xrspatial.multispectral.nbr#
- xrspatial.multispectral.nbr(nir_agg: xarray.core.dataarray.DataArray, swir2_agg: xarray.core.dataarray.DataArray, name='nbr')[source]#
Computes Normalized Burn Ratio. Used to identify burned areas and provide a measure of burn severity.
- Parameters
nir_agg (xr.DataArray) – 2D array of near-infrared band.
swir_agg (xr.DataArray) – 2D array of shortwave infrared band. (Landsat 4-7: Band 6) (Landsat 8: Band 7)
name (str, default='nbr') – Name of output DataArray.
- Returns
nbr_agg – 2D array of nbr values. All other input attributes are preserved.
- Return type
xr.DataArray of the same type as inputs
References
Examples
>>> from xrspatial.datasets import get_data >>> data = get_data('sentinel-2') # Open Example Data >>> nir = data['NIR'] >>> swir2 = data['SWIR2'] >>> from xrspatial.multispectral import nbr >>> # Generate NBR Aggregate Array >>> nbr_agg = nbr(nir_agg=nir, swir2_agg=swir2) >>> nir.plot(aspect=2, size=4) >>> swir2.plot(aspect=2, size=4) >>> nbr_agg.plot(aspect=2, size=4)
>>> y1, x1, y2, x2 = 100, 100, 103, 104 >>> print(nir[y1:y2, x1:x2].data) [[1519. 1504. 1530. 1589.] [1491. 1473. 1542. 1609.] [1479. 1461. 1592. 1653.]] >>> print(swir2[y1:y2, x1:x2].data) [[1866. 1962. 2086. 2112.] [1811. 1900. 2012. 2041.] [1838. 1956. 2067. 2109.]] >>> print(nbr_agg[y1:y2, x1:x2].data) [[-0.10251108 -0.1321408 -0.15376106 -0.14131317] [-0.09691096 -0.12659353 -0.13224536 -0.11835616] [-0.10823033 -0.14486392 -0.12981689 -0.12121212]]