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1.
Spatial structure analysis and kriging analysis have been identified to be useful tools in illustrating the spatial patterns of variables. Taihu Lake is one of the largest fresh water lakes in China, and has suffered serious eutrophication in recent years due to the rapid economic development and growing environmental pollution in the Taihu Catchment. In this paper, spatial structural analysis, kriging interpolation and eutrophication assessment were carried out for chlorophyll a in the lake. Studies show that spherical model could be applied to fit all experimental variograms. Positive nuggets were observed for three directions except NE–SW direction. The variograms show some anisotropy with anisotropic ratio falling within 1.76. The spatial structural patterns of chlorophyll a in the lake were affected by factors such as distribution of pollution sources, water flow and wind. Two-dimensional ordinary block kriging was applied for interpolation process. An eutrophication assessment map was also made based on a water-quality evaluation standard. Results show that the content of chlorophyll a in Taihu Lake was quite high. The whole lake has suffered serious eutrophication. However, the eutrophic situation varied in space. Higher contents of chlorophyll a appeared mainly in the northern part of the lake. 相似文献
2.
The use of quantitative data for constructing prognostic maps of the dynamics of ecosystem degradation and restoration by
nonlinear simulation methods is a topical field of landscape ecology. This method of dynamic cartography is based on fiberwise
comparison of data on the state of Chernye Zemli (the Kalmyk Republic, Russia) in different years and the detailed analysis
of the period on which the prognosis was based. For this purpose, materials of repeated aerial and satellite photography obtained
during a long period (1954–1993) were used. Comparison of maps characterizing the dynamics of Chernye Zemli between 1958 and
1993 allows prognostic electronic maps for the next 10–15 years (with a five-year interval) to be drawn and land prognosis
for the next 20–30 years (1998–2023) to be obtained.
Deceased 相似文献
3.
长三角典型区土壤重金属有效态的协同区域化分析、空间相关分析与空间主成分分析 总被引:11,自引:8,他引:3
以昆山市为典型区,采集了126个表层土壤样品,通过多元统计学、地统计学与GIS技术相结合,采用基于协同区域化理论的因子克立格法探讨了长三角多个土壤重金属有效态的区域分异,并在剖析不同空间尺度有效态重金属的空间结构特征基础上,应用空间相关分析和空间主成分分析来揭示引起这种分布格局的成因和污染来源,结果表明,昆山土壤有效态重金属服从正态或对数正态分布,变异系数较大,有效态Cd污染最重.重金属有效态在空间上可划分为块金尺度、小空间尺度(15 km左右)和大空间尺度(40 km左右),它可用3个尺度的实验(交叉)变异函数的协同区域化模型线性拟合.空间相关分析中,Cd和Zn在3个尺度中的相关性均极显著,且元素在小尺度和大尺度的相关性比块金尺度更强,大尺度的负相关特征较其它尺度明显.空间主成分分析表明,不同尺度的空间污染来源不同.重金属有效态第一、二主成分的空间分布格局结果表明重金属有效态含量与工业活动、污水灌溉和土壤性质密切相关. 相似文献
4.
Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods 总被引:4,自引:0,他引:4
Hernandez-Stefanoni JL Ponce-Hernandez R 《Environmental monitoring and assessment》2006,117(1-3):307-334
Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify
high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected
areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this
study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled
in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map
of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions,
kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the
procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries
between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity
over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior
information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators
due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used
as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class
kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the
most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations
of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional
role was found very useful in aiding decisions in conservation planning. 相似文献
5.
Yu-Pin Lin Bai-You Cheng Tsun-Kuo Chang 《Environmental pollution (Barking, Essex : 1987)》2010,158(1):235-244
This study identifies the natural background, anthropogenic background and distribution of contamination caused by heavy metal pollutants in soil in Chunghua County of central Taiwan by using a finite mixture distribution model (FMDM). The probabilities of contaminated area distribution are mapped using single-variable indicator kriging and multiple-variable indicator kriging (MVIK) with the FMDM cut-off values and regulation thresholds for heavy metals. FMDM results indicate that Cr, Cu, Ni and Zn can be individually fitted by a mixture model representing the background and contamination distributions of the four metals in soil. The FMDM cut-off values for contamination caused by the metals are close to the regulation thresholds, except for the cut-off value of Zn. The receiver operating characteristic (ROC) curve validates that indicator kriging and MVIK with FMDM cut-off values can reliably delineate heavy metals contamination, particularly for areas lacking background information and high heavy metal concentrations in soil. 相似文献
6.
