Many state and national geological surveys produce map products from surficial and bedrock geologic maps as a value-added deliverable for a variety of stakeholders. Improvements in powerful geostatistical exploratory tools and robust three-dimensional capabilities within geographic information systems (GIS) can facilitate the production of derivative products. In addition to providing access to...

The IsoMAP uses the multiple linear regression and geostatistical methods to analyze isotope data. Suppose the response variable Y (s) and the vector of independent variable x(s) are observed at a finite number of sites s1, · · · , sn. The multiple linear regression method assumes Y (s) and Y (s′) are independent but the geostatistical method assume they are not. In the following, we will first...

INTRODUCTION A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. METHODS A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. RESULTS Parameters Range...

Spatial dependence exists when the variation between observations is dependent on spatial location. In the present study, geostatistical methods were used to examine spatial dependence in adolescents’ perceptions of their neighborhoods: whether adolescents living in close proximity perceived their neighborhoods more similarly than adolescents living further apart. Participants included 343 adol...

We consider the problem of model selection for geospatial data. Spatial correlation is often ignored in the selection of explanatory variables, and this can influence model selection results. For example, the importance of particular explanatory variables may not be apparent when spatial correlation is ignored. To address this problem, we consider the Akaike Information Criterion (AIC) as appli...

[1] We investigate, through numerical experiments, the viability of three-dimensional transient hydraulic tomography (3DTHT) for identifying the spatial distribution of groundwater flow parameters (primarily, hydraulic conductivity K) in permeable, unconfined aquifers. To invert the large amount of transient data collected from 3DTHT surveys, we utilize an iterative geostatistical inversion str...

An accurate estimation of soil organic matter (SOM) content for spatial non-point prediction is an important driving force for the agricultural carbon cycle and sustainable productivity. This study proposed a hybrid geostatistical method of extreme learning machine-ordinary kriging (ELMOK), to predict the spatial variability of the SOM content. To assess the feasibility of ELMOK, a case study w...

Recent research has suggested that the geostatistical structure of ground-penetrating radar data may be representative of the spatial structure of hydraulic properties. However, radar images of the subsurface can change drastically with application of signal processing or by changing the signal frequency. We perform geostatistical analyses of surface radar reflection profiles in order to invest...

Accurate prediction of petroleum reservoir performance requires reliable models of the often complex reservoir heterogeneity. Geostatistical simulation techniques generate multiple realizations of the reservoir model, all equally likely to be drawn. Traditional to geostatistics, geological continuity is represented through the variogram. The variogram is limited in describing complex geological...