| Name | swesarr-pytools JSON |
| Version |
0.1.11
JSON |
| download |
| home_page | None |
| Summary | Library for data retrieval and processing of NASA GSFC Snow Water Equivalent Synthetic Aperture Radar and Radiometer data. |
| upload_time | 2024-10-07 23:02:28 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License |
| keywords |
swesarr_pytools
|
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# swesarr_pytools
[](https://pypi.python.org/pypi/swesarr_pytools)
[//]: # ([](https://anaconda.org/conda-forge/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.
Additionally, SWESARR contains airborne microwave brightness temperature observations. Observations were made at three
frequencies (10.65, 18.7, and 36.5 GHz; referred to as X, K, and Ka bands, respectively), at horizontal polarization
with a nominal 45-degree look angle.
To learn more about SWESARR, please see this tutorial delivered during the NASA Earth Science & UW Hackweek 2024:
https://snowex-2024.hackweek.io/tutorials/swesarr/swesarr_tut.html
For general information about swesarr see:
- https://earth.gsfc.nasa.gov/bio/instruments/snow-water-equivalent-sar-and-radiometer-swesarr
- https://snow.nasa.gov/instruments/swesarr
- https://www.thenewtoncorp.com/case-studies/swesarr-snow-water-equivalent-synthetic-aperture-radar-and-radiometer
-----
- Free software: MIT License
- Documentation: https://eviofekeze.github.io/swesarr_pytools
## Features
To install the package:
```commandline
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
```python
from swesarr_pytools.access_swesarr import AccessSAR
from datetime import date
# Instantiate the Access Object
swesarr_object = AccessSAR()
# Retrieve meta
swesarr_metadata = swesarr_object.data_meta
# Retrieve flight path
flight_paths = swesarr_object.flight_names
# Retrieve flight date
flight_dates = swesarr_object.flight_dates
# search for flight within a date range
available_dates = swesarr_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
**Reference:**
[1] R. Rincón et al., "Performance of Swesarr's Multi-Frequency Dual-Polarimetry Synthetic Aperture Radar During Nasa's
Snowex Airborne Campaign," IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI,
USA, 2020, pp. 6150-6153, doi: 10.1109/IGARSS39084.2020.9324391. keywords: {Radar;Snow;Radar antennas;Synthetic aperture
radar; Spaceborne radar;Airborne radar;Instruments;Snow;SAR;SWE},
[2] D. R. Boyd, A. M. Alam, M. Kurum, A. C. Gurbuz and B. Osmanoglu, "Preliminary Snow Water Equivalent Retrieval of
SnowEX20 Swesarr Data," IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur,
Malaysia, 2022, pp. 3927-3930, doi: 10.1109/IGARSS46834.2022.9883412. keywords: {Radio frequency;Sensitivity;Radar
measurements;Spaceborne radar;Snow;NASA;Prediction algorithms;Snow;SWE;Radar;SWESARR;SAR;SnowEx},
Raw data
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"description": "# swesarr_pytools\n\n\n[](https://pypi.python.org/pypi/swesarr_pytools)\n\n[//]: # ([](https://anaconda.org/conda-forge/swesarr_pytools))\n\n\n**Library for data retrieval and processing of NASA GSFC Snow Water Equivalent Synthetic Aperture Radar and Radiometer data.**\n\nswesarr_pytool is a python library created for data retrieval and processing of NASA GSFC Snow Water Equivalent Synthetic\nAperture Radar and Radiometer data.\n\nThe Snow Water Equivalent Synthetic Aperture Radar and Radiometer (SWESARR) is a Tri-Frequency Radar and Radiometer\ninstrument designed to measure the water content in a snowpack. The instrument, developed at NASA\u2019s Goddard Space Flight\nCenter, uses active and passive microwave sensors to map the radio frequency emissions of the snowpack, which can then be turned into a measurement of\nsnow water equivalent.\n\nSWESARR has three active (including a dual Ku band) and three passive bands. Radar data is collected in dual polarization\n(VV, VH) while the radiometer makes single polarization (H) observations.\n\nAdditionally, SWESARR contains airborne microwave brightness temperature observations. Observations were made at three\nfrequencies (10.65, 18.7, and 36.5 GHz; referred to as X, K, and Ka bands, respectively), at horizontal polarization\nwith a nominal 45-degree look angle.\n\n\nTo learn more about SWESARR, please see this tutorial delivered during the NASA Earth Science & UW Hackweek 2024:\nhttps://snowex-2024.hackweek.io/tutorials/swesarr/swesarr_tut.html\n\nFor general information about swesarr see:\n\n- https://earth.gsfc.nasa.gov/bio/instruments/snow-water-equivalent-sar-and-radiometer-swesarr\n- https://snow.nasa.gov/instruments/swesarr\n- https://www.thenewtoncorp.com/case-studies/swesarr-snow-water-equivalent-synthetic-aperture-radar-and-radiometer\n\n-----\n- Free software: MIT License\n- Documentation: https://eviofekeze.github.io/swesarr_pytools\n\n\n## Features\n\nTo install the package:\n\n```commandline\npip install swesarr_pytools\n```\n\n### **Usage**\n**Accessing metadata**\n\nThe package provide a functionality to retrieve available SWESARR flight paths and flight date, additionally\nflight path or list of flight path within a date range can be retrieved if such flight path exist\n\n```python\nfrom swesarr_pytools.access_swesarr import AccessSAR\nfrom datetime import date\n\n# Instantiate the Access Object\nswesarr_object = AccessSAR()\n\n# Retrieve meta\nswesarr_metadata = swesarr_object.data_meta\n\n# Retrieve flight path\nflight_paths = swesarr_object.flight_names\n\n# Retrieve flight date\nflight_dates = swesarr_object.flight_dates\n\n# search for flight within a date range\navailable_dates = swesarr_object.available_date_within_range(start_date=date(2019, 1, 1),\n end_date=date(2019, 12, 31))\n\n```\n**Data Manipulation**\n\nThe package also provides additional functionality for;\n- Reading a raster, Lidar and SWESARR\n- Converting these to Dataframe\n- Combining Fall and Winter SWESARR flights into one data frame for analysis\nPlease see the notebook directory for additional examples\n\n\n**Reference:**\n\n[1] R. Rinc\u00f3n et al., \"Performance of Swesarr's Multi-Frequency Dual-Polarimetry Synthetic Aperture Radar During Nasa's\nSnowex Airborne Campaign,\" IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI,\nUSA, 2020, pp. 6150-6153, doi: 10.1109/IGARSS39084.2020.9324391. keywords: {Radar;Snow;Radar antennas;Synthetic aperture\nradar; Spaceborne radar;Airborne radar;Instruments;Snow;SAR;SWE},\n\n[2] D. R. Boyd, A. M. Alam, M. Kurum, A. C. Gurbuz and B. Osmanoglu, \"Preliminary Snow Water Equivalent Retrieval of\nSnowEX20 Swesarr Data,\" IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur,\nMalaysia, 2022, pp. 3927-3930, doi: 10.1109/IGARSS46834.2022.9883412. keywords: {Radio frequency;Sensitivity;Radar\nmeasurements;Spaceborne radar;Snow;NASA;Prediction algorithms;Snow;SWE;Radar;SWESARR;SAR;SnowEx},\n\n\n\n",
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