Use Of Geostatistical Methods Research Articles

Kriging approach for local height transformations

Abstract In the paper a transformation between two height datums (Kronstadt’60 and Kronstadt’86, the latter being a part of the present National Spatial Reference System in Poland) with the use of geostatistical method - kriging is presented. As the height differences between the two datums reveal visible trend a natural decision is to use the kind of kriging method that takes into account nonstationarity in the average behavior of the spatial process (height differences between the two datums). Hence, two methods were applied: hybrid technique (a method combining Trend Surface Analysis with ordinary kriging on least squares residuals) and universal kriging. The background of the two methods has been presented. The two methods were compared with respect to the prediction capabilities in a process of crossvalidation and additionally they were compared to the results obtained by applying a polynomial regression transformation model. The results obtained within this study prove that the structure hidden in the residual part of the model and used in kriging methods may improve prediction capabilities of the transformation model.

The Use of Mathematical Interpolation Modeling and Statistical Analysis to Explain the Spatial Variability of Annual Rainfall in the Moulouya Watershed, Morocco

The Use of Mathematical Interpolation Modeling and Statistical Analysis to Explain the Spatial Variability of Annual Rainfall in the Moulouya Watershed, Morocco The knowledge of spatial variability of rainfall is extremely important information for hydrologists and meteorologists. This variability is highly dependents on meteorological conditions and relief. The use of geostatistical methods in the study of the space variation of annual rainfall led to understand and explain some aspect of this variation and to calculate values of rainfall in unmeasured regions to best cover the entire study area. This study seeks to evaluate spatial interpolation techniques and understand the spatial variability of annual rainfall in Moulouya watershed, which is actually belonging to a national plan of water resources modeling. Rainfall records of 74 rain stations are used in this study covering an area of about 53,000 km2. Two types of kriging methods were used in this paper: simple Kriging and co-kriging.

PROVIDING A SUBSURFACE RESERVOIR QUALITY MAPS IN OIL FIELDS BY GEOSTATISTICAL METHODS

Under study reservoir oilfield is located south-west of Iran. This field is comprised of naturally fractured Asmari and Bangestan formation. Reservoir management and characteristic evaluation of this field requires good knowledge of reservoir rock and fluid properties. One of main methods to get such information is using known parameter and estimates this property in unknown area of reservoir by geostatistics and kriging method. In this research used the porosity parameter data from 36 oil wells that taken by well logging to estimate porosity parameter in unknown part of reservoir by geostatistics and kriging method. The porosity parameter had normal distribution. After surveyed the distribution of data varioghraphy was done and strength of structure was proved and kriging parameters including characteristic of search ellipse determined for estimation. Then porosity parameter was estimated with the use of geostatistical method in reservoir.

Interpolation of Mexican soil properties at a scale of 1:1,000,000

México maintains several databases with biotic or abiotic information that enable large scale-studies (for example, at a resolution of 1km2); unfortunately, there is no information at this resolution for soil properties. The goal of this paper was to generate a set of soil variables to address this absence. We evaluated 4400 soil samples taken on Mexican territory. The following nine soil properties were evaluated for each sample: Ca, K, Mg, Na, organic C, organic matter, electrical conductivity, sodium absorption ratio, and pH. With the use of geostatistical methods, a layer was generated for each soil property after six different semivariance models were evaluated. The kriging model (simple, ordinary, or universal) was selected as the best semivariance method with a 10-fold cross-validation approach. Exponential, pentaspherical, and spherical models were selected with ordinary and universal kriging methods to spatially predict the soil properties. Five classes for each soil map were generated. The nine soil properties were classified primarily as slightly low or medium according to their distribution throughout Mexican territory.

