.. _band_math:

Band math
=========

Vegetation indices
------------------

Enhanced Vegetation Index (EVI)
-------------------------------

.. ipython:: python

    import geowombat as gw
    from geowombat.data import rgbn

Calculate a vegetation index, returning an :class:`xarray.DataArray`.

.. ipython:: python

    with gw.open(rgbn) as ds:
        print(ds)
        evi = ds.gw.evi(sensor='rgbn', scale_factor=0.0001)
        print(evi)

Use the configuration context to set parameters.

.. ipython:: python

    with gw.config.update(sensor='rgbn', scale_factor=0.0001):
        with gw.open(rgbn) as ds:
            evi = ds.gw.evi()
            print(evi)

Two-band Enhanced Vegetation Index (EVI2)
-----------------------------------------

.. ipython:: python

    with gw.config.update(sensor='rgbn', scale_factor=0.0001):
        with gw.open(rgbn) as ds:
            evi2 = ds.gw.evi2()
            print(evi2)

Normalized difference indices
-----------------------------

Use the generic :func:`xarray.DataArray.gw.norm_diff` function with any two-band combination.

.. ipython:: python

    with gw.config.update(sensor='rgbn'):
        with gw.open(rgbn) as ds:
            d = ds.gw.norm_diff('red', 'nir')
            print(d)

Tasseled cap transformations
----------------------------

.. ipython:: python

    with gw.config.update(sensor='qb', scale_factor=0.0001):
        with gw.open(rgbn) as ds:
            tcap = ds.gw.tasseled_cap()
            print(tcap)

Additional useful indices are available, such as the normalized burned ratio (NBR) and woody index (WI). For a
full list of indices, see the `API docs <https://geowombat.readthedocs.io/en/latest/api.html>`_