A collection of python scripts for interacting with the NetCDF files produced for the Seasonal Urban Backscatter (1993 - 2020) dataset submitted to Scientific Data August 2021. The data paper only describes the "seasonal" data set but this repository also includes scripts to work with the monthly data.

This is a collection of scripts used to extract CSV files from the seasonal and monthly NetCDF data files. The scripts have been developed in a miniconda. environment. You can recreate the equivalent environment using the environment.yml file:

conda env create --file environment.yml
conda activate urban_backscatter

Once you place the NetCDF data files in the "data" directory you should be able to run the test scripts by typing pytest.

There are three scripts in the src/urban_backscatter directory:

extract_grid_cells_from_seasonal.py:

usage: extract_grid_cells_from_seasonal.py [-h] [-s {JFM,AMJ,JAS,OND}] [-v] [-d [DATADIR]]
                                           lat lon locname

create CSV with values for each grid cell in a 11x11 rectangular region around a lat-lon location.

positional arguments:
  lat                   Latitude of location
  lon                   Longitude (-180-180) of location
  locname               location name

optional arguments:
  -h, --help            show this help message and exit
  -s {JFM,AMJ,JAS,OND}, --season {JFM,AMJ,JAS,OND}
                        season/quarter to select
  -v, --verbose         increase output verbosity
  -d [DATADIR], --datadir [DATADIR]
                        data directory for output and finding netcdf files

extract_grid_cells_from_monthly.py:

usage: extract_grid_cells_from_monthly.py [-h] [-v] [-d [DATADIR]] lat lon locname

create CSV with values for each grid grid cell in a 11x11 rectangular region around a lat-lon
location.

positional arguments:
  lat                   Latitude of location
  lon                   Longitude (-180-180) of location
  locname               location name

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         increase output verbosity
  -d [DATADIR], --datadir [DATADIR]
                        data directory for output and finding netcdf files

plot_seasonal_timeseries.py:

usage: plot_seasonal_timeseries.py [-h] [-s {JFM,AMJ,JAS,OND}] [-v] [-d [DATADIR]] lat lon locname

create CSV with values for each grid grid cell in a rectangular region around a lat-lon location.

positional arguments:
  lat                   Latitude of location
  lon                   Longitude (-180-180) of location
  locname               location name

optional arguments:
  -h, --help            show this help message and exit
  -s {JFM,AMJ,JAS,OND}, --season {JFM,AMJ,JAS,OND}
                        season/quarter to select
  -v, --verbose         increase output verbosity
  -d [DATADIR], --datadir [DATADIR]
                        data directory for output and finding netcdf files

This project has been set up using PyScaffold 4.0.1. For details and usage information on PyScaffold see https://pyscaffold.org/.