Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS) and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that d...

Geostatistical simulations are used to perform a global sensitivity analysis on a model Y = f(X1 ... Xk) where one of the model inputs Xi is a continuous 2D-field. Geostatistics allow specifying uncertainty on Xi with a spatial covariance model and generating random realizations of Xi. These random realizations are used to propagate uncertainty through model f and estimate global sensitivity in...

Geostatistics is a branch of statistics dealing with spatial phenomena modelled by random functions. In particular, it is assumed that, under some wellchosen simplifying hypotheses of stationarity, this probabilistic model, i.e. the random function describing spatial dependencies, can be completely assessed from the dataset by the experts. Kriging is a method for estimating or predicting the sp...

This document presents an extract of an upcoming book written by Nicolas Remy, Alexandre Boucher and Jianbing Wu. The book has 10 chapters detailing how to use the SGeMS software. SGeMS is a software for 3D geostatistical modeling. It implements many of the classical geostatistics algorithms, as well as new developments related to multiple-point geostatistics. The software is open source and fr...

Abstract. Geostatistics as a subfield of statistics accounts for the spatial correlations encountered in many applications of, example, earth sciences. Valuable information can be extracted from these correlations, also helping to address often burden data scarcity. Despite value additional data, use geostatistics still falls short its potential. This problem is connected lack user-friendly sof...

The paper presents decision-oriented mapping of pollution using hybrid models based on statistical learning theory (support vector regression or SVR) and spatial statistics (geostatistics). Adaptive and robust SVR approach is used to model non-linear large scale trends in the region and geostatistical models – spatial predictions and spatial simulations – are used to prepare decisionoriented ma...

Ecological processes act upon landscapes over a wide range of temporal and spatial extents. These processes interact to create complex and ever-changing landscape patterns. While remote sensing data (e.g. AVHRR, TM) has often been used to characterize such heterogeneity at the landscape scale, these sensors cannot resolve spatial pattern to the detail required for finer scale analyses, such as ...

permeability is a key parameter in reservoir characterization. in fact, without accurate information about reservoir permeability, there is no good solution for reservoir engineering problems. up to now, permeability values of a reservoir have been calculated through laboratory measurements or well testing methods. these methods are useful but they cannot describe a reservoir reliably and preci...