12c Data Analytics: Kriging in R

Walkthrough of a workflow for data analytics, spatial analysis and estimation in a Jupyter Notebook with R kernel. The workflow is available in Jupyter Notebook at git.io/fpkjg, and R at git.io/fpkja, both in a repository at GitHub/GeostatsGuy.

[@mingusbingus6746]

Nice, I'm a soil scientist trying to expand my GIS skills. I like how your code is free and well-documented, really helps.

[@primeshchanaka3134]

11:54 - Visualize data
12:51 - Bubble plot
13:20 - Spplot
14:06 - Variogram model
20:13 - IDW
24:00 - ordinary kriging

[@hung144]

Excellent demo.

[@elinikou1145]

thanks a million for your excellent course !
that is really useful :))

[@GeostatsGuyLectures]

Thank you Eli. I hope that it was helpful.

[@kyngelian6335]

@Abel Samson Definitely, I've been using Flixzone for months myself =)

[@EarthAnalytics]

Thank you so much!

[@Abigor2894]

I have a problem with this, I used your method on datas who were not gaussian (at all, even with a log10 function). I don't get how your normalisation works, and I'm asking myself if I really can apply it to my datas ?

[@pravakirandash9758]

Sir, When I am trying to perform normal transformation, it says could not find function 'nscore'. Could you please help!

[@preetibisht1173]

Sir where can I get the process of spatio temporal regression kriging