mdpiper / bmi-topography

Fetch and cache NASA SRTM and JAXA ALOS land elevation data through a BMI

bmi-topography

bmi-topography is a Python library for fetching and caching land elevation data from the NASA Shuttle Radar Topography Mission (SRTM) and the JAXA Advanced Land Observing Satellite (ALOS) 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 (30m, Ellipsoidal)
• ALOS World 3D (30m)
• ALOS World 3D (30m, Ellipsoidal)

The library includes an API and a CLI that accept the dataset type, a latitude-longitude 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

or with conda:

conda install -c conda-forge 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 downloading 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 build and install bmi-topography from source with

make install

API key

To better understand usage, OpenTopography requires an API key to access datasets they host. Getting an API key is easy, and it's free; just follow the instructions in the link above.

Once you have an API key, there are three ways to use it with bmi-topography:

1. parameter: Pass the API key as a string through the API_key parameter.
2. environment variable: In the shell, set the OPENTOPOGRAPHY_API_KEY environment variable to the API key value.
3. dot file: Put the API key in the file .opentopography.txt in the current directory or in your home directory.

If you attempt to use bmi-topography to access an OpenTopography dataset without an API key, you'll get a error like this:

requests.exceptions.HTTPError: 401 Client Error: This dataset requires an API Key for access.

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"] = 39.93
>>> params["north"] = 40.00
>>> params["west"] = -105.33
>>> params["east"] = -105.26
>>> params
{'dem_type': 'SRTMGL3',
 'south': 39.93,
 'north': 40.0,
 'west': -105.33,
 'east': -105.26,
 '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_39.93_-105.33_40.0_-105.26.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: 84, x: 84)>
array([[[2052, 2035, ..., 1645, 1643],
        [2084, 2059, ..., 1643, 1642],
        ...,
        [2181, 2170, ..., 1764, 1763],
        [2184, 2179, ..., 1773, 1769]]], dtype=int16)
Coordinates:
  * band     (band) int64 1
  * y        (y) float64 40.0 40.0 40.0 40.0 40.0 ... 39.93 39.93 39.93 39.93
  * x        (x) float64 -105.3 -105.3 -105.3 -105.3 ... -105.3 -105.3 -105.3
Attributes:
    transform:      (0.000833333333333144, 0.0, -105.33041666668363, 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

Display the elevations with the default xarray DataArray plot method.

>>> import matplotlib.pyplot as plt
>>> boulder.da.plot()
>>> plt.show()

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

User and developer documentation for bmi-topography is available at https://bmi-topography.readthedocs.io.