xrspatial.aspect.aspect#
- xrspatial.aspect.aspect(agg: xarray.core.dataarray.DataArray, name: Optional[str] = 'aspect') xarray.core.dataarray.DataArray[source]#
Calculates the aspect value of an elevation aggregate.
Calculates, for all cells in the array, the downward slope direction of each cell based on the elevation of its neighbors in a 3x3 grid. The value is measured clockwise in degrees with 0 (due north), and 360 (again due north). Values along the edges are not calculated.
Direction of the aspect can be determined by its value: From 0 to 22.5: North From 22.5 to 67.5: Northeast From 67.5 to 112.5: East From 112.5 to 157.5: Southeast From 157.5 to 202.5: South From 202.5 to 247.5: West From 247.5 to 292.5: Northwest From 337.5 to 360: North
Note that values of -1 denote flat areas.
- Parameters
agg (xarray.DataArray) – 2D NumPy, CuPy, or Dask with NumPy-backed xarray DataArray of elevation values.
name (str, default='aspect') – Name of ouput DataArray.
- Returns
aspect_agg – 2D aggregate array of calculated aspect values. All other input attributes are preserved.
- Return type
xarray.DataArray of the same type as agg
References
Examples
Aspect works with NumPy backed xarray DataArray .. sourcecode:: python
>>> import numpy as np >>> import xarray as xr >>> from xrspatial import aspect
>>> data = np.array([ [1, 1, 1, 1, 1], [1, 1, 1, 2, 0], [1, 1, 1, 0, 0], [4, 4, 9, 2, 4], [1, 5, 0, 1, 4], [1, 5, 0, 5, 5] ], dtype=np.float32) >>> raster = xr.DataArray(data, dims=['y', 'x'], name='raster') >>> print(raster) <xarray.DataArray 'raster' (y: 6, x: 5)> array([[1., 1., 1., 1., 1.], [1., 1., 1., 2., 0.], [1., 1., 1., 0., 0.], [4., 4., 9., 2., 4.], [1., 5., 0., 1., 4.], [1., 5., 0., 5., 5.]]) Dimensions without coordinates: y, x >>> aspect_agg = aspect(raster) >>> print(aspect_agg) <xarray.DataArray 'aspect' (y: 6, x: 5)> array([[ nan, nan , nan , nan , nan], [ nan, -1. , 225. , 135. , nan], [ nan, 343.61045967, 8.97262661, 33.69006753, nan], [ nan, 307.87498365, 71.56505118, 54.46232221, nan], [ nan, 191.30993247, 144.46232221, 255.96375653, nan], [ nan, nan , nan , nan , nan]]) Dimensions without coordinates: y, x
Aspect works with Dask with NumPy backed xarray DataArray .. sourcecode:: python
>>> import dask.array as da >>> data_da = da.from_array(data, chunks=(3, 3)) >>> raster_da = xr.DataArray(data_da, dims=['y', 'x'], name='raster_da') >>> print(raster_da) <xarray.DataArray 'raster' (y: 6, x: 5)> dask.array<array, shape=(6, 5), dtype=int64, chunksize=(3, 3), chunktype=numpy.ndarray> Dimensions without coordinates: y, x >>> aspect_da = aspect(raster_da) >>> print(aspect_da) <xarray.DataArray 'aspect' (y: 6, x: 5)> dask.array<_trim, shape=(6, 5), dtype=float32, chunksize=(3, 3), chunktype=numpy.ndarray> Dimensions without coordinates: y, x >>> print(aspect_da.compute()) # compute the results <xarray.DataArray 'aspect' (y: 6, x: 5)> array([[ nan, nan , nan , nan , nan], [ nan, -1. , 225. , 135. , nan], [ nan, 343.61045967, 8.97262661, 33.69006753, nan], [ nan, 307.87498365, 71.56505118, 54.46232221, nan], [ nan, 191.30993247, 144.46232221, 255.96375653, nan], [ nan, nan , nan , nan , nan]]) Dimensions without coordinates: y, x
Aspect works with CuPy backed xarray DataArray. Make sure you have a GPU and CuPy installed to run this example. .. sourcecode:: python
>>> import cupy >>> data_cupy = cupy.asarray(data) >>> raster_cupy = xr.DataArray(data_cupy, dims=['y', 'x']) >>> aspect_cupy = aspect(raster_cupy) >>> print(type(aspect_cupy.data)) <class 'cupy.core.core.ndarray'> >>> print(aspect_cupy) <xarray.DataArray 'aspect' (y: 6, x: 5)> array([[ nan, nan, nan, nan, nan], [ nan, -1., 225., 135., nan], [ nan, 343.61047, 8.972626, 33.690067, nan], [ nan, 307.87497, 71.56505 , 54.462322, nan], [ nan, 191.30994, 144.46233 , 255.96376, nan], [ nan, nan, nan, nan, nan]], dtype=float32) Dimensions without coordinates: y, x