.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "generated/gallery/scalar_data/from_tiff__dem.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_generated_gallery_scalar_data_from_tiff__dem.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_generated_gallery_scalar_data_from_tiff__dem.py:


GeoTIFF DEM
-----------

This example demonstrates how to render **Digital Elevation Model** (DEM) data
encoded in an `OGC GeoTIFF <https://www.ogc.org/standard/geotiff/>`_ as a
geolocated mesh.

📋 Summary
^^^^^^^^^^

Creates an elevation warped mesh from GeoTIFF encoded DEM data.

The data is sourced from the **USGS Earth Resources Observation and Science**
(EROS) Archive, which is freely available from the
`USGS EarthExplorer <https://earthexplorer.usgs.gov>`_.

The Digital Elevation Model data was collected as part of the **Shuttle
Radar Topography Mission** (SRTM) aboard the space shuttle *Endeavour*,
February 11-22, 2000.

Endeavour orbited Earth 16 times each day during the 11-day mission,
completing 176 orbits. SRTM successfully collected radar data over 80%
of the Earth's land surface between 60°N and 56°S latitude with
data points posted every 1 arc-second (approximately 30 meters).

This SRTM sample is of *Mount Fuji*, one of Japan's
`Three Holy Mountains <https://blog.japanwondertravel.com/japans-three-sacred-mountains-14297>`_,
which is an active stratovolcano, located on the Japanese island of *Honshū*.

The resulting mesh contains quad cells, with the elevation data located
on the mesh nodes/points.

The elevation data is used to extrude the mesh proportionally to reveal
the topography of Mount Fuji and its surrounding landscape.

.. tags:: DEM, GeoTIFF, Warp

.. attention:: Optional package dependency :mod:`rasterio` is required.

----

.. GENERATED FROM PYTHON SOURCE LINES 51-104







.. tab-set::



   .. tab-item:: Static Scene



            
     .. image-sg:: /generated/gallery/scalar_data/images/sphx_glr_from_tiff__dem_001.png
        :alt: from tiff  dem
        :srcset: /generated/gallery/scalar_data/images/sphx_glr_from_tiff__dem_001.png
        :class: sphx-glr-single-img
     


   .. tab-item:: Interactive Scene



       .. offlineviewer:: /home/docs/checkouts/readthedocs.org/user_builds/geovista/checkouts/v0.5.3/docs/src/generated/gallery/scalar_data/images/sphx_glr_from_tiff__dem_001.vtksz






.. code-block:: Python


    from __future__ import annotations

    import geovista as gv
    from geovista.pantry import fetch_raster
    import geovista.theme


    def main() -> None:
        """Plot and warp GeoTIFF DEM data.

        Notes
        -----
        .. versionadded:: 0.5.0

        """
        # Fetch the example GeoTIFF file.
        fname = fetch_raster("fuji_dem.tif")

        # Plot the DEM data.
        plotter = gv.GeoPlotter()

        # Load the GeoTIFF image, which requires the optional package
        # dependency 'rasterio'.
        mesh = gv.Transform.from_tiff(fname, extract=True, name="Elevation / {units}")

        # Warp the mesh nodes by the elevation.
        mesh.compute_normals(cell_normals=False, point_normals=True, inplace=True)
        mesh.warp_by_scalar(inplace=True, factor=2e-7)

        sargs = {"fmt": "%.1f", "shadow": True}
        plotter.add_mesh(mesh, cmap="speed_r", scalar_bar_args=sargs, smooth_shading=True)
        plotter.add_logo_widget(fetch_raster("japan_map.png"), position=(0.8, 0.8))
        plotter.add_axes()
        plotter.add_text(
            "Mount Fuji, Digital Elevation Model GeoTIFF",
            position="upper_left",
            font_size=10,
            shadow=True,
        )

        # Define a specific camera position and orientation.
        cpos = [
            (-0.6134635189209598, 0.5500672658209347, 0.5735486559145044),
            (-0.6130746222715426, 0.5383021484428419, 0.5780820278342568),
            (-0.6616613958706443, 0.25045119061438004, 0.7067378568708134),
        ]

        plotter.show(cpos=cpos)


    if __name__ == "__main__":
        main()


.. _sphx_glr_download_generated_gallery_scalar_data_from_tiff__dem.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: from_tiff__dem.ipynb <from_tiff__dem.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: from_tiff__dem.py <from_tiff__dem.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: from_tiff__dem.zip <from_tiff__dem.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_