Simulation of urban development in the City of Rome: Framework, methodology, and problem solving

In Italy’s case, the implementation of the UrbanSIM model involved the territory of Rome, including the municipalities of Rome and Fiumicino. The main goal was to build scenarios regarding the future of economic deconcentration. Rome is the largest municipality in Europe, with an inhabited surface area only slightly smaller than that of Greater London and almost double that of the inner Paris suburbs (the Petite Couronne). The spatial distribution of buildings within the municipality is distinctive. Unbuilt areas comprise 73 percent of the territory. These voids are often farmland (paradoxically, Rome is the largest rural municipality in Italy) or areas with high environmental, historic or cultural value. Fiumicino, previously part of the municipality of Rome, became an independent municipality in 1991. Its autonomy, made all the more significant because Fiumicino hosts the international airport, marked the start of an extensive process of economic deconcentration along the route connecting Rome to the airport. In Italy’s case, the implementation of the UrbanSIM model posed several challenges, notably the availability, homogeneity and completeness of data. This paper uses four specific cases (land use, travel times, accessibility, and residential land values) to propose a general methodology to solve problems related to missing or non-homogeneous data. For the land use, we simply combine two different land use data sources, while for accessibility and travel time data, we propose the use of geostatistical methods in order to estimate missing and unavailable data, calculating also the accuracy of the predictions. For the residential land values, which are discrete data, we suggest the use of deterministic interpolation techniques. While it has not yet been possible to implement the calibration stage, some simulation outputs are presented.

Geostatistical Simulation for the Assessment of Regional Soil Pollution. 区域土壤污染评估的地统计模拟方法

Regional scale inventories of heavy metal concentrations in soil increasingly are being done to evaluate their global patterns of variation. Sometimes these global pattern evaluations reveal information that is not identified by more detailed studies. Geostatistical methods, such as stochastic simulation, have not yet been used routinely for this purpose in spite of their potential. To investigate such a use of geostatistical methods, we analyzed a data set of 14,674 copper and 12,441 cadmium observations in the topsoil of Flanders, Belgium, covering 13,522 km2. Outliers were identified and removed, and the distributions were spatially declustered. Copper was analyzed using sequential Gaussian simulation, whereas for cadmium we used sequential indicator simulation because of the large proportion (43%) of censored data. We complemented maps of the estimated values with maps of the probability of exceeding a critical sanitation threshold for agricultural land use. These sets of maps allowed the identification of regional patterns of increased metal concentrations and provided insight into their potential causes. Mostly areas with known industrial activities (such as lead and zinc smelters) could be delineated, but the effects of shells fired during the First World War were also identified.

Urban green and its relation with air pollution: ecological studies in the Metropolitan area of Rome

Tropospheric ozone (O3) and Particulate Matter (PM) have become a major concern in mostEuropean cities. In particular, in Italy the O3 concentrations exceed the limits established for the protection ofboth human health and vegetation. More integrative studies are revealing that urban trees could concretelyhelp in improving air quality, not only because of their well known aesthetic and recreational benefit, but alsofor their capability to reduce air temperature and to remove air pollutants. This reduction takes place bothdirectly, by dry deposition to plant surfaces and uptake through stomata, and indirectly, by mitigation of theurban heat island intensity by canopy transpiration and building shading, that lowers the activity of chemicalreactions that led to the formation of photochemical pollutants in air. This is of particular importanceespecially for those cities located in the Mediterranean Basin, whose urban vegetation is often characterizedby VOC-emitting species that can contribute significantly to the O3 formation and destruction dynamics. Theaim of this paper is to present a short review of ecological research performed on vegetation of themetropolitan area of Rome, at different spatial and temporal scale, in order to evaluate the functional role ofurban green to monitor and improve urban air quality. In the frame of the project HEREPLUS (EU FP7), all ofthis information, opportunely integrated with climatic and pollutant data, will be implemented in a GIS and,by the use of geo-statistical methods, the ameliorating effect of urban vegetation will be quantified andmapped.

Using decision trees to predict benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea

In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0-20, 20-63, 63-2,000 mu) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.

Temporal and spatial dynamical simulation of groundwater characteristics in Minqin Oasis

Application scope of geostatistics has been gradually extended from original geologic field to soil science and ecological field, etc. and its successful application results have been widely demonstrated. But little information is reported as to the direct use of geostatistical method to work out the distribution map of groundwater characteristics. In this paper the semivariogram of geostatistics, in combination with GIS, was used to quantitatively study the spatial variation characteristics of groundwater table depth and mineralization degree and their relation to the landuse changes. F test of the used spherical model reached a very significant level, and the theoretical model can well reflect the spatial structural characteristics of groundwater table depth and mineralization degree and achieve an ideal result. This shows that the application of the method in the dynamical simulation of groundwater is feasible. And this paper also provides useful reference for the application of geostatistics in the study of the dynamical variations of groundwater resources in the oasis.

