Abstract In mining projects, the confidence in an estimate is associated with quantity and quality of available information. Thus, closer data to targeted location, smaller error estimated value. advanced stages a project (i.e. pre-feasibility feasibility phases), it usual take samples derived from drillings. Since sampling chemical analysis involve high costs, essential that these costs contri...

The paper presents some contemporary approaches to the spatial environmental data analysis, processing and presentation. The main topics are concentrated on the decision–oriented problems of environmental and pollution spatial data mining and modelling: valorisation and representativity of data with the help of exploratory data analysis, topological, statistical and fractal measures of monitori...

Purpose. This paper aims to estimate phosphate ore grade in the Abu Tartur area, Western Desert, Egypt, using four Machine Learning Algorithms (MLA), Geostatistical Techniques (variogram and kriging models), GIS-analysis. Methods. Four machine-learning techniques include Optimizable Decision Tree (ODT), Support Vector (OSVM), Gaussian Process Regression (OGPR), Artificial Neural Network (ANN) a...

The quality properties of andesite (Unit Volume Weight, Uniaxial Compression Strength, Los500, etc.) are required to determine the exploitable blocks and their sequence of extraction. However, the number of samples that can be taken and analyzed is restricted, and thus the quality properties should be estimated at unknown locations. Cokriging has been traditionally used in the estimation of spa...

In order to exploit the upcoming regular measurements of vertical carbon dioxide (CO2) profiles over North America implemented in the framework of the North American Carbon Program (NACP), we design a direct carbon budgeting approach to infer carbon sources and sinks over the continent using model simulations. Direct budgeting puts a control volume on top of North America, balances air mass ina...

We review recent developments of sequential data assimilation techniques used in oceanography to integrate spatio-temporal observations into numerical models describing physical and ecological dynamics. Theoretical aspects from the simple case of linear dynamics to the general case of nonlinear dynamics are described from a geostatistical point-of-view. Current methods derived from the Kalman f...

Microtopography has long been regarded as a key variable affecting basin irrigation performance. This paper reports on the extension of a flat bed two-dimensional basin irrigation model to the simulation of irrigation events in basins with microtopography. The model incorporates the local surface slopes in the x and y directions to the governing set of partial differential equations. Three fiel...

Truncated Gaussian Simulation (TGS) is a well-known method to generate realizations of the ore domains located in a spatial sequence. In geostatistical framework geological domains are normally utilized for stationary assumption. The ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. As a simple a...