3D Visualization of Geospatial Huge Knowledge by Lexcube! (Python) | by Mahyar Aboutalebi, Ph.D. ๐ŸŽ“ | Feb, 2024


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Learn to work with Lexcube, a Python package deal for knowledge visualization within the space-time area!

Mahyar Aboutalebi, Ph.D. ๐ŸŽ“

Towards Data Science
  1. ๐ŸŒŸ Introduction
  2. ๐ŸŒ Lexcube
  3. ๐Ÿ“ฐ Knowledge
  4. ๐Ÿ“‚ Knowledge Dice with Random Numbers
  5. ๐Ÿ—‚๏ธ Knowledge Dice with Local weather Knowledge
  6. ๐Ÿ”„ Raster Layers to Xarray
  7. ๐ŸŒ 3D Visualization of Xarray by Lexcube
  8. ๐Ÿ“ฆ What Else Can We Do with Lexcube
  9. ๐Ÿ“ Conclusion
  10. ๐Ÿ“š References

๐ŸŒŸ Introduction

Knowledge visualization in three dimensions (latitude, longitude, and time) is fascinating, isnโ€™t it? As a geospatial knowledge scientist, I’ve at all times wished to know the simplest method to plot a cubic dataset created by merging a whole lot of raster layers. Whereas studying my feeds on LinkedIn, I discovered a terrific Python library known as Lexcube, which has lately grow to be accessible for Jupyter Pocket book. For extra details about Lexcube, please discuss with this article and/or try Lexcube on GitHub.

Initially, Iโ€™d wish to thank Miguel Mahecha for sharing that put up on LinkedIn and likewise Maximilian Sรถchting and his group for creating a invaluable instrument for the geospatial knowledge neighborhood. Secondly, here’s a hands-on train that will help you use this package deal to visualise your cubic knowledge in a 3D plot. All of the steps have been coded in Python in Google Colab and by the top of this story, you’ll learn to convert your raster layers to the Xarray format after which use it in Lexcube to create a 3D plot of your knowledge.

If, like me, you had been looking for a package deal for 3D visualization of your knowledge, this story is for you. I’ve no affiliation with Lexcube and simply wished to my expertise by scripting this weblog put up.

๐ŸŒ Lexcube

Leipzig Explorer of Earth Knowledge Cubes, or Lexcube, is an interactive knowledge visualization instrument developed by Maximilian Sรถchting as a Ph.D. challenge beneath the supervision of Gerik Scheuermann and Miguel Mahecha at Leipzig College. The instrument is designed to deal with giant Earth knowledge cubes. The challenge acquired funding from a number of establishments and companies, together with the European House Company (ESA). In Could 2022, an internet model of this instrument turnedโ€ฆ



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