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1.
Bivariate and multivariate statistical analyses were used to predict the spatial distribution of landslides in the Cuyahoga River watershed, northeastern Ohio, U.S.A. The relationship between landslides and various instability factors contributing to their occurrence was evaluated using a Geographic Information System (GIS) based investigation. A landslide inventory map was prepared using landslide locations identified from aerial photographs, field checks, and existing literature. Instability factors such as slope angle, soil type, soil erodibility, soil liquidity index, landcover pattern, precipitation, and proximity to stream, responsible for the occurrence of landslides, were imported as raster data layers in ArcGIS, and ranked using a numerical scale corresponding to the physical conditions of the region. In order to investigate the role of each instability factor in controlling the spatial distribution of landslides, both bivariate and multivariate models were used to analyze the digital dataset. The logistic regression approach was used in the multivariate model analysis. Both models helped produce landslide susceptibility maps and the suitability of each model was evaluated by the area under the curve method, and by comparing the maps with the known landslide locations. The multivariate logistic regression model was found to be the better model in predicting landslide susceptibility of this area. The logistic regression model produced a landslide susceptibility map at a scale of 1:24,000 that classified susceptibility into four categories: low, moderate, high, and very high. The results also indicated that slope angle, proximity to stream, soil erodibility, and soil type were statistically significant in controlling the slope movement.  相似文献   

2.
This paper describes a geostatistical method, known as factorial kriging analysis, which is well suited for analyzing multivariate spatial information. The method involves multivariate variogram modeling, principal component analysis, and cokriging. It uses several separate correlation structures, each corresponding to a specific spatial scale, and yields a set of regionalized factors summarizing the main features of the data for each spatial scale. This method is applied to an area of high manganese-ore mining activity in Amapá State, North Brazil. Two scales of spatial variation (0.33 and 2.0 km) are identified and interpreted. The results indicate that, for the short-range structure, manganese, arsenic, iron, and cadmium are associated with human activities due to the mining work, while for the long-range structure, the high aluminum, selenium, copper, and lead concentrations, seem to be related to the natural environment. At each scale, the correlation structure is analyzed, and regionalized factors are estimated by cokriging and then mapped.  相似文献   

3.
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4.
Statistical models are one of the most preferred methods among many landslide susceptibility assessment methods. As landslide occurrences and influencing factors have spatial variations, global models like neural network or logistic regression (LR) ignore spatial dependence or autocorrelation characteristics of data between the observations in susceptibility assessment. However, to assess the probability of landslide within a specified period of time and within a given area, it is important to understand the spatial correlation between landslide occurrences and influencing factors. By including these relations, the predictive ability of the developed model increases. In this respect, spatial regression (SR) and geographically weighted regression (GWR) techniques, which consider spatial variability in the parameters, are proposed in this study for landslide hazard assessment to provide better realistic representations of landslide susceptibility. The proposed model was implemented to a case study area from More and Romsdal region of Norway. Topographic (morphometric) parameters (slope angle, slope aspect, curvature, plan, and profile curvatures), geological parameters (geological formations, tectonic uplift, and lineaments), land cover parameter (vegetation coverage), and triggering factor (precipitation) were considered as landslide influencing factors. These influencing factors together with past rock avalanche inventory in the study region were considered to obtain landslide susceptibility maps by using SR and LR models. The comparisons of susceptibility maps obtained from SR and LR show that SR models have higher predictive performance. In addition, the performances of SR and LR models at the local scale were investigated by finding the differences between GWR and SR and GWR and LR maps. These maps which can be named as comparison maps help to understand how the models estimate the coefficients at local scale. In this way, the regions where SR and LR models over or under estimate the landslide hazard potential were identified.  相似文献   

5.
This study uses Ordinary Kriging (OK), Sequential Gaussian Simulation (SGS) and Simulated Annealing Simulation (SAS) to relocate the completely heterotopic dataset from the locations of the Standardized Satellite Oriented Control Point System (SSOCPS) stations to the Groundwater Monitoring Networks (GMNS) stations and factorial kriging to analyze and map relationships among seven variables, including the hydraulic conductivities of three aquifers, the vertical displacements of the ground and groundwater level changes in the wells of three aquifers, and also to delineate the anomalies of multi-scale spatial variation of hydrogeological properties associated with the ChiChi earthquake, measuring 7.3 on the Richter scale, in the ChouShui River alluvial fan in Taiwan. In this study, the anomalies of spatial variation of hydrogeological properties associated with the earthquake are illustrated at micro, local and regional scales of 9, 12 and 36 km, respectively. In the study area, regionalization components associated with variation at local and regional scales are obtained and mapped by factorial kriging. Factorial Kriging Analysis (FKA) also demonstrated that the main effects of the ChiChi earthquake on the spatial variations of groundwater hydrological changes include porous media compression at micro scale, hydrogeological heterogeneousness of the sediments within the aquifer at local scale and the cyclic loading of deviatoric stress at regional scale. Finally, maps of spatial variations of regional components fully depicted all of the anomalies of spatial variation of hydrogeological changes due to the ChiChi earthquake and can be used to identify, confirm and monitor the hydrogeological properties in this study area.  相似文献   

