This article gives a brief overview of classical spatial statistics. Three main types of spatial data are considered: geostatistical data, lattice data, and spatial point patterns. Modeling themes common to all three data types are emphasized. In addition, some basic structural identification procedures for each data type are described. Finally, maximum likelihood estimation and spatial predict...

Geostatistical modeling methods for deep-water depositional systems, which provide a framework to characterize spatial uncertainty, have generally focused on channel-levee-overbank-lobe models. However, these models do not fit all deepwater depositional settings. For example, irregular surface topography of subaqueous mass-transport-deposits (MTDs) played a primary role in controlling the depos...

[1] Interpolation and inverse modeling problems are ubiquitous in environmental sciences. In many applications, the parameters being estimated or mapped have physical constraints, such as nonnegativity (e.g. concentration, hydraulic conductivity), solubility limits, censored data (e.g. due to dry wells or detection limits), and other physical boundaries or missing data. Geostatistical interpola...

Accurate knowledge of spatial distribution of soil physical and chemical properties is needed for suitable management and proper use of rangelands in Masileh plain, Qom, Iran. In present study, for the spatial modeling of chemical and physical parameters such as sodium (Na), calcium (Ca), soluble potassium (K), magnesium (Mg), Electrical Conductivity (EC), Saturation Percentage (SP%), silt, cla...

This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data were inverted in 2D along several profiles across the main favorable zones of Cu-bearing mine...

The objective of this paper is to show that the structure of the spatiotemporal continuum has important implications in practical stochastic hydrology (e.g., geostatistical analysis of hydrologic sites) and is not merely an abstract mathematical concept. We propose that the concept of physical geometry as a spatiotemporal continuum with properties that are empirically de®ned is important in hyd...