eumap.gapfiller.SSA

class SSA(fn_files=None, data=None, season_size=4, max_gap_pct=0.8, ltm_resolution=5, window_size=4, ngroups=4, reconstruct_ngroups=2, outlier_remover=None, std_win=3, std_env=2, perc_env=[2, 98], n_jobs_io=4, verbose=True)[source]

Bases: eumap.gapfiller.ImageGapfill

Approach that uses a Singular Spectral Analysis (SSA [1]) to gapfill the missing values and smooth all the raster data. The missing values are first gapfilled using a long-term median strategy derived over values from other days/months/seasons. Later the SSA is uses to decompose each time series in multiple components (ngroups), considering only part of them to reconstruct the output time series. (reconstruct_ngroups).

Parameters

  • fn_files (Optional[List]) – Raster file paths to be read and gapfilled.

  • data (Optional[array]) – 3D array where the last dimension is the time.

  • season_size (int) – Season size of a year used to calculate the long-term median (for monthly time series it is equal 12).

  • max_gap_pct (int) – Max percentage allowed to run the approach. For pixels where this condition is satisfied the result is np.nan for all dates.

  • ltm_resolution (int) – Number of years used to calculate the long-term median.

  • window_size (int) – Size of the sliding window (i.e. the size of each word). If float, it represents the percentage of the size of each time series and must be between 0 and 1. The window size will be computed as max(2, ceil(window_size * n_timestamps)) [1].

  • ngroups (int) – Number of components used to decompose the time series [1].

  • reconstruct_ngroups (int) – Number of components used to reconstruct the time series.

  • outlier_remover (Optional[OutlierRemover]) – Strategy to remove outliers.

  • std_win (int) – Temporal window size used to calculate a local median and std.

  • std_env (int) – Number of std used to define a local envelope around the median. Values outside of this envelope are removed.

  • perc_env (list) – A list containing the lower and upper percentiles used to defined a global envelope for the time series. Values outside of this envelope are removed.

  • n_jobs_io – Number of parallel jobs to read/write raster files.

  • verbose – Use True to print the progress of the gapfilled.

References

[1] Pyts SingularSpectrumAnalysis

Examples

>>> from eumap import gapfiller
>>>
>>> # For a 4-season time series
>>> ssa = gapfiller.SSA(fn_files=fn_rasters, season_size=4)
>>> data_ssa = ssa.run()
>>>
>>> fn_rasters_ssa = ssa.save_rasters('./gapfilled_ssa', dtype='uint8', save_flag=False)

Methods

gapfill_ltm

run

Execute the gapfilling approach.

save_rasters

Save the result in raster files maintaining the same filenames of the read rasters.
run()

Execute the gapfilling approach.

save_rasters(out_dir, dtype=None, out_mantain_subdirs=True, root_dir_name='eumap_data', fn_files=None, nodata=None, spatial_win=None, save_flag=True)

Save the result in raster files maintaining the same filenames of the read rasters.

Parameters

  • out_dir – Folder path to save the files.

  • dtype (Optional[str]) – Convert the rasters for the specified Numpy dtype before save. This argument overwrite the values retrieved of fn_files

  • out_mantain_subdirs (bool) – Keep the full folder hierarchy of the read raster in the out_dir.

  • root_dir_name (str) – Keep the relative folder hierarchy of the read raster in the out_dir considering of the sub folders of root_dir_name.

  • fn_files (Optional[List]) – Raster file paths to retrieve the filenames and folders. Use this parameter in situations where the data parameter is informed in the class constructor. The pixel size, crs, extent, image size and nodata for the gapfilled rasters are retrieved from the first valid raster of fn_files

  • nodata – Nodata value used for the the gapfilled rasters. This argument overwrite the values retrieved of fn_files. This argument doesn’t affect the flag rasters (gapfill summary), which have nodata=0.

  • spatial_win (Optional[Window]) – Save the gapfilled rasters considering the specified spatial window.

  • save_flag – Save the flag rasters (gapfill summary).