:orphan:

.. _examples-basic:

Basic
=====

Examples using **terrain methods** and **DEM differences**, as well as
pre-defined **coregistration** and **uncertainty analysis** pipelines.


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    <div class="sphx-glr-thumbcontainer" tooltip="Subtracting a DEM with another one should be easy.">

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  .. image:: /basic_examples/images/thumb/sphx_glr_plot_dem_subtraction_thumb.png
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  :doc:`/basic_examples/plot_dem_subtraction`

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      <div class="sphx-glr-thumbnail-title">DEM differencing</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how to configure verbosity level, or logging, using a coregistration method. Logging can be customized to various severity levels, from DEBUG for detailed diagnostic output, to INFO for general updates, WARNING for potential issues, and ERROR or CRITICAL for serious problems.">

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  .. image:: /basic_examples/images/thumb/sphx_glr_plot_logging_configuration_thumb.png
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  :doc:`/basic_examples/plot_logging_configuration`

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      <div class="sphx-glr-thumbnail-title">Configuring verbosity level</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Digital elevation models have a precision that can vary with terrain and instrument-related variables. Here, we rely on a non-stationary spatial statistics framework to estimate and model this variability in elevation error, using terrain slope and maximum curvature as explanatory variables, with stable terrain as an error proxy for moving terrain.">

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  .. image:: /basic_examples/images/thumb/sphx_glr_plot_infer_heterosc_thumb.png
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  :doc:`/basic_examples/plot_infer_heterosc`

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      <div class="sphx-glr-thumbnail-title">Elevation error map</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Digital elevation models have errors that are spatially correlated due to instrument or processing effects. Here, we rely on a non-stationary spatial statistics framework to estimate and model spatial correlations in elevation error. We use a sum of variogram forms to model this correlation, with stable terrain as an error proxy for moving terrain.">

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  .. image:: /basic_examples/images/thumb/sphx_glr_plot_infer_spatial_correlation_thumb.png
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  :doc:`/basic_examples/plot_infer_spatial_correlation`

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      <div class="sphx-glr-thumbnail-title">Spatial correlation of errors</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Terrain attributes generated from a DEM have a multitude of uses for analytic and visual purposes. Here is an example of how to generate these products.">

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  .. image:: /basic_examples/images/thumb/sphx_glr_plot_terrain_attributes_thumb.png
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  :doc:`/basic_examples/plot_terrain_attributes`

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      <div class="sphx-glr-thumbnail-title">Terrain attributes</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="The Nuth and Kääb coregistration corrects horizontal and vertical shifts, and is especially performant for precise sub-pixel alignment in areas with varying slope. In xDEM, this approach is implemented through the xdem.coreg.NuthKaab class.">

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  .. image:: /basic_examples/images/thumb/sphx_glr_plot_nuth_kaab_thumb.png
    :alt:

  :doc:`/basic_examples/plot_nuth_kaab`

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      <div class="sphx-glr-thumbnail-title">Nuth and Kääb coregistration</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Iterative closest point (ICP) is a registration method accounting for both rotations and translations.">

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  .. image:: /basic_examples/images/thumb/sphx_glr_plot_icp_coregistration_thumb.png
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  :doc:`/basic_examples/plot_icp_coregistration`

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      <div class="sphx-glr-thumbnail-title">Iterative closest point coregistration</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Propagating elevation errors spatially accounting for heteroscedasticity and spatial correlation is complex. It requires computing the pairwise correlations between all points of an area of interest (be it for a sum, mean, or other operation), which is computationally intensive. Here, we rely on published formulations to perform computationally-efficient spatial propagation for the mean of elevation (or elevation differences) in an area.">

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  .. image:: /basic_examples/images/thumb/sphx_glr_plot_spatial_error_propagation_thumb.png
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  :doc:`/basic_examples/plot_spatial_error_propagation`

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      <div class="sphx-glr-thumbnail-title">Spatial propagation of elevation errors</div>
    </div>


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    </div>


.. toctree::
   :hidden:

   /basic_examples/plot_dem_subtraction
   /basic_examples/plot_logging_configuration
   /basic_examples/plot_infer_heterosc
   /basic_examples/plot_infer_spatial_correlation
   /basic_examples/plot_terrain_attributes
   /basic_examples/plot_nuth_kaab
   /basic_examples/plot_icp_coregistration
   /basic_examples/plot_spatial_error_propagation


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  .. container:: sphx-glr-footer sphx-glr-footer-gallery

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

      :download:`Download all examples in Python source code: basic_examples_python.zip </basic_examples/basic_examples_python.zip>`

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

      :download:`Download all examples in Jupyter notebooks: basic_examples_jupyter.zip </basic_examples/basic_examples_jupyter.zip>`


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