6.
This paper extends the concept of dispersion variance to the multivariate case where the change of support affects dispersion covariances and the matrix of correlation between attributes. This leads to a concept of correlation between attributes as a function of sample supports and size of the physical domain. Decomposition of dispersion covariances into the spatial scales of variability provides a tool for computing the contribution to variability from different spatial components. Coregionalized dispersion covariances and elementary dispersion variances are defined for each multivariate spatial scale of variability. This allows the computation of dispersion covariances and correlation between attributes without integrating the cross-variograms. A correlation matrix, for a second-order stationary field with point support and infinite domain, converges toward constant correlation coefficients. The regionalized correlation coefficients for each spatial scale of variability, and the cases where the intrinsic correlation hypothesis holds are found independent of support and size of domain. This approach opens possibilities for multivariate geostatistics with data taken at different support. Two numerical examples from soil textural data demonstrate the change of correlation matrix with the size of the domain. In general, correlation between attributes is extended from the classic Pearson correlation coefficient based on independent samples to a most general approach for dependent samples taken with different support in a limited domain.  相似文献   

7.
Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data. However, these classical multivariate methods deal with two-way matrices, usually parameters × sites or parameters × time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters × sites × time. Three-way matrices, such as the one proposed here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach is the use of Partial Triadic Analysis (PTA). Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears to be a new promising statistical instrument for hydrogeologists, for characterization of temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for (1) identifying a common multivariate spatial structure, (2) untapping the different hydrochemical patterns and explaining their controlling factors and (3) analyzing the temporal variability of this structure and grasping hydrochemical changes.  相似文献   

8.
勘查地球化学找矿工作的重点在于正确解译地球化学数据,以便从冗杂的地质信息中精准提取与成矿有关的异常信息,指导找矿研究。然而,地球化学数据属于成分数据,具有闭合效应,只有对数据进行正确的预处理才能应用多元统计分析方法,还原元素真实的空间分布。本文在阿舍勒铜锌矿区外围南侧区域共收集1009件地表原生晕样品,对样品中的13种微量元素进行测试,并对原始数据、对数及ilr变换后的数据进行EDA分析,对比数据空间分布及内部结构特征。运用(稳健)主成分分析,结合成分数据双标图及第一主成分点位图,解译三类数据指示的元素组合与成矿信息之间的关联。随后运用多重分形滤波技术,对以ilr变换为基础的稳健主成分得分数据分解元素组合异常和背景分布特征。结果表明:①经过对数及ilr变换后的数据相比原始数据空间尺度更均匀,数据近似正态分布;②三类数据双标图表明,仅ilr变换后的数据消除了“闭合效应”,且其第一主成分元素分组揭示了研究区铜矿化与铅锌多金属矿化组合;以对数变换与ilr变换为基础的第一主成分点位图表明,后者主成分得分异常能够较好指示研究区地质找矿信息;③结合研究区地质找矿信息、元素组合异常及背景空间分布特征,最终圈定3个有利找矿靶区。  相似文献   

9.
In Sahel-Doukkala, which is characterized by lands of a relatively low relief, global DEMs and DEMs generated from digitizing topographic maps, have been the primary source of several multidisciplinary researches. Although these products present a great value of the conducted research, the level of the given accuracy is not sufficient enough for detailed geospatial analysis. These requirements led us to generate a high-resolution DEM as an alternative of available global DEMs or/and DEMs generated from digitizing topographic maps. In this study, we present a workflow to extract high-resolution DEM at 5 m resolution and derived orthoimages from ALOS-PRISM data over Sahel-Doukkala, through photogrammetric techniques, using a variation of GCPs obtained from topographic maps at scale 1:25,000. The accuracy of the generated products is reported according to NSSDA standards. Using ten GCPs, a PRISM-DEM with 3.88 m vertical accuracy and 11.60 m horizontal accuracy, both at 95% confidence level is obtained. This DEM will serve as base dataset for further detailed geospatial analysis and mapping applications in order to identify the relationship between surface parameters and groundwater, and also to assess and understand all factors influencing the development of karst landscapes and consequently subsurface stability in the investigated area.  相似文献   

10.

