Tools

The Earth Data Science tools below provide resources to access and work with data using R and Python and to setup R and Python environments. Our custom docker containers are pre-built environments that you can install on your computer that contain all of the software programs, libraries and tools that you need to process specific types of data. We have several pre built docker containers including ones to work with spatial data in R and Python. All Earth Lab libraries are open source and permissively licensed.

Many of these tools are open source and permissively licensed.

GeoMAC_DL

Programmatic access to Geospatial Multi-Agency Coordination (GeoMAC) fire data in Python.

OpenTopoDL

Programmatic access to digital elevation models and lidar point clouds from OpenTopo with Python.

ABC Classroom

A suite of Python command-line utilities that makes it easier to manage a class using GitHub classroom.

Docker images

Pre-built computing environments for reproducible and portable geospatial analysis.

Earth Analytics Python Conda Environment

A python environment for working with earth and environment data.

EarthPy

EarthPy makes it easier to plot and manipulate spatial data in Python.

Setup JupyterHub Using Google Cloud Through GitHub

Infrastructure and operations for the Earth Lab JupyterHubs.

matplotcheck

Matplotcheck is a Python package that makes it easier to test plots. It can be used to support autograding Python homework assignments.

qtoolkit

An R package to get process and visualize Qualtrics survey data.

smapr

An R package for acquiring and processing soil moisture data from the NASA SMAP mission.