GSTL: the geostatistical template library in C++

Rémy, Nicolas; Shtuka, Arben; Lévy, Bruno; Caers, Jef

doi:10.1016/s0098-3004(02)00021-3

Cited by 9 publications

(8 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our software is implemented in c++, using the GsTL and ANN libraries [19,20]. GsTL is used to build and solving the linear systems.…”

Section: Methodsmentioning

confidence: 99%

“…We generated our synthetic data sets using the Sgems [18] software. We generated values on a (1000 × 1000) grid, using the Sequential Gaussian Simulation (sgsim) algorithm of the Sgems software [19,18]. Points were simulated through ordinary kriging with a Gaussian covariance function of range equal to 12, using a maximum of 400 neighboring points within a 24 unit radius area.…”

Section: Data Setsmentioning

confidence: 99%

See 1 more Smart Citation

Efficient Implementation of an Optimal Interpolator for Large Spatial Data Sets

Memarsadeghi

Mount

2007

Computational Science – ICCS 2007

View full text Add to dashboard Cite

Abstract. Interpolating scattered data points is a problem of wide ranging interest. One of the most popular interpolation methods in geostatistics is ordinary kriging. The price for its statistical optimality is that the estimator is computationally very expensive. We demonstrate the space and time efficiency and accuracy of approximating ordinary kriging through the use of covariance tapering combined with iterative methods.

show abstract

“…Our software is implemented in c++, using the GsTL and ANN libraries [19,20]. GsTL is used to build and solving the linear systems.…”

Section: Methodsmentioning

confidence: 99%

Section: Data Setsmentioning

confidence: 99%

Efficient Implementation of an Optimal Interpolator for Large Spatial Data Sets

Memarsadeghi

Mount

2007

Computational Science – ICCS 2007

View full text Add to dashboard Cite

show abstract

“…The idea of Sgems started in 2001 when an Msc student "Nicolas Remy" introduced a C++ library with a title "GsTL:THE GEOSTATISTICAL 1 A voxel : The "voxel" term had originated from two words "volume" and "pixel". A voxel is a volume element .…”

Section: Sgems (Stanford Geo-statistical Modeling Software)mentioning

confidence: 99%

“…This concept was abstracted through an equation: Z(s) = µ(s) + ε(s)+ m [6] . [1] where Z(s) is the phenomena to be predicted at location s and µ is a mean (structural function describing the structural component) which is known or unknown and it is either constant or varies with location (in data with trends), and these properties depends on the type of the used Kriging. ε(s) is the stochastic but spatially auto-correlated residuals from µ(s) (i.e.…”

Section: Introductionmentioning

confidence: 99%

Integrating Geo-Statistics and Geographic Information Systems in Geotechnical Soil Profiling

Ismail

Fatah

Hefny

2015

ERJ. Engineering Research Journal

View full text Add to dashboard Cite

Since it s evolution, Geotechnical engineering is considered one of the sciences that deeply based on uncertainties. These uncertainties are attributed to two facts. First fact, the formulas used in geotechnical engineering are empirical formulas and could be deeply affected by the nonhomogeneity of soil formation. The second fact is that always the soil is being characterized through a group of boreholes that are considered representative for the whole site, which could result in the missing of some anomalies in soil composition. Hence, geo-technical engineers are always looking for a technique, that can be used in dealing with these uncertainties. Several techniques were adopted starting from the sixties of the previous century like knowledge base expert systems, finite element analysis and finally geo-statistics. But the most sidelined of these techniques was geo-statistics due to several reasons. Hence, this paper tries to introduce geostatistics focusing on its applications in geotechnical engineering specially in soil profiling. It discusses the reason behind the fact that still the actual implementation of Geo-statistics in Geotechnical engineering is without real presence in the traditional work of any geotechnical engineer. Moreover, it introduces a look ahead towards actual implementation of Geo-statistics in soil profiling through the integration between one of the most mature geo-statistical software (Sgems) and the GIS software which is ARCGIS of ESRI

show abstract

“…SGeMS was developed by Nicholas Remy with contributions from Alexandre Boucher, Jianbing Wu, and Ting Li in the Department of Energy Resources Engineering at Stanford University, and it is considered an evolution of GSLIB. The geostatistical algorithms implemented in SGeMS are taken from the Geostatistics Template Library (G S TL) (Remy 2001), which is a C++ library containing an extensive set of geostatistical tools. This library is designed to be easily extended and readily integrated into software packages.…”

Section: Introductionmentioning

confidence: 99%