xrspatial.flood.vegetation_roughness#

xrspatial.flood.vegetation_roughness(vegetation_agg: DataArray, mode: str = 'nlcd', lookup: dict | None = None, name: str = 'mannings_n') → DataArray[source]#

Derive Manning’s n roughness from land cover or NDVI.

Parameters:

  • vegetation_agg (xarray.DataArray) – 2D raster. For mode='nlcd' this should contain integer NLCD land cover codes. For mode='ndvi' this should contain continuous NDVI values (typically -1 to 1).

  • mode ({'nlcd', 'ndvi'}, default 'nlcd') –

    How to convert vegetation data to roughness.

    • 'nlcd': categorical lookup from NLCD codes to Manning’s n.

    • 'ndvi': piecewise linear interpolation of NDVI to Manning’s n.

  • lookup (dict, optional) – Override the default NLCD-to-n mapping. Keys are integer NLCD codes, values are Manning’s n floats. Only used when mode='nlcd'.

  • name (str, default 'mannings_n') – Name of the output DataArray.

Returns:

2D float64 Manning’s n raster. Unrecognized NLCD codes and NaN inputs map to NaN.

Return type:

xarray.DataArray

Notes

Supports NumPy, CuPy, Dask with NumPy, and Dask with CuPy backed xarray DataArrays.

Examples

>>> import numpy as np
>>> import xarray as xr
>>> from xrspatial import vegetation_roughness
>>> nlcd = xr.DataArray(
...     np.array([[41, 71], [11, 82]], dtype=np.int32),
...     dims=['y', 'x'])
>>> roughness = vegetation_roughness(nlcd, mode='nlcd')