estimation and mapping of forest resources are preconditions for management, planning and research. in this study, we applied kriging interpolation of geostatistics for estimation and mapping of forest stock at-tributes in a natural, uneven-aged, unmanaged forest in the caspian region of northern iran. the site of the study has an area of 516 ha and an elevation that ranges from 1100 to 1450 m ...

The work deals with development and application of Radial basis functions neural networks (RBFNN) for spatial predictions. Geostatistical tools for spatial correlation analysis (variography) are used to qualify and quantify the estimation results. Geostatistical analysis is performed on the residuals obtained at the training and test sample locations. Variogram of residuals explores spatial cor...

Estimation and mapping of forest resources are preconditions for management, planning and research. In this study, we applied kriging interpolation of geostatistics for estimation and mapping of forest stock at-tributes in a natural, uneven-aged, unmanaged forest in the Caspian region of northern Iran. The site of the study has an area of 516 ha and an elevation that ranges from 1100 to 1450 m ...

Traditional geostatistical estimation techniques have been used predominantly by the mining industry for ore reserve estimation. Determination of mineral reserve has posed considerable challenge to mining engineers due to the geological complexities of ore body formation. Extensive research over the years has resulted in the development of several state-of-the-art methods for predictive spatial...

nowadays, much attention has been paid on using geostatistical methods for estimation of spatial parameters, either using the variables of these parameters (kriging) or auxiliary variables (cokriging), in water and soil sciences. the quality of ground water for agriculture is very important; however, it is expensive and time consuming to measure parameters such as sar, na, ca, th, tds and ec. t...

Determination of Geostatistical Parameters Using Well Test Data — In this paper we describe a new method to obtain estimations of the geostatistical parameters (GPs) such as the correlation length, lc and the permeability variance, σln from well test data. In practical studies, the GPs are estimated using geological and petrophysical data, but often, these data are too scarce to give precise re...

This paper describes a geostatistical approach for environmental data modeling based on value descriptive analysis, variographic analysis, estimation method and validation. It shows an application related to atmospheric pollutant dispersion (ozone) detected by active biomonitoring in the province of Livorno (Italy). This work proposes a two-stage approach based on: the computation of an index o...

Modern geostatistical mapping methods are being applied to various types of data to produce more realistic and flexible characterizations of a natural random process. The Bayesian Maximum Entropy (BME) is a well-known geostatistical estimation method, especially for the use of soft knowledge as well as exact measurement data. Although development in geostatistical methods helps us to solve limi...