Exploration for diamond-bearing kimberlites in the Chidliak project area by Peregrine Diamonds has generated a grid-like till sampling pattern across four discrete areas of interest totalling 402 km2 that is densely populated with research-grade compositional data for 10,743 mantle-derived Cr-pyrope garnets. The available dataset is well suited to statistical analysis, in part due to the relatively unbiased spatial coverage. Previous workers showed empirically that the TiO2 and Mn thermometry (Ti-TMn) attributes of Cr-pyrope populations at the Chidliak project may serve as source-specific “fingerprints”. In this work, we employ a simplified version of the multivariate Mahalanobis distance technique to formally examine the variability of, and differences between, Ti-TMn attributes of Cr-pyrope subpopulations recovered from a Laurentide-age glaciated terrain that also contains 30 known kimberlites within the four areas of interest. We show the simplified Mahalanobis distance approach enables accurate discrimination of Cr-pyrope subpopulations with subtly to distinctly different Ti-TMn attributes, and permits proper demarcation of their respective kimberlite source(s), specifically in areas with straightforward glacial histories. Redistribution and blending of Cr-pyrope subpopulations from known kimberlite sources is also observed, and typifies areas at Chidliak with complex late-glacial histories. Our results support <1 km horizontal scale subtle to obvious variability in the proportions of TiO2-rich and high-temperature (> 1100 °C) Cr-pyropes between closely spaced kimberlite source(s) and also between physically adjacent magma batches within single kimberlite pipes. The local scale variability is attributed to protokimberlite fluid or melt interacting with, and metasomatizing discrete conduits within, the ambient diamond-facies peridotitic mantle at times closely preceding eruption of kimberlite magma batches at Chidliak.

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11.
《Applied Geochemistry》2005,20(2):341-352
Dealing with geochemical data also means coping with their underlying limitations that are related to sampling, analytical techniques, and other characteristics of the data. This paper discusses the issue of data cleaning, using a regional geochemical dataset of 6 heavy metals in glacial till. Interactive data manipulation techniques provided in the freeware visualization system XmdvTool were used for exploring both metal concentrations reported as under the detection limit, and high or extreme values (outliers) in the dataset. The proposed integrated visual evaluation (IVE) approach for selective removal of outliers outperformed simple removal of the highest concentrations of metals, showing that existing spatial multi-element fingerprints in data could be recognized and preserved by IVE. The uniqueness of visualization is in simultaneous display of both multivariate and spatial information. Being simple and interactive, integrated visual evaluation can be recommended as a valuable complementary tool in cleaning and analysing multi-element geochemical data.  相似文献   

12.
Maps showing the potential for soil erosion at 1:100,000 scale are produced in a study area within Lebanon that can be used for evaluating erosion of Mediterranean karstic terrain with two different sets of impact factors built into an erosion model. The first set of factors is: soil erodibility, morphology, land cover/use and rainfall erosivity. The second is obtained by the first adding a fifth factor, rock infiltration. High infiltration can reflect high recharge, therefore decreasing the potential of surface runoff and hence the quantity of transported materials. Infiltration is derived as a function of lithology, lineament density, karstification and drainage density, all of which can be easily extracted from satellite imagery. The influence of these factors is assessed by a weight/rate approach sharing similarities between quantitative and qualitative methods and depending on pair-wise comparison matrix.The main outcome was the production of factorial maps and erosion susceptibility maps (scale 1:100,000). Spatial and attribute comparison of erosion maps indicates that the model that includes a measure of rock infiltration better represents erosion potential. Field investigation of rills and gullies shows 87.5% precision of the model with rock infiltration. This is 17.5% greater than the precision of the model without rock infiltration. These results indicate the necessity and importance of integrating information on infiltration of rock outcrops to assess soil erosion in Mediterranean karst landscapes.  相似文献   

13.
Surface map of soil properties plays an important role in various applications in a watershed. Ordinary kriging (OK) and regression kriging (RK) are conventionally used to prepare these surface maps but generally need large number of regularly girded soil samples. In this context, REML-EBLUP (REsidual Maximum Likelihood estimation of semivariogram parameters followed by Empirical Best Linear Unbiased Prediction) shown capable but not fully tested in a watershed scale. In this study, REML-EBLUP approach was applied to prepare surface maps of several soil properties in a hilly watershed of Eastern India and the performance was compared with conventionally used spatial interpolation methods: OK and RK. Evaluation of these three spatial interpolation methods through root-mean-squared residuals (RMSR) and mean squared deviation ratio (MSDR) showed better performance of REML-EBLUP over the other methods. Reduction in sample size through random selection of sampling points from full dataset also resulted in better performance of REML-EBLUP over OK and RK approach. The detailed investigation on effect of sample number on performance of spatial interpolation methods concluded that a minimum sampling density of 4/km2 may successfully be adopted for spatial prediction of soil properties in a watershed scale using the REML-EBLUP approach.  相似文献   

