AquaSat
A data set to enable remote sensing of water quality for inland waters.
https://github.com/GlobalHydrologyLab/AquaSat
Category: Natural Resources
Sub Category: Water Supply and Quality
Last synced: about 21 hours ago
JSON representation
Repository metadata
Monitoring water quality from space!
- Host: GitHub
- URL: https://github.com/GlobalHydrologyLab/AquaSat
- Owner: GlobalHydrologyLab
- License: mit
- Created: 2017-10-25T15:48:28.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2020-07-20T19:37:28.000Z (almost 5 years ago)
- Last Synced: 2025-04-20T09:04:32.074Z (8 days ago)
- Language: HTML
- Size: 78.8 MB
- Stars: 53
- Watchers: 14
- Forks: 18
- Open Issues: 4
- Releases: 0
-
Metadata Files:
- Readme: README.html
- License: LICENSE
README.html
README.utf8.md watersat
Monitoring water quality from space!
Python Instructions
For this pipeline to work you will need to have a Google Earth Engine configured python installation ready to go. Explaining exactly how to do this is beyond the scope of this package but Google provides detailed installation instructions here. In addition to configuring Google Earth Engine you will need to install (probably best to do so in the following order):
using
scipiper
The
scipiper
package is an extremely young work in progress, intended to support projects for our USGS data science team and a limited number of collaborators. (Specifically, the code is public but we’re not planning to provide any support for projects we’re not directly involved in.) APA would really like to try it here if everybody is game. Install scipiper from GitHub:devtools::install_github('USGS-R/scipiper', update_dependencies = TRUE)
scipiper
offers 3 features that will likely be useful to us:
Support for a shared cache: our code can all live on GitHub while our data can all live on Google Drive and Earth Engine. Each big data file only needs to get acquired or processed once; the rest of us only need to pull that file locally if we’re running a process that requires that exact file.
Integration of a shared cache with a file/object dependency manager called
remake
(https://github.com/richfitz/remake). With this integration in place, we should all be able to contribute to keeping the shared cache consistent with the code on GitHub. We won’t need to question whether we remembered to run that edited version of the script or whether the data on GD is still from last week; we’ll know.An expansion of
remake
from jobs into tasks, where many tasks might be part of a single job, and our project is a collection of jobs. This idea should eventually be useful for spreading tasks across a cluster, but even at the current development phase this idea will allow us to split the WQP pull (one job) into a separate task for each state, and to attempt all those tasks with fault tolerance and retries as needed.The main way we’d use
scipiper
would be in building the project, in conjunction with development of the remake.yml file to declare the relationships among our raw, intermediate, and end-product data files. To build a specific file, along with any upstream dependencies that might be out of date, callscmake()
on that file. For example:library(scipiper) scmake('1_wqdata/out/wqp_wisconsin.feather')
Or to build any out-of-date targets in the entire project, simply:
scmake()
Owner metadata
- Name: Global Hydrology Lab
- Login: GlobalHydrologyLab
- Email:
- Kind: organization
- Description:
- Website: uncglobalhydrology.org
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/33097472?v=4
- Repositories: 5
- Last ynced at: 2023-03-07T14:41:48.830Z
- Profile URL: https://github.com/GlobalHydrologyLab
GitHub Events
Total
- Watch event: 7
- Fork event: 2
Last Year
- Watch event: 7
- Fork event: 2
Committers metadata
Last synced: 7 days ago
Total Commits: 164
Total Committers: 5
Avg Commits per committer: 32.8
Development Distribution Score (DDS): 0.396
Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0
Name | Commits | |
---|---|---|
matthewross07 | m****7@g****m | 99 |
Alison Appling | a****g@u****v | 46 |
Simon Topp | s****p@g****m | 13 |
Ross | m****r@c****u | 4 |
Simon Topp | s****p@d****u | 2 |
Committer domains:
Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 18
Total pull requests: 26
Average time to close issues: 4 months
Average time to close pull requests: 6 days
Total issue authors: 3
Total pull request authors: 3
Average comments per issue: 0.94
Average comments per pull request: 0.27
Merged pull request: 26
Bot issues: 0
Bot pull requests: 0
Past year issues: 0
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 0
Past year pull request authors: 0
Past year average comments per issue: 0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- matthewross07 (10)
- SimonTopp (7)
- seanhardison1 (1)
Top Pull Request Authors
- matthewross07 (13)
- aappling-usgs (8)
- SimonTopp (5)
Top Issue Labels
Top Pull Request Labels
Score: 5.652489180268651