Use of chemometric and geostatistical methods to evaluate pesticide pollution in the irrigation and drainage channels of the Ebro river delta during the rice-growing season

Data sets obtained from quantitative analysis of seventeen pesticides in water samples from a network of irrigation and drainage channels in the Ebro river delta (Catalonia, NE Spain) have been analysed by chemometric and geostatistical methods. Samples were taken at fourteen locations during the main rice-growing season, from May to August 2005. Principal-component analysis enabled investigation of the spatial and temporal distribution of the main pollution patterns caused by application of pesticides in the region under study. A first pesticide-contamination pattern from the Ebro river was differentiated from a second more specific pattern from the water-drainage channels of the delta, collected from the rice fields. The seasonal peak in this more specific rice pesticide source was observed in July. Coupling the results from chemometric data analysis with use of geostatistical methods was shown to be a useful procedure for discovery of the most significant spatial and monthly variations of the main pesticide-contamination patterns, taking into account the particular geographical structure of the area under study.

The use of geostatistics in relating soil moisture to RADARSAT-1 SAR data obtained over the Great Basin, Nevada, USA

Block kriging is applied to geographically register digital images from the RADARSAT-1 satellite to soil moisture samples. Both satellite and soil moisture data are interpolated in this process to obtain precise registration. Median and adaptive Lee filtering of images are also used to correlate pixel values with soil moisture. A case study is presented using a playa in the western Great Basin, Nevada, of North America. A statistically significant correlation is found between interpolated RADARSAT-1 digital numbers and interpolated soil moisture. Results indicate that RADARSAT-1 is sensitive to median soil moisture levels; however, filtering does not significantly improve this sensitivity. The study results indicate the ability of synthetic aperture radar to delineate and map temporal soil moisture variability with the use of geostatistical methods to interpolate values over pixel areas.

A community-based assessment of learning disabilities using environmental and contextual risk factors

Childhood placement in learning disability (LD) programs in the USA has tripled over the last few decades to 6% of all children enrolled in the public schools today. The revision of educational laws to improve LD testing and reporting guidelines has been credited for these trends. However, some researchers also believe that the increase in LD incidence may be due, in part, to chronic low level exposure to toxicants such as lead, heavy metals, solvents and others chemicals in the physical environment. This study employs the use of geo-statistical methods to explore the potential linkages between these pollution sources and the prevalence rates of LD within an urbanized environment, in the USA. The role of contextual factors such as housing quality, poverty, low parental educational achievement, and other disadvantages are also examined. Using primary data on childhood disabilities for 1997, the LD cases were queried and analyzed to identify the spatial clusters within the community. The neighborhoods within the LD clusters were then compared to other areas in the community on the basis of the environmental and contextual risk factors. The results confirmed that areas of high risk for LD were strongly associated with historically significant sources of lead toxicity and air pollution facilities. Among the socio-economic indicators, the high-risk neighborhoods were characterized by multiple/subdivided housing units, poverty, higher percentage of residents on public assistance and lower adult educational attainment. Taken together, these results suggest the need for a more inclusive multi-disciplinary research on LD that extends beyond the classroom context to the neighborhoods and communities in which these children reside.

Assessing Environmental Exposure to PCBs among Mohawks at Akwesasne through the Use of Geostatistical Methods

The Mohawk Nation at Akwesasne is a Native American community located along the St. Lawrence River in New York State, Ontario, and Quebec. One component of a multiphase human health study was to assess the impact of different pathways of human exposure resulting from the off-site migration of polychlorinated biphenyl (PCB) contamination in this area. This paper illustrates how mapped residential information and environmental sampling data can be united to assist in exposure assessment for epidemiologic studies using geographic information system (GIS) technology and statistical methods. A proportional sampling scheme was developed to collect 119 surface soils. Using a method of cross validation, the average estimated error can be computed and the best estimator can be selected. Seven spatial methods were examined to estimate surface soil PCB concentrations; the lowest relative mean error was 0.42% for Inverse 3 nearest neighbor weighted according to the inverse distance, and the highest relative mean error was 4.4% for Voronoi polygons. Residual plots indicated that all methods performed well except near some of the sampling points that formed the outer boundaries of the sampling distribution.

Use of geostatistical methods for the survey of lateritic gravels (In French)

Use of geostatistical methods for the survey of lateritic gravels (In French)