14.
Soil salinization is a serious environmental problem in the world, especially in arid and semi-arid regions. Therefore, estimating spatial variability of soil salinity plays an important role in environmental sciences. Aiming at the problem of soil salinization inside an oasis, a case study was carried out at the Sangong River catchment in Xinjiang province, northwest China. Methods of classical statistics, geostatistics, remote sensing (RS) and geographic information system (GIS) were applied to estimate the spatial variability of soil salt content in the topsoil (0–20 cm) and its relationship with landscape structure at catchment scale. The objective of this study was to provide a scientific basis to understand the heterogeneous of spatial distribution of soil salt content at a large scale. The results revealed that (1) elevation of landform was a key factor for soil salt content’s spatial variability, and soil salt content had a strong spatial autocorrelation, which was mainly induced by structural factors. (2) Mapping of soil salt content by Kriging and comparing it with landscape maps showed that area of soil salinization in old oasis was smaller than that in new oasis, and degree of soil salinization in old oasis was also lower than that in the new one. Among all landscapes, cropland was mostly affected by salinity, with 38.8% of the cropland in new oasis moderately affected by soil salinity, and 8.54% in old oasis.  相似文献   

15.
《Applied Geochemistry》2000,15(7):1053-1067
This study examines the spatial variability of the factors obtained from the application of correspondence analysis to a hydrogeochemical data set. The goal was to synthesize the hydrogeochemical information using this multivariate statistical technique, by setting a series of factors which clarified the main properties of one aquifer. Then, a geostatistical framework to obtain a probabilistic assessment of groundwater quality was established. Experimental and theoretical semivariograms of the selected factors, considered as regionalized variables, were computed. These variographic information and factor values in the experimental sites were used in the ordinary kriging, which provides unbiased and linear estimates of the regionalized variables. These estimates were used to compile maps of the chosen factors, which explain their spatial distribution.The selected case study was the alluvial aquifer of Alto Guadalentı́n which is situated in southeast Spain, in the Internal Zones of Betic Cordilleras. These waters are chiefly SO4 and Cl types, but HCO3 facies are common in the central sector of the basin. High temperature, acid pH, problems of overexploitation and pollution by CO2-gas characterise these waters. Available groundwater quality monitoring data were used to calibrate the numerical model. The present study focused on setting the main physical and chemical attributes and establishing the spatial pattern of groundwater quality and the temporal changes in this pattern.  相似文献   

16.
This study explores the water quality status and pollution sources in Ghrib Dam, Algeria. It allows us to obtain more accurate information on water quality by applying a series of multivariate statistical techniques, including principal component analysis (PCA)/factor analysis (FA), hierarchical cluster analysis (CA), and multiple regression analysis (MRA). On 19 physicochemical parameters dataset over 5 years and from 6 different sites located in and around the lake. One-way analysis of variance (ANOVA) was used to investigate the statistically considerable spatial and seasonal differences. The results of ANOVA suggest that there exist a statistically significant temporal variation in the water quality of the dam for all parameters. On the other hand, only organic matter has a statistically significant spatial variation. In the multiple linear models, an association between organic and inorganic parameters was found; their origin comes from the mechanical erosion process of agricultural lands in the watershed. The PCA/FA identifies five dominant factors as responsible of the data structure, explaining more than 94.96% of the total variance in the water quality dataset. This suggests that the variations in water compounds’ concentration are mainly related to the multiple anthropogenic activities, as well as natural processes. The results of cluster analysis demonstrate that the sampling stations were divided in two similar groups, which indicates spatial homogeneity. While seasonal grouping has showed that the source of pollution was related to the level of runoff in the seasons.  相似文献   

17.
An air photographic mosaic covering an area of 44.5×10 5 m2 was subdivided into 741 rectangular cells (60×100 m). Pattern frequency, center relief, shape, and wedge image clarity were tabulated using three states for each character on a nominal scale. These state variables were converted to an interval scale by the application of a spatial smoothing filter. The new values were subjected to a principal components analysis which indicated that a parsimonious classification of pattern spatial variation could be constructed by equally weighting the first three nominal variables (frequency, relief, shape). The maps derived from this scheme indicate the areas on the tundra surface where polygon evolution may be occurring at the present time.  相似文献   

