Collection

class aeronet.dataset.raster.BandCollection(bands)

Bases: aeronet.dataset.raster.geoobject.GeoObject

A collection of Band s with the same crs, transform and shape.

It is intended to contain a multi-band image and associated raster masks. All the bands must have the same resolution, so if the initial images have different resolution, they must be resampled previously. Every band must be stored in a separate file; if the initial data is in one file, use aeronet.converters.split.split() to split it to separate files

Parameters:bands – list of Band or list of file paths

crs

Geographic coordinate reference system of the object Returns a rasterio.CRS

transform

Transform matrix as the affine.Affine object. This transform maps pixel row/column coordinates to coordinates in the dataset’s coordinate reference system.

nodata

The value that should be interpreted as ‘No data’. May be None or a value within dtype range

height

Height of the raster data object in pixels

width

Width of the raster data object in pixels

count

(int) number of channels/bands.

bounds

Georeferenced bounds - bounding box in the CRS of the image, based on transform and shape

shape

(count, height, width); or (height, width)

Type:Dimensions of the raster in pixels, a tuple of int

res

Resolution (or ground sampling distance) along X and Y axes in units of the CRS. Tuple (x_resolution, y_resolution)

is_valid

Check if all bands have the same resolution, shape and coordinate system

append(other)

Add a band to collection, checking it to be compatible by shape, transform and crs

sample(y, x, height, width)

Sample memory object from BandCollection.

Parameters:

• x – int, top left corner X offset in pixels
• y – int, top left corner Y offset in pixels
• width – int, width of samples in pixels
• height – int, height of samples in pixels

Returns:

a new BandCollectionSample containing the specified spatial subset of the BandCollection

ordered(*names)

Creates a new object, containing the specified bands in the specific order.

Parameters:*names – order of names Returns:reordered BandCollection

reproject(dst_crs, directory=None, interpolation='nearest')

Reprojects every Band of the collection, see Band.reproject() and returns a new reprojected BandCollection

reproject_to_utm(directory=None, interpolation='nearest')

Alias of reproject method with automatic utm zone determining

resample(dst_res, directory=None, interpolation='nearest')

Resamples every Band of the collection, see Band.resample() and returns a new reprojected BandCollection

generate_samples(height, width)

A generator for sequential sampling of the whole BandCollection, used for the windowed reading of the raster. It allows to handle and process large files without reading them at once in the memory.

Parameters:

• width (int) – dimension of sample in pixels and step along X axis
• height (int) – dimension of sample in pixels and step along Y axis

Yields:

BandCollectionSample – sequential samples of the specified dimensions

numpy()

profile

A joint representation of the main properties

Returns:{ ‘crs’: crs, ‘nodata’: nodata, ‘transform’: transform } Return type:Dict

class aeronet.dataset.raster.BandCollectionSample(samples)

Bases: aeronet.dataset.raster.geoobject.GeoObject

A collection of BandSample , which are also

crs

Geographic coordinate reference system of the object Returns a rasterio.CRS

transform

Transform matrix as the affine.Affine object. This transform maps pixel row/column coordinates to coordinates in the dataset’s coordinate reference system.

res

Resolution (or ground sampling distance) along X and Y axes in units of the CRS. Tuple (x_resolution, y_resolution)

width

Width of the raster data object in pixels

height

Height of the raster data object in pixels

count

Number of bands (layers) in the collection

shape

(count, height, width); or (height, width)

Type:Dimensions of the raster in pixels, a tuple of int

nodata

The value that should be interpreted as ‘No data’. May be None or a value within dtype range

bounds

Georeferenced bounds - bounding box in the CRS of the image, based on transform and shape

is_valid

Check if all bands have the same resolution, shape and coordinate system

append(obj)

Add sample to collection, checking it to be compatible by shape, transform and crs

sample(y, x, height, width)

reproject(dst_crs, interpolation='nearest')

Reprojects every BandSample of the collection, see BandSample.reproject() and returns a new reprojected BandCollectionSample

reproject_to_utm(interpolation='nearest')

Alias of reproject method with automatic utm zone determining

resample(dst_res=None, dst_shape=None, interpolation='nearest')

Reprojects every BandSample of the collection, see BandSample.reproject() and returns a new reprojected BandCollectionSample

numpy()

ordered(*names)

Creates a new object, containing the specified bands in the specific order.

Parameters:*names – order of names Returns:reordered BandCollectionSample

save(directory, extension='.tif', **kwargs)

Saves every BandSample in the specified deirectory, see BandSample.save()

generate_samples(height, width)

A generator for sequential sampling of the BandCollectionSample similar to BandCollection, used for the windowed processing of the raster data.

Parameters:

• width (int) – dimension of sample in pixels and step along X axis
• height (int) – dimension of sample in pixels and step along Y axis

Yields:

BandCollectionSample – sequential samples of the specified dimensions

profile

A joint representation of the main properties

Returns:{ ‘crs’: crs, ‘nodata’: nodata, ‘transform’: transform } Return type:Dict