Resampling
Resampling in Satpy.
Satpy provides multiple resampling algorithms for resampling geolocated
data to uniform projected grids. The easiest way to perform resampling in
Satpy is through the Scene
object’s
resample()
method. Additional utility functions are
also available to assist in resampling data. Below is more information on
resampling with Satpy as well as links to the relevant API documentation for
available keyword arguments.
Resampling algorithms
Resampler |
Description |
Related |
---|---|---|
nearest |
Nearest Neighbor |
|
ewa |
Elliptical Weighted Averaging |
|
ewa_legacy |
Elliptical Weighted Averaging (Legacy) |
|
native |
Native |
|
bilinear |
Bilinear |
|
bucket_avg |
Average Bucket Resampling |
|
bucket_sum |
Sum Bucket Resampling |
|
bucket_count |
Count Bucket Resampling |
|
bucket_fraction |
Fraction Bucket Resampling |
|
gradient_search |
Gradient Search Resampling |
|
The resampling algorithm used can be specified with the resampler
keyword
argument and defaults to nearest
:
>>> scn = Scene(...)
>>> euro_scn = scn.resample('euro4', resampler='nearest')
Warning
Some resampling algorithms expect certain forms of data. For example, the EWA resampling expects polar-orbiting swath data and prefers if the data can be broken in to “scan lines”. See the API documentation for a specific algorithm for more information.
Resampling for comparison and composites
While all the resamplers can be used to put datasets of different resolutions on to a common area, the ‘native’ resampler is designed to match datasets to one resolution in the dataset’s original projection. This is extremely useful when generating composites between bands of different resolutions.
>>> new_scn = scn.resample(resampler='native')
By default this resamples to the
highest resolution area
(smallest footprint per
pixel) shared between the loaded datasets. You can easily specify the lowest
resolution area:
>>> new_scn = scn.resample(scn.coarsest_area(), resampler='native')
Providing an area that is neither the minimum or maximum resolution area may work, but behavior is currently undefined.
Caching for geostationary data
Satpy will do its best to reuse calculations performed to resample datasets,
but it can only do this for the current processing and will lose this
information when the process/script ends. Some resampling algorithms, like
nearest
and bilinear
, can benefit by caching intermediate data on disk in the directory
specified by cache_dir and using it next time. This is most beneficial with
geostationary satellite data where the locations of the source data and the
target pixels don’t change over time.
>>> new_scn = scn.resample('euro4', cache_dir='/path/to/cache_dir')
See the documentation for specific algorithms to see availability and limitations of caching for that algorithm.
Create custom area definition
See pyresample.geometry.AreaDefinition
for information on creating
areas that can be passed to the resample method:
>>> from pyresample.geometry import AreaDefinition
>>> my_area = AreaDefinition(...)
>>> local_scene = scn.resample(my_area)
Create dynamic area definition
See pyresample.geometry.DynamicAreaDefinition
for more information.
Examples coming soon…
Store area definitions
Area definitions can be saved to a custom YAML file (see pyresample’s writing to disk) and loaded using pyresample’s utility methods (pyresample’s loading from disk):
>>> from pyresample import load_area
>>> my_area = load_area('my_areas.yaml', 'my_area')
Or using satpy.resample.get_area_def()
, which will search through all
areas.yaml
files in your SATPY_CONFIG_PATH
:
>>> from satpy.resample import get_area_def
>>> area_eurol = get_area_def("eurol")
For examples of area definitions, see the file etc/areas.yaml
that is
included with Satpy and where all the area definitions shipped with Satpy are
defined.