Introduction to geostatistical analysis of data in geosciences: theory and aplication
Guardado en:
| Autor: | |
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| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2022 |
| Descripción: | Kriging, the interpolation method linked to geostatistics, has been used and has been proposed as the best interpolation method, a lot of times without really understanding how to properly apply it and allowing the software that offers it to decide how to implement it. This statement is correct when used in the right way, performing all the necessary steps throughout the geostatistical analysis and modeling, for this reason is necessary to understand how to apply Kriging correctly so the results are relevant and reliable. These steps are detailed in this work, going over the theory, and through a practical example, using average temperature data over the last 10 years for March 8th for the San José province, the method is implemented using the free statistical software R. Additionally, a free access web application is shown for those who are not comfortable using programming languages. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/51474 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/geologica/article/view/51474 |
| Access Level: | acceso abierto |
| Palabra clave: | Geostatistics Kriging R Variogram Interpolation Cross-validation Geoestadística Variograma Interpolación Validación cruzada |