bmi-topography 0.3

Fetch and cache NASA SRTM land elevation data

bmi-topography

bmi-topography is a Python library to fetch and cache NASA Shuttle Radar Topography Mission (SRTM) land elevation data using the OpenTopography REST API.

The bmi-topography library provides access to the following global raster datasets:

• SRTM GL3 (90m)
• SRTM GL1 (30m)
• SRTM GL1 (Ellipsoidal)

The bmi-topography library includes an API and CLI that accept the dataset type, a latitude-longiture bounding box, and the output file format. Data are downloaded from OpenTopography and cached locally. The cache is checked before downloading new data. Data from a cached file can optionally be loaded into an xarray DataArray using the experimental open_rasterio method.

The bmi-topography API is wrapped with a Basic Model Interface (BMI), which provides a standard set of functions for coupling with data or models that also expose a BMI. More information on the BMI can found in its documentation.

Installation

Install the latest stable release of bmi-topography with pip:

pip install bmi-topography

The bmi-topography library can also be built and installed from source. The library uses several other open source libraries, so a convenient way of building and installing it is within a conda environment. After cloning or downloding the bmi-topography repository, change into the repository directory and set up a conda environment with the included environment file:

conda env create --file=environment.yml

Then install bmi-topography with

make install

Documentation

Documentation for the bmi-topography API and CLI is available at https://bmi-topography.readthedocs.io.

Examples

A brief example of using the bmi-topography API is given in the following steps.

Start a Python session and import the Topography class:

>>> from bmi_topography import Topography

For convenience, a set of default parameter values for Topography are included in the class definition. Copy these and modify them with custom values:

>>> params = Topography.DEFAULT.copy()
>>> params["south"] = 39.75
>>> params["north"] = 40.25
>>> params["west"] = -105.25
>>> params["east"] = -104.75
>>> params
{'dem_type': 'SRTMGL3',
 'south': 39.75,
 'north': 40.25,
 'west': -105.25,
 'east': -104.75,
 'output_format': 'GTiff',
 'cache_dir': '~/.bmi_topography'}

These coordinate values represent an area around Boulder, Colorado.

Make a instance of Topography with these parameters:

>>> boulder = Topography(**params)

then fetch the data from OpenTopography:

>>> boulder.fetch()
PosixPath('/Users/mpiper/.bmi_topography/SRTMGL3_39.75_-105.25_40.25_-104.75.tif')

This step might take a few moments, and it will increase for requests of larger areas. Note that the file has been saved to a local cache directory.

Load the data into an xarray DataArray for further work:

>>> boulder.load()
<xarray.DataArray 'SRTMGL3' (band: 1, y: 600, x: 600)>
[360000 values with dtype=int16]
Coordinates:
  * band     (band) int64 1
  * y        (y) float64 40.25 40.25 40.25 40.25 ... 39.75 39.75 39.75 39.75
  * x        (x) float64 -105.3 -105.2 -105.2 -105.2 ... -104.8 -104.8 -104.8
Attributes:
    transform:      (0.000833333333333144, 0.0, -105.25041666668365, 0.0, -0....
    crs:            +init=epsg:4326
    res:            (0.000833333333333144, 0.000833333333333144)
    is_tiled:       1
    nodatavals:     (0.0,)
    scales:         (1.0,)
    offsets:        (0.0,)
    AREA_OR_POINT:  Area
    units:          meters
    location:       node

For examples with more detail, see the two Jupyter Notebooks included in the examples directory of the bmi-topography repository.

Acknowledgments

This work is supported by the National Science Foundation under Award No. 2026951, EarthCube Capabilities: Cloud-Based Accessible and Reproducible Modeling for Water and Sediment Research.

Changes for bmi-topography

0.3 (2021-02-25)

• Update README with overview and install instructions
• Write documentation

0.2 (2021-02-24)

• Implement BMI for Topography class from template generated by bmipy-render
• Include sample config file and Jupyter Notebook to demo BMI
• Add CI with GitHub Actions

0.1.1 (2021-02-22)

• Add Makefile rule to test upload to TestPyPI
• Test upload to TestPyPI

0.1 (2021-02-22)

• Create base library that calls OpenTopography API
• Create CLI for library
• Write tests for library and CLI
• Include demo Jupyter Notebook for library

Contributing

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

Types of Contributions

Report Bugs

Report bugs at https://github.com/csdms/bmi-topography/issues.

If you are reporting a bug, please include:

• Your operating system name and version.
• Any details about your local setup that might be helpful in troubleshooting.
• Detailed steps to reproduce the bug.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with "bug" and "help wanted" is open to whoever wants to implement it.

Implement Features

Look through the GitHub issues for features. Anything tagged with "enhancement" and "help wanted" is open to whoever wants to implement it.

Write Documentation

bmi-topography could always use more documentation, whether as part of the official docs, in docstrings, or even on the web in blog posts, articles, and such.

Submit Feedback

The best way to send feedback is to file an issue at https://github.com/csdms/bmi-topography/issues.

If you are proposing a feature:

• Explain in detail how it would work.
• Keep the scope as narrow as possible, to make it easier to implement.
• Remember that this is a volunteer-driven project, and that contributions are welcome :)

Get Started!

Ready to contribute? Here's how to set up bmi-topography for local development.

1. Fork the bmi-topography repo on GitHub.

2. Clone your fork locally:

   $ git clone [e-mail]:your_name_here/bmi-topography.git
   

3. Install your local copy into a conda environment. A conda enviroment file is supplied at the root of the repository. Assuming you have conda installed, this is how you set up your fork for local development:

   $ cd bmi-topography
   $ conda env create --file=environment.yml
   $ conda activate topography
   $ make install
   

4. Create a branch for local development:

   $ git checkout -b name-of-your-bugfix-or-feature
   

   Now you can make your changes locally.

5. When you're done making changes, check that your changes pass flake8 and the tests:

   $ make lint
   $ make test
   

   Both flake8 and pytest are included in the environment.

6. Commit your changes and push your branch to GitHub:

   $ git add .
   $ git commit -m "Your detailed description of your changes."
   $ git push origin name-of-your-bugfix-or-feature
   

7. Submit a pull request through the GitHub website.

Pull Request Guidelines

Before you submit a pull request, check that it meets these guidelines:

1. The pull request should include tests.
2. If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
3. The pull request need only work with Python >= 3.8.

Deploying

A reminder for the maintainers on how to deploy. To make a new release, you will need to have zest.releaser installed, which can be installed with pip,

$ pip install zest.releaser[recommended]

Make sure all your changes are committed (including an entry in CHANGES.md). Then run,

$ fullrelease

This will create a new tag and alert the bmi-topography feedstock on conda-forge that there is a new release.