https://github.com/dshean/snowtools

Utilities for working with snow data
https://github.com/dshean/snowtools

Last synced: about 2 months ago
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Utilities for working with snow data

• Host: GitHub
• URL: https://github.com/dshean/snowtools
• Owner: dshean
• License: apache-2.0
• Created: 2017-08-05T02:12:58.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2021-05-13T18:30:19.000Z (about 3 years ago)
• Last Synced: 2024-01-25T12:07:35.725Z (5 months ago)
• Language: Python
• Homepage:
• Size: 882 KB
• Stars: 9
• Watchers: 3
• Forks: 9
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• cryosphere-links - snowtools - D. Shean's utilities for working with snow data (Snow / SN Software)

README

        
# snowtools 

A collection of tools for processing and analyzing snow data

## Features

- Automated querying and processing of SNOTEL data from CUAHSI database

- Processing and analysis of NASA SnowEx campaign data

- Automated retrieval and processing of MODSCAG fracitonal snow-covered area (fSCA) products

- Automated retrieval and processing of SNODAS model snow depth 

## Examples

![Rainier example](docs/rainier_snowdepth_2015-2017_sm.jpg)

## Tools 

- `get_snotel.py` - retrieve SNOTEL data for a given input extent (e.g., raster snow depth map from ΔDEM)

  - Note: can use [`compute_dz.py`](https://github.com/dshean/demcoreg/blob/master/demcoreg/compute_dz.py) in demcoreg repo to compute snow depth from two arbitrary input DEMs (e.g. LiDAR, SfM, satellite stereo)

- `swe.py` - convert snow depth raster to snow water equivalent (SWE)  

- `get_modscag.py` - extract MODSCAG fSCA for a given date to match another raster (e.g. LS8 image, DEM)

- `get_snodas.py` - extract SNODAS model snow depth for a given date to match another raster (e.g. LS8 image, DEM)

## Future

- Implement multiple snow models (e.g., Sturm et al. [2010]) to estimate density for arbitrary location and timestamp

### Core requirements

- [pygeotools](https://github.com/dshean/pygeotools)

### Optional requirements

- [ulmo](https://github.com/ulmo-dev/ulmo)