.. _topography:

==========
Topography
==========

Topographic information is an important input to WAsP's flow models.
Specifically, WAsP's terrain model takes as input maps of surface elevation,
surface roughness, and optionally displacement height.

In PyWAsP, instead of dealing with surface roughness maps and displacement height maps as completely separate layers,
we deal with them as land cover maps, where patches of land are associated with specific land cover classes,
each having specific surface characteristics (i.e. the surface roughness and displacement height).

Maps in the forms of rasters or vectors of surface roughness can be read by :doc:`WindKit <windkit:windkit>`, but are converted directly to land cover classes and an associated look-up table of
surface characteristics.

To start working with topographic data, we will import ``xarray``, ``matplotlib``, ``windkit``, and ``pywasp``.

.. ipython:: python
    :okwarning:

    import xarray as xr
    import matplotlib.pyplot as plt
    import windkit as wk
    import pywasp as pw


Topography I/O
========================

Reading and writing topography files is handled by :doc:`WindKit <windkit:windkit>`. Currently,
windkit supports the following file formats:

.. list-table:: Supported topography file formats
   :widths: 2, 3, 2, 2
   :align: center
   :header-rows: 1

   * - Format
     - Raster/Vector
     - Read
     - Write
   * - ``.nc``
     - Raster
     - yes
     - yes
   * - ``.grd``
     - Raster
     - yes
     - yes
   * - ``.tif``
     - Raster
     - yes
     - yes
   * - ``.map``
     - Vector
     - yes
     - yes
   * - ``.gml``
     - Vector
     - yes
     - yes
   * - ``.gpkg``
     - Vector
     - yes
     - yes

All raster maps, regardless of the format, are read and written using:
 - :py:func:`windkit.read_raster_map`
 - :py:func:`windkit.raster_map_to_file`.

Similarly, all vector maps are read and written using:
 - :py:func:`windkit.read_vector_map`
 - :py:func:`windkit.vector_map_to_file`


Raster Maps
========================

To start, let's read some raster elevation data. The data covers part of the west coast of Jutland, Denmark:

.. ipython:: python
    :okwarning:

    elev_map_raster = wk.read_raster_map(
        "source/tutorials/data/elev.tif",
        map_type="elevation"
    )
    print(elev_map_raster)

Since the data is a ``xr.DataArray`` it is easy to visualize:

.. ipython:: python
     :okwarning:

    @savefig elev_raster_plot_example_ll.png width=6in
    elev_map_raster.plot(cmap="viridis", vmin=0.0, vmax=60.0);

The raster is in latitude-longitude projection (EPSG:4326).
To reproject the data to a new raster in UTM coordinates, :py:func:`windkit.spatial.warp` can be used:

.. ipython:: python
    :okwarning:

    elev_map_raster = wk.spatial.warp(elev_map_raster, to_crs="EPSG:25832", method="cubic")

    @savefig elev_raster_plot_example_utm.png width=6in
    elev_map_raster.plot(cmap="viridis", vmin=0.0, vmax=60.0);

Warping to a new raster can create cells with missing data along the edges,
so to clip the raster to only include real data, we will create a bounding box and clip to its bounds:

.. ipython:: python
    :okwarning:

    bbox = wk.spatial.BBox.from_cornerpts(
        minx=433_000,
        miny=6_245_000.0,
        maxx=468_000,
        maxy=6_280_000,
        crs="EPSG:25832"
    )

    elev_map_raster = wk.spatial.clip(elev_map_raster, bbox)

    @savefig elev_raster_plot_example_clipped.png width=6in
    elev_map_raster.plot(cmap="viridis", vmin=0.0, vmax=60.0);


While WindKit and PyWAsP have great support for working with both raster and vector maps and the PyWAsP
terrain model can work with elevation maps as both rasters and vector maps, for land cover maps PyWAsP expects
vector maps as input. Therefore, PyWAsP enables conversion from raster maps to vector maps, through the
:py:func:`pywasp.io.rastermap_to_vectormap` function.

.. ipython:: python
    :okwarning:

    elev_map_vector = pw.io.rastermap_to_vectormap(elev_map_raster)

    fig, ax = plt.subplots(1, 1, figsize=(6, 6))
    elev_map_raster.plot(ax=ax, cmap="Greys_r", vmin=0.0, vmax=60.0, add_colorbar=False)

    @savefig elev_vector_plot_example1.png width=6in
    elev_map_vector.plot("elev", ax=ax, legend=True, legend_kwds={"label": "Elevation [m]"});


Vector Maps
========================

To further illustrate how to work with vector maps, let's read some land cover data from the Serra Santa Luzia site.
Since the data comes in a ``.map``, which does not hold information about the
coordinate reference system, and, because it can hold both roughness and elevation information, we
have to provide the ``crs`` value and ask for the "roughness" part of the data via the ``map_type="roughness"`` argument.
Remember, the roughness map is converted to land cover classes by windkit.

