Large synthetic datasets for univariate geostatistical modeling

The enclosed datasets have been generated by the internal spatial data generator tool included in the ExaGeoStat software (https://github.com/ecrc/exageostat). The datasets are univariate 2D spatial data spanning different correlation strengths between the geospatial locations with three different smoothness levels (0.6, 1.5, and 2.3). The main purpose of these datasets is to validate any exact or approximation geospatial modeling algorithm by providing the truth parameters used for generating each dataset. For certain data configurations that are not covered by the provided datasets, ExaGeoStat software can be used directly to generate geospatial data with a prescribed number of locations and prescribed parameter set.

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Abdulah, S., Ltaief, H., Sun, Y., Genton, M. G., & Keyes, D. E. (2020). Large synthetic datasets for univariate geostatistical modeling [Data set]. KAUST Research Repository. https://doi.org/10.25781/KAUST-JJVCN

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[Article]
Abdulah S, Ltaief H, Sun Y, Genton MM, Keyes D (2018) ExaGeoStat: A High Performance Unified Software for Geostatistics on Manycore Systems. IEEE Transactions on Parallel and Distributed Systems: 1–1. Available: http://dx.doi.org/10.1109/tpds.2018.2850749.. DOI: 10.1109/tpds.2018.2850749 Handle: 10754/628384

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