geoutils.SatelliteImage

class geoutils.SatelliteImage(filename_or_dataset, load_data=True, bands=None, read_from_fn=True, datetime=None, tile_name=None, satellite=None, sensor=None, product=None, version=None, read_from_meta=True, fn_meta=None, silent=True)

__init__(filename_or_dataset, load_data=True, bands=None, read_from_fn=True, datetime=None, tile_name=None, satellite=None, sensor=None, product=None, version=None, read_from_meta=True, fn_meta=None, silent=True)

Load satellite data through the Raster class and parse additional attributes from filename or metadata.

Parameters:

• filename_or_dataset (Union[str, TypeVar(RasterType, bound= Raster), DatasetReader, MemoryFile]) – The filename of the dataset.

• load_data (bool) – Load the raster data into the object. Default is True.

• bands (int | list[int] | None) – The band(s) to load into the object. Default is to load all bands.

• read_from_fn (bool) – Try to read metadata from the filename

• datetime (datetime | None) – Provide datetime attribute

• tile_name (str | None) – Provide tile name

• satellite (str | None) – Provide satellite name

• sensor (str | None) – Provide sensor name

• product (str | None) – Provide data product name

• version (str | None) – Provide data version

• read_from_meta (bool) – Try to read metadata from known associated metadata files

• fn_meta (str | None) – Provide filename of associated metadata

• silent (bool) – No informative output when trying to read metadata

Returns:

A SatelliteImage object (Raster subclass)

Methods

__init__(filename_or_dataset[, load_data, ...])	Load satellite data through the Raster class and parse additional attributes from filename or metadata.
astype(dtype[, convert_nodata, inplace])	Convert data type of the raster.
coords([grid, shift_area_or_point, force_offset])	Get coordinates (x,y) of all pixels in the raster.
copy([new_array, cast_nodata])	Copy the raster in-memory.
crop(crop_geom[, mode, inplace])	Crop the raster to a given extent.
from_array(data, transform, crs[, nodata, ...])	Create a raster from a numpy array and the georeferencing information.
from_xarray(ds[, dtype])	Create raster from a xarray.DataArray.
georeferenced_grid_equal(raster)	Check that raster shape, geotransform and CRS are equal.
get_bounds_projected(out_crs[, densify_points])	Get raster bounds projected in a specified CRS.
get_footprint_projected(out_crs[, ...])	Get raster footprint projected in a specified CRS.
get_mask()	Get mask of invalid values from the raster.
get_metric_crs([local_crs_type, method])	Get local metric coordinate reference system for the raster (UTM, UPS, or custom Mercator or Polar).
get_nanarray([return_mask])	Get NaN array from the raster.
ij2xy(i, j[, shift_area_or_point, force_offset])	Get coordinates (x,y) of indexes (row,column).
info([stats, verbose])	Print summary information about the raster.
interp_points(points[, method, band, ...])	Interpolate raster values at a set of points.
intersection(raster[, match_ref])	Returns the bounding box of intersection between this image and another.
load([bands])	Load the raster array from disk.
outside_image(xi, yj[, index])	Check whether a given point falls outside the raster.
plot([bands, cmap, vmin, vmax, alpha, ...])	Plot the raster, with axes in projection of image.
polygonize([target_values])	Polygonize the raster into a vector.
proximity([vector, target_values, ...])	Compute proximity distances to the raster target pixels, or to a vector geometry on the raster grid.
raster_equal(other[, strict_masked, ...])	Check if two rasters are equal.
reproject([ref, crs, res, grid_size, ...])	Reproject raster to a different geotransform (resolution, bounds) and/or coordinate reference system (CRS).
save(filename[, driver, dtype, nodata, ...])	Write the raster to file.
set_area_or_point(new_area_or_point[, ...])	Set new pixel interpretation of the raster.
set_mask(mask)	Set a mask on the raster array.
set_nodata(new_nodata[, update_array, ...])	Set a new nodata value for all bands.
shift(xoff, yoff[, distance_unit, inplace])	Shift a raster by a (x,y) offset.
split_bands([copy, bands])	Split the bands into separate rasters.
subsample(subsample[, return_indices, ...])	Randomly sample the raster.
to_pointcloud([data_column_name, data_band, ...])	Convert raster to point cloud.
to_points(**kwargs)
to_rio_dataset()	Export to a Rasterio in-memory dataset.
to_xarray([name])	Convert raster to a xarray.DataArray.
value_at_coords(x, y[, latlon, band, ...])	Extract raster values at the nearest pixels from the specified coordinates, or reduced (e.g., mean of pixels) from a window around the specified coordinates.
xy2ij(x, y[, op, precision, shift_area_or_point])	Get indexes (row,column) of coordinates (x,y).

Attributes

area_or_point	Pixel interpretation of the raster.
bands	Band indexes loaded in memory if they are, otherwise on disk.
bands_on_disk	Band indexes on disk if a file exists.
bounds	Bounding coordinates of the raster.
count	Count of bands loaded in memory if they are, otherwise the one on disk.
count_on_disk	Count of bands on disk if it exists.
crs	Coordinate reference system of the raster.
data	Array of the raster.
datetime
driver	Driver used to read a file on disk.
dtype	Data type of the raster (string representation).
height	Height of the raster in pixels.
indexes	Band indexes (duplicate of .bands attribute, mirroring Rasterio naming "indexes").
is_loaded	Whether the raster array is loaded.
is_modified	Whether the array has been modified since it was loaded from disk.
name	Name of the file on disk, if it exists.
nodata	Nodata value of the raster.
product
res	Resolution (X, Y) of the raster in georeferenced units.
satellite
sensor
shape	Shape (i.e., height, width) of the raster in pixels.
tile_name
transform	Geotransform of the raster.
version
width	Width of the raster in pixels.
date