EarthPy

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

Why EarthPy?

Python is a generic programming language designed to support many different applications. Because of this, many commonly performed spatial tasks for science including plotting and working with spatial data take many steps of code. EarthPy takes advantage of functionality developed for raster data (rasterio) and vector data (geopandas) and simplifies the code needed to :

• Stack raster bands from data such as Landsat into an easy to use numpy array
• Work with masks to set bad pixels such a those covered by clouds and cloud-shadows to NA (mask_pixels())
• Plot rgb (color), color infrared and other 3 band combination images (plot_rgb())
• View histograms of sets of raster
• Create discrete (categorical) legends

EarthPy also has an io module that allows users to

1. Quickly access pre-created datasubsets used in the earth-analytics courses hosted on www.earthdatascience.org
2. Download other datasets that they may want to use in their workflows.

View Example EarthPy Applications in Our Documentation Gallery

Check out our vignette gallery for applied examples of using EarthPy in common spatial workflows.

Install

To install, use pip or conda-forge. We encourage you to use conda-forge if you are a conda users.

Install via Pip

To install EarthPy via pip use:

$ pip install --upgrade earthpy

Install Using Conda / conda-forge Channel

If you are working within an Anaconda environment, we suggest that you install EarthPy using conda-forge

$ conda install -c conda-forge earthpy

Note: if you want to set conda-forge as your default conda channel, you can use the following install workflow. We recommmend this approach. Once you have run conda config, you can install earthpy without specifying a channel.

$ conda config --add channels conda-forge
$ conda install earthpy

Once you have successfully installed EarthPy, you can import it into Python.

>>> import earthpy as et

Below is a quick example of plotting multiple bands in a numpy array format.

>>> arr = np.random.randint(4, size=(3, 5, 5))
>>> ep.plot_bands(arr, titles=["Band 1", "Band 2", "Band 3"])
>>> plt.show()

Active Contributors

We welcome contributions to EarthPy. Below are the current active package maintainers. Please see our contributors file for a complete list of all of our contributors.

How to Contribute

We welcome contributions to EarthPy! Please be sure to check out our contributing guidelines for more information about submitting pull requests or changes to EarthPy.

License

BSD-3