Kriging With External Drift. #1 Introduction and Grid.

Kriging With External Drift. #1 Introduction and Grid.
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#geographicinformationsystem #QGIS #SpatialAnalysis #mapping #GoogleEarth #historicalimagery
This is the 1st part of the 4 lesson of the 4th Geostatistics Course. Kriging and Cokriging Interpolation & Mapping, where the main topic is Kriging with external drift.
Geostatistical techniques often use multiple terms for similar methods, causing confusion to users. However, universal kriging, kriging with external drift, and regression kriging are essentially the same technique.
Many authors use the term “Universal Kriging” specifically when only the coordinates are used as predictors to define the trend surface.
The term “Kriging with External Drift” is preferred when the drift, or deterministic part of variation, is defined externally as a linear function of certain explanatory variables, rather than the coordinates.
In kriging with external drift, an additional variable, known as the external drift, is included in the interpolation process. The external drift can be any variable that is thought to have an influence on the variable being interpolated.
In this lesson, we will use QGIS to create a grid for our prediction locations, including the external drift (covariate). We previously learned how to create a grid with R, but we will focus on using QGIS in this lesson because it is more intuitive and will help us better understand the concepts. Using QGIS will also make it easier for us to complete the process.

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To learn more about Geo RGB, visit us at:
giscourse.online/
Visit us in the Facebook page at:
facebook.com/GeoRGBCommunity
Follow us in LinkedIn:
www.linkedin.com/company/georgb-community/
Follow me in LinKedIn:
linkedin.com/in/marcel-cedrez
Contact us at:
[e-mail]

[@JorgeRodriguez-mp1mt]

Thanks for sharing, greetings from Mexico

[@GeoRGBCommunity]

Thanks for commenting!!!