The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial Sciences
This paper presents practical methods for the sequential generation or simulation of a Gaussian two-dimensional random field. The specific realizations typically correspond to geospatial errors or perturbations over a horizontal plane or grid. The errors are either scalar, such as vertical errors, o...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2014-06-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2220-9964/3/2/817 |
| _version_ | 1811327406866169856 |
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| author | John Dolloff Peter Doucette |
| author_facet | John Dolloff Peter Doucette |
| author_sort | John Dolloff |
| collection | DOAJ |
| description | This paper presents practical methods for the sequential generation or simulation of a Gaussian two-dimensional random field. The specific realizations typically correspond to geospatial errors or perturbations over a horizontal plane or grid. The errors are either scalar, such as vertical errors, or multivariate, such as , , and errors. These realizations enable simulation-based performance assessment and tuning of various geospatial applications. Both homogeneous and non-homogeneous random fields are addressed. The sequential generation is very fast and compared to methods based on Cholesky decomposition of an a priori covariance matrix and Sequential Gaussian Simulation. The multi-grid point covariance matrix is also developed for all the above random fields, essential for the optimal performance of many geospatial applications ingesting data with these types of errors. |
| first_indexed | 2024-04-13T15:07:11Z |
| format | Article |
| id | doaj.art-ee3d417795034fde99e3922948724528 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-04-13T15:07:11Z |
| publishDate | 2014-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-ee3d417795034fde99e39229487245282022-12-22T02:42:08ZengMDPI AGISPRS International Journal of Geo-Information2220-99642014-06-013281785210.3390/ijgi3020817ijgi3020817The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial SciencesJohn Dolloff0Peter Doucette1Sensor Geopositioning Center, National Geospatial-Intelligence Agency (contractors), 7500 GEOINT Dr, Springfield, VA 22150, USASensor Geopositioning Center, National Geospatial-Intelligence Agency (contractors), 7500 GEOINT Dr, Springfield, VA 22150, USAThis paper presents practical methods for the sequential generation or simulation of a Gaussian two-dimensional random field. The specific realizations typically correspond to geospatial errors or perturbations over a horizontal plane or grid. The errors are either scalar, such as vertical errors, or multivariate, such as , , and errors. These realizations enable simulation-based performance assessment and tuning of various geospatial applications. Both homogeneous and non-homogeneous random fields are addressed. The sequential generation is very fast and compared to methods based on Cholesky decomposition of an a priori covariance matrix and Sequential Gaussian Simulation. The multi-grid point covariance matrix is also developed for all the above random fields, essential for the optimal performance of many geospatial applications ingesting data with these types of errors.http://www.mdpi.com/2220-9964/3/2/817geospatialrandom fielderrorssequentialsimulationcovariance matrixstrictly positive definite correlation function |
| spellingShingle | John Dolloff Peter Doucette The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial Sciences ISPRS International Journal of Geo-Information geospatial random field errors sequential simulation covariance matrix strictly positive definite correlation function |
| title | The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial Sciences |
| title_full | The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial Sciences |
| title_fullStr | The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial Sciences |
| title_full_unstemmed | The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial Sciences |
| title_short | The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial Sciences |
| title_sort | sequential generation of gaussian random fields for applications in the geospatial sciences |
| topic | geospatial random field errors sequential simulation covariance matrix strictly positive definite correlation function |
| url | http://www.mdpi.com/2220-9964/3/2/817 |
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