Tutorial 5 - 3D Topography #14
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Tutorial showcasing Mars Orbiter Laser Altimeter (MOLA) dataset, focusing on Olympus Mons. Data loaded via `pygmt.datasets.load_mars_relief`, plotting in 2D with `grdimage`, and in 3D using `grdview`. data processing pipeline over Wellington, New Zealand. Doing data loading using laspy, pre-processing with `blockmedian`, gridding with `surface`, and plotting in 2D with `grdimage` and in 3D using `grdview`.
Include tut5_topography in Table of Contents, and citation for the MOLA dataset.
Draft section on plotting an Antarctic DEM with RGB image overlay. Using REMA as the DEM, and Sentinel-2 L2A imagery. Need to mosaic two tiles together using rioxarray for both the DEM and RGB imagery. Have done a quick `grdview` plot based on my old code at weiji14/30DayMapChallenge2021@61f5698.
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@weiji14 |
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| @@ -10,3 +10,4 @@ dependencies: | |||
| # Optional dependencies | |||
| - geopandas=1.0.1 | |||
| - jupyter-book=1.0.2 | |||
| - rioxarray=0.17.0 | |||
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I cloned the repository and tested it on my local machine. It seems that rioxarray needs to be included in the environment.yml file. Is this correct, or am I missing something?
Yes, added here already 😄
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Hello @weiji14,
I’ve tested everything here, and I was planning to add a few more explanations, especially about the pros and cons of data resolution and computational requirements for large mosaics. Should I make these changes directly in the tut5_topography.md file, or should I create a new branch?
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Yes, feel free to push changes directly (be sure to do a git pull first in case I push any changes too 😉). I'll be adding more text to the Antarctica section too later.
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These maps look quite cool and visually appealing! I especially like the Antarctica map 🙂 !
I'll convert the *.md file (done in MyST Markdown) into a Jupyter Notebook before merging this PR. Using a markdown file for now just to make it easier to review the code.
Yeah, reviewing code and docs in plain text, i.e., normal Python scripts or at least markdown, is so much more convenient!
If anyone wants to test this locally, clone this branch and run jupyter-book build book/
Will try this, hopefully tomorrow, for a more detailed review.
| [Mollweide projection](https://www.pygmt.org/v0.13.0/projections/misc/misc_mollweide.html). | ||
| To get a reddish hue, we'll use a | ||
| [colormap](https://docs.generic-mapping-tools.org/6.5/reference/cpts.html) | ||
| called `SCM/managua` which comes with a soft hinge |
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Hm. For me, it works to directly give the name of a Scientific colourmap (without the folder "SCM"). We are also doing this in the PyGMT examples.
| called `SCM/managua` which comes with a soft hinge | |
| called `managua` which comes with a soft hinge |
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Yes, there's backwards compatibility with just using managua vs SCM/managua (see GenericMappingTools/gmt#6446 (comment)). The SCM/ prefix is intended for better recognition that this is a Scientific Colour Map, see comment at https://docs.generic-mapping-tools.org/6.5/reference/cpts.html:
The color maps are subdivided into a number of sections relating to their source. This avoids name clashes and improves recognision of the color maps as well as their authors
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Thanks for pointing out this GMT PR! Hm, maybe we should then do this for all tutorials consistently.
Co-authored-by: Yvonne Fröhlich <[email protected]>
Co-authored-by: Yvonne Fröhlich <[email protected]>
Explain some of the parameters used for image draping such as `drapegrid`, `surftype` and `zscale`. Moved some explanatory text into a 'tip' admonition cell.
Tutorial showcasing 3D perspective plots over Mars and Antarctica using
grdview.Preview image for Olympus Mons, Mars:
Preview image for Antarctica:
Notes:
jupyter-book build book/TODO:
grdviewfor elevation plot with simple colormap over Marsgrdviewto create 3D plot with draped imagery over AntarcticaReferences:
Fixes #11