3DPolate - Shiny Contest Submission

3DPolate

Authors: Andreas Botnen Smebye, Erlend Briseid Storrøsten

Abstract: 3DPolate expands your knowledge on how to walk, or interpolate if you like, from your point measurements and find estimated values anywhere in the 3D suroundings! We have put up different methods for you to compare so you can get the best fit for your datastet!

Full Description: Getting tired of those lengthy lunch discussion on how to interpolate in 3D? Likely not... Anyways, here's an app that enables you to go from point measurements to a estimates in a 3D grid. To end those lunch discussions on methodology you didn't have, we have compared different interpolation techniques and their associated errors for you in a qualitative assesment. We have focues on both deterministic methods such as Nearest Neighbour and Inverse Distance Weighting in addition to Geostatiscal methods such as Ordinary Kriging.


Keywords: Spatial, 3D, geostat
Shiny app: https://miljongi.shinyapps.io/3DPolate
Repo: GitHub - smebotand/3Dpolate: Repos for shiny 2021 contest submission
RStudio Cloud: Posit Cloud

Thumbnail:
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Very interesting, could it also be used with 2D data? (X, Y).

Thnx for the feedback! Things got a bit hecktick here (submitted 2 minutes before the deadline...) and its getting late, so I must admit the testing was kept at a minimum... but I guess 2D should be fine as well as long as you provide your dataset with a constant z-value :slight_smile: