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https://github.com/ungarj/mapchete

Tile-based geodata processing using rasterio & Fiona
https://github.com/ungarj/mapchete

batch-processor earth-observation earth-sciences fiona geoprocessing gis pyramid raster rasterio tile vector web-mercator

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Tile-based geodata processing using rasterio & Fiona

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README 

        
.. image:: logo/mapchete.svg



Tile-based geodata processing.



.. image:: https://badge.fury.io/py/mapchete.svg

    :target: https://badge.fury.io/py/mapchete



.. image:: https://github.com/ungarj/mapchete/actions/workflows/python-package.yml/badge.svg

    :target: https://github.com/ungarj/mapchete/actions



.. image:: https://readthedocs.org/projects/mapchete/badge/?version=latest

    :target: http://mapchete.readthedocs.io/en/latest/?badge=latest

    :alt: Documentation Status



.. image:: https://img.shields.io/pypi/pyversions/mapchete.svg

    :target: https://pypi.python.org/pypi/mapchete



Mapchete processes raster and vector geodata in digestable chunks.



Processing larger amounts of data requires chunking the input data into smaller tiles

and process them one by one. Python provides a lot of useful packages to process geodata

like shapely_ or numpy_. From within your process code you will have access to the geodata

in the form of ``NumPy`` arrays for raster data or GeoJSON-like feature dictionaries for

vector data.



Internally the processing job is split into tasks which can processed in parallel using either

``concurrent.futures`` or build task graphs and use dask_ to intelligently process either on

the local machine or on a cluster.



With the help of fiona_ and rasterio_ Mapchete takes care about resampling and

reprojecting geodata, applying your Python code to the tiles and writing the output either

into a single file or into a directory of files organized in a WMTS_-like tile pyramid.

Details on tiling scheme and available map projections are outlined in the

`tiling documentation`_.



.. _shapely: http://toblerity.org/shapely/

.. _numpy: http://www.numpy.org/

.. _dask: https://www.dask.org/

.. _fiona: https://github.com/Toblerity/Fiona

.. _rasterio: https://github.com/mapbox/rasterio/

.. _WMTS: https://en.wikipedia.org/wiki/Web_Map_Tile_Service

.. _`tiling documentation`: https://mapchete.readthedocs.io/en/latest/tiling.html



.. figure:: https://mapchete.readthedocs.io/en/latest/_images/mercator_pyramid.svg

   :align: center

   :target: https://mapchete.readthedocs.io/en/latest/tiling.html



   (standard Web Mercator pyramid used in the web)



-----

Usage

-----



You need a ``.mapchete`` file for the process configuration. The configuration is based

on the ``YAML`` syntax.



.. code-block:: yaml



    process: my_python_process.py  # or a Python module path: mypythonpackage.myprocess

    zoom_levels:

        min: 0

        max: 12

    input:

        dem: /path/to/dem.tif

        land_polygons: /path/to/polygon/file.geojson

    output:

        format: PNG_hillshade

        path: /output/path

    pyramid:

        grid: mercator



    # process specific parameters

    resampling: cubic_spline



You also need either a ``.py`` file or a Python module path where you specify the process

itself.



.. code-block:: python



    def execute(mp, resampling="nearest"):



        # Open elevation model.

        with mp.open("dem") as src:

            # Skip tile if there is no data available or read data into a NumPy array.

            if src.is_empty(1):

                return "empty"

            else:

                dem = src.read(1, resampling=resampling)



        # Create hillshade using a built-in hillshade function.

        hillshade = mp.hillshade(dem)



        # Clip with polygons from vector file and return result.

        with mp.open("land_polygons") as land_file:

            return mp.clip(hillshade, land_file.read())



You can then interactively inspect the process output directly on a map in a

browser (first, install dependencies by ``pip install mapchete[serve]`` go to

``localhost:5000``):



.. code-block:: shell



    $ mapchete serve hillshade.mapchete --memory



The ``serve`` tool recognizes changes in your process configuration or in the

process file. If you edit one of these, just refresh the browser and inspect the

changes (note: use the ``--memory`` flag to make sure to reprocess each tile and

turn off browser caching).



Once you are done with editing, batch process everything using the ``execute``

tool.



.. code-block:: shell



    $ mapchete execute hillshade.mapchete



-------------

Documentation

-------------



There are many more options such as zoom-dependent process parameters, metatiling, tile

buffers or interpolating from an existing output of a higher zoom level. For deeper

insights, please go to the documentation_.



.. _documentation: http://mapchete.readthedocs.io/en/latest/index.html



Mapchete is used in many preprocessing steps for the `EOX Maps`_ layers:



* Merge multiple DEMs into one global DEM.

* Create a customized relief shade for the Terrain Layer.

* Generalize landmasks & coastline from OSM for multiple zoom levels.

* Extract cloudless pixel for Sentinel-2 cloudless_.



.. _cloudless: https://cloudless.eox.at/

.. _`EOX Maps`: http://maps.eox.at/



------------

Installation

------------



via PyPi:



.. code-block:: shell



    $ pip install mapchete



from source:



.. code-block:: shell



    $ git clone [email protected]:ungarj/mapchete.git && cd mapchete

    $ pip install .



To make sure Rasterio, Fiona and Shapely are properly built against your local GDAL and

GEOS installations, don't install the binaries but build them on your system:



.. code-block:: shell



    $ pip install --upgrade rasterio fiona shapely --no-binary :all:



To keep the core dependencies minimal if you install mapchete using ``pip``, some features

are only available if you manually install additional dependencies:



.. code-block:: shell



    # for contour extraction:

    $ pip install mapchete[contours]



    # for dask processing:

    $ pip install mapchete[dask]



    # for S3 bucket reading and writing:

    $ pip install mapchete[s3]



    # for mapchete serve:

    $ pip install mapchete[serve]



    # for VRT generation:

    $ pip install mapchete[vrt]



-------

License

-------



MIT License



Copyright (c) 2015 - 2022 `EOX IT Services`_



.. _`EOX IT Services`: https://eox.at/