Quick Start
Installing earthaccess
The latest release of earthaccess
can be installed with mamba
, conda
or pip
. We recommend using mamba
because it is faster.
You will need Python 3.8 or higher installed.
Using mamba
Using conda
Using pip
Check earthaccess
is installed
This should run seamlessly (fingers-crossed). To check earthaccess
is correctly installed you can start a python interpreter (either python or ipython) and run the following code.
$ python
Python 3.12.1 | packaged by conda-forge | (main, Dec 23 2023, 08:03:24) [GCC 12.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import earthaccess
>>> earthaccess.__version__
'0.8.2'
Note: Your
python
andearthaccess
versions may be different.
Get Data in 3 Steps
earthaccess
allows you to search for and access data in as little as three steps. We
give a very quick example below. These three steps allow you to get data whether you
are working in the cloud or on your local laptop or workstation. Read the
User Guide for more information. If you want to quickly find how
to perform some common searches and data access, take a look at our how-to guides in the
sidebar.
The only requirement to use this library is to open a free account with NASA Earthdata Login.
The following steps can be executed in a Python interpreter, a Python file, or a Jupyter notebook.
Step 1: Login
To access NASA data, you have to login using your Earth Data Login credentials. You can register for a free Earth Data Login account here.
By default, earthaccess
will look for your Earth Data Login credentials in a .netrc
file, or in environment variables EARTHDATA_USERNAME
and EARTHDATA_PASSWORD
. If you don't
have either of these set up, you can login manually. See Authenticating to learn how to create a .netrc
file or environment variables.
Step 2: Search for data
As an example, we'll search for the "ATLAS/ICESat-2 L3A Land Ice Height", or ATL06, dataset from the NASA ICESat-2 mission.
results = earthaccess.search_data(
short_name='ATL06',
bounding_box=(-10, 20, 10, 50),
temporal=("1999-02", "2019-03"),
count=10
)
Step 3. Download the files
Once you have found the files you want, you can download them to your local machine.
Note
This will download the data to a directory named local_folder
in your current
working directory (the directory from which you are running this code, also known as
.
). If that directory doesn't exist, it will be created automatically.
Data can also be opened in-memory with earthaccess.open()
. See our API
docs for more.