18.
Water recharge from land surfaces into subsurface media is an essential element in the hydrologic cycle. For a small-scale assessment, experimental approaches are usually followed, however, on a regional scale, this assessment needs to be made into a comprehensive picture where spatial data of the different contributing factors are treated. The case of Occidental Lebanon, with an area of around 5,000 km2, was studied by the integration of all factors influencing this hydrologic process. Contributing factors are: lineaments and drainage frequency density, lithologic character, karstic domains and land cover/land use. The determination of these factors was carried out mainly by the application of remote sensing. Satellite images (Landsat 7 ETM &; SPOT) and aerial photos were subjected to several treatment processes using a miscellany of software, mainly ERDAS Imagine and ESRI’s Arc View software. Furthermore, exogenetic data, such as topographic and geologic maps, were utilized. The extracted information for these factors was plotted on maps. The integration of the maps in a GIS allowed deciding their interactive effects. However, each factor had its own degree of effect, i.e., weight, which was also determined in this study. This study is an approach to better estimate and provide qualitative assessments of recharge potential (RP). The resultant map shows the highest recharge potentials towards the elevated regions where karstification is well development. It was found that around 57% of the study area is terrain with very high to high recharge rate values, which a considerable amount of precipitated water is allowed to percolate into subsurface rocks.  相似文献   

19.
Sinkholes usually have a higher probability of occurrence and a greater genetic diversity in evaporite terrains than in carbonate karst areas. This is because evaporites have a higher solubility and, commonly, a lower mechanical strength. Subsidence damage resulting from evaporite dissolution generates substantial losses throughout the world, but the causes are only well understood in a few areas. To deal with these hazards, a phased approach is needed for sinkhole identification, investigation, prediction, and mitigation. Identification techniques include field surveys and geomorphological mapping combined with accounts from local people and historical sources. Detailed sinkhole maps can be constructed from sequential historical maps, recent topographical maps, and digital elevation models (DEMs) complemented with building-damage surveying, remote sensing, and high-resolution geodetic surveys. On a more detailed level, information from exposed paleosubsidence features (paleokarst), speleological explorations, geophysical investigations, trenching, dating techniques, and boreholes may help in investigating dissolution and subsidence features. Information on the hydrogeological pathways including caves, springs, and swallow holes are particularly important especially when corroborated by tracer tests. These diverse data sources make a valuable database—the karst inventory. From this dataset, sinkhole susceptibility zonations (relative probability) may be produced based on the spatial distribution of the features and good knowledge of the local geology. Sinkhole distribution can be investigated by spatial distribution analysis techniques including studies of preferential elongation, alignment, and nearest neighbor analysis. More objective susceptibility models may be obtained by analyzing the statistical relationships between the known sinkholes and the conditioning factors. Chronological information on sinkhole formation is required to estimate the probability of occurrence of sinkholes (number of sinkholes/km2 year). Such spatial and temporal predictions, frequently derived from limited records and based on the assumption that past sinkhole activity may be extrapolated to the future, are non-corroborated hypotheses. Validation methods allow us to assess the predictive capability of the susceptibility maps and to transform them into probability maps. Avoiding the most hazardous areas by preventive planning is the safest strategy for development in sinkhole-prone areas. Corrective measures could be applied to reduce the dissolution activity and subsidence processes. A more practical solution for safe development is to reduce the vulnerability of the structures by using subsidence-proof designs.  相似文献   

20.
《Applied Geochemistry》2004,19(4):623-631
This study concerns the application of multiple correspondence analysis and factorial kriging analysis to soil data, and aims to identify spatial patterns and superficial soil anomalies of the Au and Ag deposit at Marrancos, Vila Verde. The mineral deposit can be described as a quartz auriferous shear-zone, consisting of a quartz breccia of tectonic origin hosted by metamorphic rocks (hornfels). Gold is associated with arsenopyrite and pyrite, and Ag with galena and galenobismuthite. A total of 286 soil samples were analysed for Fe, Cu, Zn, Pb, Co, Ni, Mn, Ag and Bi by atomic absorption spectrometry, As, Se, Te and Sb by atomic absorption spectrometry–hydride generation system and Au by inductively coupled plasma–atomic emission spectroscopy after extraction of the metal by an organic solvent (methyl-isobutylketone). The methodology used included (a) multiple correspondence analysis applied to soil data to obtain some factors that summarize geochemical information, (b) a structural analysis (variography) in order to account for spatial variability of these factors, and (c) factorial kriging analysis used to split these factors into their spatial components. This methodology allowed an efficient multi-element characterization of the spatial patterns as well as the identification and interpretation of significant anomalies, not always associated to Au-bearing geological structures.  相似文献   

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