xrspatial.multispectral.mndwi#

xrspatial.multispectral.mndwi(green_agg: DataArray, swir_agg: DataArray, name='mndwi')[source]#

Computes Modified Normalized Difference Water Index (MNDWI).

MNDWI improves on NDWI for urban areas by substituting SWIR for NIR, which reduces false positives from built-up surfaces.

Parameters:

  • green_agg (xr.DataArray) – 2D array of green band data. (Landsat 8: Band 3) (Sentinel-2: Band 3)

  • swir_agg (xr.DataArray) – 2D array of shortwave infrared band data. (Landsat 8: Band 6) (Sentinel-2: Band 11)

  • name (str, default='mndwi') – Name of output DataArray.

  • Alternatively

  • first (a single xr.Dataset may be passed as the)

  • Dataset (argument with keyword arguments mapping band names to)

  • example:: (variables. For) – mndwi(ds, green=’B3’, swir=’B11’)

Returns:

mndwi_agg – 2D array of mndwi values in the range [-1, 1]. All other input attributes are preserved.

Return type:

xr.DataArray of same type as inputs

References

  • Xu, H., 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), pp.3025-3033.

Examples

>>> import numpy as np
>>> import xarray as xr
>>> from xrspatial.multispectral import mndwi
>>> green = xr.DataArray(np.array([[600., 500.], [400., 300.]]))
>>> swir = xr.DataArray(np.array([[300., 400.], [500., 600.]]))
>>> mndwi(green, swir).values
array([[ 0.33333334,  0.11111111],
       [-0.11111111, -0.33333334]], dtype=float32)
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