更好的重构效果。     

某污染场地土壤苯并(a)芘含量的三维估值及不确定性分析

污染场地修复前的准确评估是开展场地修复行动的基础和前提。建立了一套评估污染场地中污染土方量的三维插值方法,采用该方法模拟了某污染场地土壤苯并(a)芘(BaP)含量的空间分布并分析其不确定性。结果表明：场地地下环境中BaP含量数据服从对数正态分布,土壤中污染严重区域分别位于研究区的西南部和北部。通过普通克里格插值得到的BaP浓度超过0.4 mg·kg^-1的污染羽体积为14134 m³,对应的累积概率为0.585。依据给定变差范围值计算,得出现有收集数据对整个场地的描述程度为65%。基于该三维插值方法能准确地反映场地污染物空间分布特征,其不确定性分析可为补充采样布点及精准评估提供参考。