![]() To map a 3D object in 2D space, the surface must be transformed using a map projection. I work with these DEM files in GDAL (short for Geospatial Data Abstraction Library). Note: Many software programs can't read this kind of file, so it's normal if the DEM looks strange in Preview or other default image applications. Each pixel in this GeoTIFF file is a signed 16-bit integer that describes the elevation at that specific location on the moon. ![]() In this project I used a DEM for the moon provided by the United States Geologic Survey. To adapt this existing code to plot each geologic unit separately, you can edit the Moon_geologic_unit_colors.csv data file to use a different color for each geologic unit.ĭigital Elevation Models (DEMs) are data files that provide height information about different locations on a planet or moon. You may want to skip this step in 1_process_moon_data.ipynb to reproduce the data exactly. The end result is a summarized geologic map rather than a precise replication of the original data. The map features are colored only by geologic category (craters, basins, etc.) and not by age. I thought it was too complicated to show all these uncertain aggregations in one map, so I decided to omit timescale data entirely. And some geologic categories combined many time periods, like craters from Imbrian, Nectarian, and pre-Nectarian time periods. Some areas were described with uncertainty - like plains from the Imbrian or Nectarian era. This moon data was also challenging because the geologic timescales weren’t very precise. So I decided to combine closely related terms into a single color, using unit_descriptions_from_files.csv. One complication with having six datasets was that some geologic categories were described differently in each dataset, like Basin Material, Rugged vs. Each dataset had unique labels (and sometimes different data formats) so I spent a lot of time piecing the data together to create a cohesive map. Gathering and processing data Combining Geologic datasetsĪlthough I already made a geologic map of Mars and open-sourced the code, this moon map was much more difficult because the geologic data was split into six different datasets. Map design in Illustrator and Photoshop.There is no perfect software that fits everyone's needs, so you'll want to understand the pros and cons for the different raster and vector programs before choosing. I use Adobe Photoshop and Illustrator, but you can also use the free open-source programs Gimp and Inkscape. You'll need software for editing raster and vector images ( this article explains the difference). The instructions in this document under the "Conda" section are probably the most relevant if you've installed Python as described above. For the code in this repository you will also need to install GDAL. After you've installed Python using these tutorials, you can use Git Desktop and the instructions in this tutorial to download the code and data in this tutorial. Software Carpentry has great tutorials for installing Python (scroll down and follow the directions in the Bash Shell and Python sections), getting starting with Jupyter Notebooks, and beginner-friendly Python programming. Special instructions for beginners If you're new to coding: ![]() Dependencies can be installed with pip install -r requirements.txt. Python dependencies: pandas cartopy matplotlib os numpy shapefile jupyter. If you have comments or suggestions for this tutorial, please let me know on my blog! You can also buy the finished map here if you like. Software used includes Python 3.7.1, GDAL 2.4.1, bash, Illustrator CC 2019 and Photoshop CC 2019. ![]() This repository explains how to make a geologic map of the moon using open-source data from the USGS, IAU, and NASA. ![]()
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