GSLIB

GSLIB, short for Geostatistical Software Library, is a collection of computer programs and subroutines for performing geostatistical analysis on spatial data. It provides tools for variogram analysis, estimation and simulation, including various kriging methods (ordinary, simple, universal) and stochastic simulation techniques such as sequential Gaussian simulation, used for creating multiple realizations of a spatial field conditioned on sample data.

History and scope: GSLIB emerged in the 1980s as a standard reference implementation in geostatistics. It has been distributed in source code form and runs primarily in Fortran on Unix-like systems, with later adaptations to other environments. The library implements core geostatistical routines that have been described in journals and textbooks, and has influenced subsequent software packages and courses in the field.

Features: variogram modeling and estimation; kriging; block kriging; indicator and probability kriging; simulation and conditional simulation; post-processing tools for toning results; cross-validation to assess accuracy. It emphasizes a modular design that can be extended or embedded in other programs.

Impact and legacy: GSLIB remains widely cited as a foundational tool in geostatistics and education. It motivated the development of modern geostatistical software and libraries, and several open-source and commercial packages provide interfaces to GSLIB routines or re-implement equivalent functionality. While newer packages offer graphical interfaces and enhanced usability, GSLIB's straightforward algorithms and portability keep it in use in some research and applied settings.

See also: Geostatistics, Kriging, Stochastic simulation, Sequential Gaussian Simulation, Variogram.