ecoscope.analysis.seasons#

Module Contents#

ecoscope.analysis.seasons.logger#
ecoscope.analysis.seasons._min_max_scaler(x)[source]#
ecoscope.analysis.seasons.std_ndvi_vals(aoi, img_coll, start, nir_band=None, red_band=None, end=None, img_scale=1)[source]#
Parameters:

  • aoi (geopandas.GeoDataFrame | geopandas.GeoSeries | shapely.geometry.base.BaseGeometry)

  • img_coll (str)

  • start (str | datetime.datetime)

  • nir_band (str | None)

  • red_band (str | None)

  • end (str | datetime.datetime | None)

  • img_scale (int)

Return type:

pandas.DataFrame

ecoscope.analysis.seasons.val_cuts(vals, num_seasons=2)[source]#
Parameters:

  • vals (pandas.DataFrame)

  • num_seasons (int)

Return type:

list[float]

ecoscope.analysis.seasons.seasonal_windows(ndvi_vals, cuts, season_labels)[source]#
Parameters:

  • ndvi_vals (pandas.DataFrame)

  • cuts (list[float])

  • season_labels (list[str])

Return type:

pandas.DataFrame

ecoscope.analysis.seasons.add_seasonal_index(df, index_name, start_date, end_date, time_col, ndvi_vals, seasons=2, season_labels=None)[source]#
Parameters:

  • df (pandas.DataFrame)

  • index_name (str)

  • start_date (datetime.datetime)

  • end_date (datetime.datetime)

  • time_col (str)

  • ndvi_vals (geopandas.GeoDataFrame)

  • seasons (int)

  • season_labels (list[str] | None)

Return type:

pandas.DataFrame