Francisco Ferreira Hugo Tente Pedro Torres Sérgio Cardoso José M. Palma-Oliveira 《Environmental monitoring and assessment》2000,65(1-2):443-450
The environmental decision-making process is related with the interpretation of data both in spatial and temporal dimensions. This paper presents a methodology that integrates the time-space framework of air quality data to infer the temporal pattern and spatial variability that could be interpreted for environmental decision purposes. Variograms that accommodate time and space lags were used for the analysis and proved to be effective. Its environmental meaning, in particular its relationship with traffic patterns is discussed. Data from air quality monitoring stations located in the central part of Lisbon were used in this study. It describes a strategy to identify the type of vehicles responsible for certain pollutant levels, particularly for nitrogen oxides, and discusses the application of new air quality European legislation to the city of Lisbon, Portugal. 相似文献
7.
David C. Garen Gregory L. Johnson Clayton L. Hanson 《Journal of the American Water Resources Association》1994,30(3):481-491
ABSTRACT: A procedure using detrended kriging has been developed to calculate daily values of mean areal precipitation (MAP) for input to hydrologic models. The important features of this procedure that overcome weaknesses in existing MAP procedures are: (1) specific precipitation-elevation relationships are determined for each time period as opposed to using relationships based on climatological averages, (2) spatial variability is incorporated by estimating precipitation for each grid cell over a watershed, (3) the spatial correlation structure of precipitation is explicitly modeled, and (4) station weights for precipitation estimates are determined objectively and optimally. Detailed cross-validation testing of the procedure was done for the Reynolds Creek research watershed in southwestern Idaho. The procedure is suitable for use in operational streamflow forecasting. 相似文献
8.
For modeling spatial processes, we propose a rich parametric class of stationary range anisotropic covariance structures that, when applied in R2, greatly increases the scope of variogram contors. Geometric anisotropy, which provides the most common generalization of isotropy within stationarity, is a special case. Our class is built from monotonic isotropic correlation functions and special cases include the Matérn and the general exponential functions. As a result, our range anisotropic correlation specification can be attached to a second order stationary spatial process model, unlike ad hoc approaches to range anisotropy in the literature. We adopt a Bayesian perspective to obtain full inference and demonstrate how to fit the resulting model using sampling-based methods. In the presence of measurement error/microscale effect, we can obtain both the usual predictive as well as the noiseless predictive distribution. We analyze a data set of scallop catches under the general exponential range anisotropic model, withholding ten sites to compare the accuracy and precision of the standard and noiseless predictive distributions. 相似文献
9.
Frank C. Curriero Michael E. Hohn Andrew M. Liebhold Subhash R. Lele 《Environmental and Ecological Statistics》2002,9(1):89-110
Geostatistics is a set of statistical techniques that is increasingly used to characterize spatial dependence in spatially referenced ecological data. A common feature of geostatistics is predicting values at unsampled locations from nearby samples using the kriging algorithm. Modeling spatial dependence in sampled data is necessary before kriging and is usually accomplished with the variogram and its traditional estimator. Other types of estimators, known as non-ergodic estimators, have been used in ecological applications. Non-ergodic estimators were originally suggested as a method of choice when sampled data are preferentially located and exhibit a skewed frequency distribution. Preferentially located samples can occur, for example, when areas with high values are sampled more intensely than other areas. In earlier studies the visual appearance of variograms from traditional and non-ergodic estimators were compared. Here we evaluate the estimators' relative performance in prediction. We also show algebraically that a non-ergodic version of the variogram is equivalent to the traditional variogram estimator. Simulations, designed to investigate the effects of data skewness and preferential sampling on variogram estimation and kriging, showed the traditional variogram estimator outperforms the non-ergodic estimators under these conditions. We also analyzed data on carabid beetle abundance, which exhibited large-scale spatial variability (trend) and a skewed frequency distribution. Detrending data followed by robust estimation of the residual variogram is demonstrated to be a successful alternative to the non-ergodic approach. 相似文献
10.
地统计学在土壤重金属研究中的应用及展望 总被引:14,自引:0,他引:14
从采矿学与地质学研究中发展起来的地统计学是应用数理统计学的一个分支。与传统的统计学相比,地统计学可应用于土壤重金属研究中,能探索土壤重金属的空间分布特征及其变异规律。地统计学的基础理论与方法主要包括:区域化变量、半方差函数、克立格空间插值技术。半方差函数可以用来描述研究土壤重金属分布的空间相关性;而克立格插值可以对未采样区土壤重金属的含量进行无偏最优估计。在对地统计学理论进行简要阐述的基础上,回顾了近些年在土壤重金属研究的采样设计、空间结构分析、空间插值等方面的应用,并就其应用前景作了展望。 相似文献