Geostatistical Software

Abstract

Geostatistical spatio-temporal models provide a probabilistic framework for data analysis and predictions that build on the joint spatial and temporal dependence between observations. Since its original development in the mining industry in the late 1950s and early 1960s, the geostatistical approach has been adopted in many disciplines, such as environmental sciences (remote sensing, characterization of contaminated sediments, estimation of fish abundance), meteorology (space-time distribution of temperature and rainfall), hydrology (modeling of subsurface hydraulic conductivity), ecology (characterization of population dynamics), agriculture (maps of soil properties and crop yields), and health (patterns of diseases and exposure to pollutants). Following the increasing popularity of geostatistics, the software market has expanded substantially since the late 1980s when it was restricted more or less to two public-domain applications running under DOS: Geo- EAS (Geostatistical Environmental Assessment Software, Englund and Sparks 1988) and the Geostatistical Toolbox (Froidevaux 1990). Nowadays geostatistical software encompasses a wide range of products in terms of price, operating systems, user-friendliness, functionalities, graphical and visualization capabilities. Several organizations, such as AI-GEOSTATS (www.aigeostats.org) or the Pedometrics commission of the International Union of Soil Sciences (www.pedometrics.org), provide a fairly complete list of geostatistical freeware and commercial packages on their website; the long list could intimidate any newcomer to the field and it is summarized in Table A.7.1.