bmi-topography¶
bmi-topography is a Python library for fetching and caching land elevation data using the OpenTopography REST API.
The bmi-topography library provides access to the following global raster datasets:
SRTMGL3 (SRTM GL3 90m)
SRTMGL1 (SRTM GL1 30m)
SRTMGL1_E (SRTM GL1 Ellipsoidal 30m)
AW3D30 (ALOS World 3D 30m)
AW3D30_E (ALOS World 3D Ellipsoidal, 30m)
SRTM15Plus (Global Bathymetry SRTM15+ V2.1)
NASADEM (NASADEM Global DEM)
COP30 (Copernicus Global DSM 30m)
COP90 (Copernicus Global DSM 90m)
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 through rioxarray.
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
pip install -e .
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:
parameter: Pass the API key as a string through the
api_key
parameter.environment variable: In the shell, set the
OPENTOPOGRAPHY_API_KEY
environment variable to the API key value.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
* x (x) float64 -105.3 -105.3 -105.3 ... -105.3 -105.3 -105.3
* y (y) float64 40.0 40.0 40.0 40.0 ... 39.93 39.93 39.93 39.93
spatial_ref int64 0
Attributes:
_FillValue: 0.0
scale_factor: 1.0
add_offset: 0.0
units: meters
location: node
Note that coordinate reference system information is stored in the
spatial_ref
non-dimension coordinate:
>>> boulder.da.spatial_ref
<xarray.DataArray 'spatial_ref' ()>
array(0)
Coordinates:
spatial_ref int64 0
Attributes:
crs_wkt: GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["...
semi_major_axis: 6378137.0
semi_minor_axis: 6356752.314245179
inverse_flattening: 298.257223563
reference_ellipsoid_name: WGS 84
longitude_of_prime_meridian: 0.0
prime_meridian_name: Greenwich
geographic_crs_name: WGS 84
grid_mapping_name: latitude_longitude
spatial_ref: GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["...
GeoTransform: -105.33041666668363 0.000833333333333144 0....
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.
Additional Information¶
API Reference¶
Looking for information on a particular function, class, or method? This part of the documentation is for you.
Changelog¶
- Changes for bmi-topography
- 0.8.4 (unreleased)
- 0.8.3 (2023-12-18)
- 0.8.2 (2023-02-06)
- 0.8.1 (2023-01-27)
- 0.8 (2022-07-05)
- 0.7.1 (2022-06-03)
- 0.7 (2022-03-24)
- 0.6 (2022-02-17)
- 0.5.1 (2022-02-15)
- 0.5 (2022-01-25)
- 0.4 (2021-09-03)
- 0.3.2 (2021-04-23)
- 0.3.1 (2021-03-04)
- 0.3 (2021-02-25)
- 0.2 (2021-02-24)
- 0.1.1 (2021-02-22)
- 0.1 (2021-02-22)
Project documents¶
Indices and tables¶
Help¶
Depending on your need, CSDMS can provide advice or consulting services. Feel free to contact us through the CSDMS Help Desk.
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.