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64 lines
1.6 KiB
ReStructuredText
64 lines
1.6 KiB
ReStructuredText
==========================================
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Rasterio: access to geospatial raster data
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==========================================
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Geographic information systems use GeoTIFF and other formats to organize and
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store gridded raster datasets such as satellite imagery and terrain models.
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Rasterio reads and writes these formats and provides a Python API based on
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Numpy N-dimensional arrays and GeoJSON.
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Here's an example program that extracts the GeoJSON shapes of a raster's valid
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data footprint.
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.. code:: python
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import rasterio
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import rasterio.features
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import rasterio.warp
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with rasterio.open('example.tif') as dataset:
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# Read the dataset's valid data mask as a ndarray.
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mask = dataset.dataset_mask()
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# Extract feature shapes and values from the array.
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for geom, val in rasterio.features.shapes(
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mask, transform=dataset.transform):
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# Transform shapes from the dataset's own coordinate
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# reference system to CRS84 (EPSG:4326).
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geom = rasterio.warp.transform_geom(
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dataset.crs, 'EPSG:4326', geom, precision=6)
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# Print GeoJSON shapes to stdout.
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print(geom)
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The output of the program:
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.. code:: python
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{'type': 'Polygon', 'coordinates': [[(-77.730817, 25.282335), ...]]}
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Rasterio supports Python versions 2.7 and 3.3 or higher.
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.. toctree::
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:maxdepth: 2
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intro
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installation
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quickstart
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cli
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topics/index
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api/index
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contributing
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faq
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Indices and Tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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.. _GDAL: http://gdal.org/
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