swesarr-pytools 0.1.7

Library for data retrieval and processing of NASA GSFC Snow Water Equivalent Synthetic Aperture Radar and Radiometer data.

swesarr_pytools

Library for data retrieval and processing of NASA GSFC Snow Water Equivalent Synthetic Aperture Radar and Radiometer data.

swesarr_pytool is a python library created for data retrieval and processing of NASA GSFC Snow Water Equivalent Synthetic Aperture Radar and Radiometer data..

The Snow Water Equivalent Synthetic Aperture Radar and Radiometer (SWESARR) is a Tri-Frequency Radar and Radiometer instrument designed to measure the water content in a snowpack. The instrument, developed at NASA’s Goddard Space Flight Center, uses active and passive microwave sensors to map the radio frequency emissions of the snowpack, which can then be turned into a measurement of snow water equivalent.

SWESARR has three active (including a dual Ku band) and three passive bands. Radar data is collected in dual polarization (VV, VH) while the radiometer makes single polarization (H) observations.

• Free software: MIT License
• Documentation: https://eviofekeze.github.io/swesarr_pytools

Features

To install the package:

pip install swesarr_pytoolS

Usage

Accessing metadata

The package provide a functionality to retrieve available SWESARR flight paths and flight date, additionally flight path or list of flight path within a date range can be retrieved if such flight path exist

from swesarr_pytools.access_swesarr import AccessSwesarr
from datetime import date


#Instantiate the Access Object
meta_object = AccessSwesarr()

#Retrieve meta
swesarr_metadata = meta_object.data_meta

#Retrieve flight path
flight_paths = meta_object.flight_names

#Retrieve flight date
flight_dates = meta_object.flight_dates

#search for flight within a date range
available_dates = meta_object.available_date_within_range(start_date=date(2019, 1, 1),
                                               end_date=date(2019, 12, 31))

Data Manipulation

The package also provides additional functionality for;

• Reading a raster, Lidar and SWESARR
• Converting these to Dataframe
• Combining Fall and Winter SWESARR flights into one data frame for analysis Please see the notebook directory for additional examples