Categorize daily indices into spread day classes “Minimal, Normal & Significant”
Open
- Dominant language
- Python
- Stars
- 65
- Forks
- 11
- Avg merge
- 21h 25m
- Merged PRs (30d)
- 70
Description
- [ ] Using current weather station indices add in 10 day forecast from MORECAST and calculate out 10 days of FWI values
- Weather stations will also have a polygon area they cover and any fires/MODIS hotspot that falls in that polygon
Contributor guide
Research direction
No files, tests, or entry points are named. Start by locating the current weather-station index workflow and any MORECAST or FWI integrations. Done should include a 10-day forecast, 10 days of FWI values, and classification of fires or MODIS hotspots within each station polygon into Minimal, Normal, or Significant spread-day classes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- backend, data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100