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Wrapper around rasterio to query points on a Digital Elevation Model
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README.md

demquery

Pypi Downloads Supported Python Versions

Wrapper around rasterio to query points on a Digital Elevation Model.

Features

  • Use multiple raster files without having to merge them into a new file
  • Query many points at once
  • Optional 2D interpolation (linear, cubic, or quintic)
  • Reasonably performant by reading the minimal data required from raster

Install

I recommend first installing dependencies with Conda, then installing demquery itself with pip.

conda install gdal rasterio numpy scipy -c conda-forge
pip install demquery

CLI Script

> demquery --help
Usage: demquery [OPTIONS] FEATURES...

  Assign elevations to GeoJSON

Options:
  -d, --dem PATH          Paths to DEM files.  [required]
  -g, --dem-glob TEXT     Glob expression for DEM paths if folder is provided.
  -b, --band INTEGER      Band of rasters to use  [default: 1]
  -i, --interp-kind TEXT  either None, "linear", "cubic", or "quintic". None
                          will do no interpolation and choose the value in the
                          DEM closest to the provided point. linear creates a
                          3x3 grid and runs linear interpolation; cubic
                          creates a 5x5 grid and runs cubic interpolation;
                          quintic creates a 7x7 grid and runs quintic
                          interpolation.
  --help                  Show this message and exit.
echo \
    '{"type":"Feature","properties":{"name": "Glacier Peak"},"geometry":{"type":"Point","coordinates":[-121.2436843,48.0163834]}}' \
    | demquery -d /path/to/dem/files

Outputs:

{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-121.243684, 48.016383, 1431.5755615234375]}, "properties": {"name": "Glacier Peak"}}]}

Documentation

from demquery import Query

dem_paths = ['dem1.tif', 'dem2.tif']
query = Query(dem_paths)

# Points must be in longitude, latitude order!
# These points are in Manhattan, not Antarctica
points = [(-73.985564, 40.757965), (-73.968520, 40.778912)]
elevations = query.query_points(points, interp_kind='linear')

Data Download

For a great visual tool to download worldwide SRTM data, check out these sites:

Releasing

To upload a new release to PyPI

python setup.py sdist
twine upload dist/demquery-0.3.0.tar.gz
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