Chintan2108 / Chintan2108/Water-Based-Indices-on-Sentinel-2A-Images-using-Python
Analysis and Documentation: Water body extraction from Landsat-8 Images
Open
Nobody has claimed this yet.
documentation
enhancement
SLoP-75
- Dominant language
- Jupyter Notebook
- Stars
- 34
- Forks
- 15
- PR merge metrics
- No merged PRs in 30d
Description
- Water bodies are extracted using two methods: (i) NDWI indices (ii) Spectral Modulation Function
- Create ground truth map using QGIS by drawing polygons over the feature of interest
- Compare the results of both the methods with the ground truth using the parameters "Miss Factor = FN/TP" and "Detection Percentage = TP/(TP+FN)"
- Update documentation in readme accordingly by creating a new section of results comparison of the two methods for Landsat-8 images
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the existing README and the project’s NDWI and Spectral Modulation Function material first. Use QGIS to create a ground-truth map for Landsat-8 water bodies, compare both methods using Miss Factor and Detection Percentage, and document the results in a new README section.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- computer-vision, documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100