ds.rst.resample_at_points() or Raster.resample_at_points()

ds.rst.resample_at_points() or Raster.resample_at_points()#

RasterBase.resample_at_points(points, method=None, *, resampling=None, backend='auto', resampling_kwargs=None, coverage=None, band=1, input_latlon=False, as_array=False, nodata_handling=None, error_structure=None, window=None, window_shape=None, masked=False, boundless=True, **kwargs)[source]#

Resample raster values at points with a named interpolation or statistic.

Interpolation shares the SciPy and chunked paths of interp_at_points(). Statistics summarize a 3 x 3 window by default; pass window=5 to use five cells along each axis. Advanced callers can supply an Interpolator or Reducer for custom calculations or neighborhoods.

Parameters:

  • points (tuple[NDArray[floating[Any] | integer[Any]], NDArray[floating[Any] | integer[Any]]] | tuple[int | float | integer[Any] | floating[Any], int | float | integer[Any] | floating[Any]] | PointCloudBase | GeoDataFrame | DataArray) – X/Y coordinates or a point cloud defining the requested positions.

  • method (Literal['nearest', 'linear', 'bilinear', 'cubic', 'cubic_convolution', 'cubic_spline', 'lanczos', 'quintic', 'slinear', 'pchip', 'splinef2d', 'idw', 'inv_dist', 'kriging', 'mean', 'average', 'sum', 'median', 'med', 'quantile', 'q1', 'q3', 'mode', 'minimum', 'min', 'maximum', 'max', 'range', 'count', 'stdev', 'std', 'standard_deviation', 'rms', 'rmse', 'average_distance', 'average_distance_pts'] | Interpolator | Reducer | Callable[[NDArray[floating[Any] | integer[Any]]], float] | None) – Legacy alias for resampling, also accepting a reduction callable.

  • resampling (Literal['nearest', 'linear', 'bilinear', 'cubic', 'cubic_convolution', 'cubic_spline', 'lanczos', 'quintic', 'slinear', 'pchip', 'splinef2d', 'idw', 'inv_dist', 'kriging', 'mean', 'average', 'sum', 'median', 'med', 'quantile', 'q1', 'q3', 'mode', 'minimum', 'min', 'maximum', 'max', 'range', 'count', 'stdev', 'std', 'standard_deviation', 'rms', 'rmse', 'average_distance', 'average_distance_pts'] | Interpolator | Reducer | None) – Built-in method name, such as “linear”, “mean” or “median”, or an advanced operator. Defaults to the configured interpolation method.

  • backend (Literal['auto', 'gdal', 'scipy', 'numba', 'gstools', 'gpytorch']) – “auto” uses SciPy; “gstools” and “gpytorch” select a kriging solver.

  • resampling_kwargs (dict[str, Any] | None) – Method settings, such as a quantile q or a fitted kriging model.

  • coverage (Literal['center', 'all_touched', 'fractional'] | None) – Select cells by center, include all touched cells, or weight by covered area.

  • band (int) – Source band number, starting at one.

  • input_latlon (bool) – Convert tuple coordinates from longitude/latitude to the raster CRS.

  • as_array (bool) – Return values rather than a point cloud at the requested coordinates.

  • nodata_handling (Literal['nearest', 'ignore', 'propagate'] | Literal['half_order_up', 'half_order_down'] | int | None) – How missing source values affect the result. Reducers omit them by default. A distance choice also masks results near missing source cells.

  • error_structure (ErrorStructure | None) – Optional observation error model used for weighting and fitting. Use geoutils.uncertainty.propagate() to calculate output uncertainty.

  • window (int | None) – Optional odd window size for a reducer, overriding its configured neighborhood for this call.

  • window_shape (Literal['square', 'circular'] | None) – Use a square or circular window.

  • masked (bool) – Return a masked array when as_array=True.

  • boundless (bool) – Allow partial reduction windows at raster edges. If False, incomplete windows return NaN.

  • kwargs (Any) – Additional interp_at_points() options when method is an Interpolator or method name.

Return type:

Any

Returns:

Resampled values.