ntlMisc

extract_monthly_ntl(aoi, out_folder, sel_files=[])¶

Description:

Extract monthly nighttime lights imagery from AWS S3 for an area of interest and save to an output folder.

Parameters:

• aoi (geopandas.GeoDataFrame): Polygonal area of interest to extract imagery for.

• out_folder (str): Path to the folder to save extracted imagery.

• sel_files (list, optional): Files to extract; defaults to all returned from gostrocks.dataMisc.aws_search_ntl().

Returns:

• None: Writes output and returns nothing.

read_raster_box(curRaster, geometry, bandNum=1)¶

Description:

Read a section of a rasterio object with a specified geometry.

Parameters:

• curRaster (rasterio.DatasetReader): Raster file to read from.

• geometry (shapely.geometry): Geometry to read from raster.

• bandNum (int, optional): Band in curRaster to read, defaults to 1.

Returns:

• numpy.ndarray: Array of raster values from curRaster within geometry.

calc_annual(df, extent, agg_method='MEAN')¶

Description:

Combine monthly nighttime lights images into an annual composite.

Parameters:

• df (pandas.DataFrame): Data frame of images with columns YEAR, MONTH, PATH.

• extent (shapely.Polygon): Area to extract imagery from.

• agg_method (str, optional): Aggregation method, defaults to MEAN.

generate_annual_composites(aoi, agg_method='MEAN', sel_files=[], out_folder='')¶

Description:

Collapse several monthly nighttime lights images into an annual composite.

Parameters:

• aoi (geopandas.GeoDataFrame): Polygonal dataframe to use for clip extent.

• agg_method (str, optional): Aggregation method, defaults to MEAN.

• sel_files (list, optional): NTL files to process; defaults to [] (uses gostrocks.dataMisc.aws_search_ntl).

• out_folder (str, optional): Output folder path; empty string skips writing.

Returns:

• None: Writes output and returns nothing.

map_viirs(cur_file, out_file='', class_bins=[-10, 0.5, 1, 2, 3, 5, 10, 15, 20, 30, 40, 50], text_x=0, text_y=5, dpi=100)¶

Description:

Map VIIRS nighttime lights imagery and optionally create an output image.

Parameters:

• cur_file (str): Path to input GeoTIFF.

• out_file (str, optional): Path to create output image; empty string skips writing.

• class_bins (list[float], optional): Breaks for applying colour ramp, defaults to [-10, 0.5, 1, 2, 3, 5, 10, 15, 20, 30, 40, 50].

• text_x (int, optional): X position for year text, defaults to 0.

• text_y (int, optional): Y position for year text, defaults to 5.

• dpi (int, optional): Dots per inch for output image, defaults to 100.

Returns:

• matplotlib.pyplot: Matplotlib object containing the map.

run_zonal(inD, ntl_files=[], minval=0.1, verbose=False, calc_sd=True)¶

Description:

Run zonal statistics against a series of nighttime lights files.

Parameters:

• inD (gpd.GeoDataFrame): Input GeoDataFrame to summarize results within.

• ntl_files (list, optional): NTL files to summarize; defaults to searching S3 using dataMisc.aws_search_ntl().

• minval (float, optional): Minimum value to summarize; values below become 0, defaults to 0.1.

• verbose (bool, optional): Print additional information, defaults to False.

• calc_sd (bool, optional): Calculate standard deviation alongside summary stats, defaults to True.