.. ipython:: python
    :okwarning:

    lc_map_vector, lc_tbl = wk.read_vector_map(
        "source/tutorials/data/SerraSantaLuzia.map",
        map_type="roughness",
        crs="EPSG:32629",
    )
    print(lc_map_vector)

Vector maps are :py:class:`geopandas.GeoDataFrame` objects with :py:class:`shapely.LineString` geometries associated with either land cover boundaries or elevation levels.
Here, we have just two columns of data, the geometry column (for the :py:class:`shapely.LineString`'s') and the elevation column "elev".

Since vector maps are :py:class:`geopandas.GeoDataFrame` objects, they are easy to inspect and plot.
To avoid too much clutter, we will only plot lines where some specific classes are present (ocean and one forest category):

.. ipython:: python
    :okwarning:

    fig, ax = plt.subplots(1, 1, figsize=(6, 6))
    ax.set_facecolor("black")
    cats = [3, 4]
    mask = lc_map_vector.id_left.isin(cats) | lc_map_vector.id_right.isin(cats)
    lc_map_vector.loc[mask].plot(
        "id_left",
        cmap="tab20",
        vmin=-0.5,
        vmax=19.5,
        linewidth=2,
        ax=ax
    );
    @savefig elev_vector_plot_example2.png width=8in align=center
    lc_map_vector.loc[mask].plot(
        "id_right",
        cmap="tab20",
        vmin=-0.5,
        vmax=19.5,
        ax=ax,
        linewidth=1,
        linestyle="--",
        legend=True,
        legend_kwds={"label": "Land cover category", "ticks": list(range(13))},
    );

The way we plot the roughness-change lines, each line has two colors: the index for the "left" and "right" land cover category.
The lines represent jumps from one type of land cover to another.
The land cover table holds the information about the classes and their associated surface roughnesses and displacement heights:

.. ipython:: python

    print(lc_tbl)


Preparing Input for Terrain Modeling
====================================

To predict site effects from the Topography data with PyWAsP, the data is bundled together
in the :class:`pywasp.wasp.TopographyMap` PyWAsP class object.
It takes as input an elevation vector map, a land cover vector map, and a land cover table, as input.

.. ipython:: python
    :okwarning:

    elev_map_vector = wk.read_vector_map(
        "source/tutorials/data/SerraSantaLuzia.map",
        map_type="elevation",
        crs="EPSG:32629",
    )

    topo_map = pw.wasp.TopographyMap(
        elev_map_vector,
        lc_map_vector,
        lc_tbl
    )
    print(topo_map)


Topography maps can be saved to, and loaded from, a ZipFile archive using the :py:meth:`pywasp.wasp.TopographyMap.save` and :py:func:`pywasp.wasp.TopographyMap.load` methods.

In :ref:`wasp_flow_model` we describe the WAsP models in more details and show how terrain effects can be calculated
from a ``topo_map``, like the one above.

Best practices for working with roughness maps
==============================================

Roughness maps can come from many different sources and can be of varying quality and resolution.
When working with roughness maps, it is important to consider the following best practices for making them
suitable for use in WAsP:

1. **Water bodies have 0.0 roughness**: Water bodies should have a roughness value of 0.0, this is the signal to WAsP that the surface is water.
    During calculations in WAsP, the roughness value of 0.0 is replaced with the water roughness value set in the :py:class:`pw.wasp.Config` (default is 0.0002).
    This is important for the stability model of WAsP, as it uses different stability functions for water and land.

2. **Land roughness values should be in the range [0.0002, 5.0]**: Roughness values should be in the range [0.0002, 5.0] for land surfaces.
    WAsP assumes the lowest roughness to be the water roughness value (0.0002) and the highest roughness to be 5.0. Any land roughness values outside this range
    can cause problems in WAsP. If a lower water roughness value was set in the WAsP Config, the lower limit is adjusted accordingly.

3. **Keep the number of unique roughness values to a reasonable number**: WindKit reads roughness maps and converts them to land cover classes.
    The number of unique roughness values in the roughness map should be kept to a reasonable number to avoid too many land cover classes. The suitable number of unique roughness values
    depends on the application. PyWAsP allows up to 100, but typically 5-50 unique roughness values are sufficient. Internally, WAsP uses a limited number of roughness-change events per sector, so having too many
    unique roughness values dont add any value.

In the future, WindKit will provide tools to preprocess roughness maps to adhere to these best practices. In the meantime, ``QGIS``, ``xarray``, ``xarray-spatial``, and other GIS tools can be used.