Environmental Systems References

These references were gathered while learning about environmental systems and data analytics while attending the CU Boulder EarthLab course on Earth Data Analytics. To help me understand and organize code and ideas, I developed the landmapy package. See also Python Strategy.

byandell.github.io/Documentation

Earth Data Analytics

Home Computer Visual Studio Code & GitBash

Lesson 2. Setup Git, Bash, and Conda on Your Computer Setup earth analytics environment

Command line entries to install miniconda via bash:

mkdir -p ~/miniconda3
curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh -o ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm ~/miniconda3/miniconda.sh

Set up SSH key in GitHub account

Generating a new SSH key and adding it to the ssh-agent

ssh-keygen -t ed25519 -C "byandell@wisc.edu"

Default storage is in ~/.ssh/id_ed25519.

Can use pbcopy to copy public key to clipboard for subsequent paste to GitHub SSH key generation (2 ways).

cat ~/.ssh/id_ed25519.pub | pbcopy
pbcopy < ~/.ssh/id_ed25519.pub

Open Street Map

OpenStreetMap (OSM). Data can be accessed via osmdata. Static maps are plotted using ggplot2 with sf bridging via geom_sf for polygon and point layers. OSM base map layer is added with annotation_map_tile from ggspatial package. Interactive maps can be produces with package tmap.

OSM is a free resource with maps and features (but should be cited). Most people seem to use Python to work with such maps, but there are some tools in R.

osmdata package

ggspatial package

tmap package

Google Maps Platform Access

Google maps can be used via ggmap but require a Google Map Key, which requires CC and payment.


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