https://github.com/drivendataorg/cyfi
Estimate cyanobacteria density based on Sentinel-2 satellite imagery
https://github.com/drivendataorg/cyfi
cyanobacteria habs satellite-imagery sentinel-2
Last synced: 4 months ago
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Estimate cyanobacteria density based on Sentinel-2 satellite imagery
- Host: GitHub
- URL: https://github.com/drivendataorg/cyfi
- Owner: drivendataorg
- License: mit
- Created: 2023-07-17T21:18:38.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-03-10T17:40:21.000Z (7 months ago)
- Last Synced: 2025-05-30T02:19:20.983Z (5 months ago)
- Topics: cyanobacteria, habs, satellite-imagery, sentinel-2
- Language: Python
- Homepage: https://cyfi.drivendata.org/
- Size: 10.6 MB
- Stars: 24
- Watchers: 5
- Forks: 6
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
CyFi: Cyanobacteria Finder
==============================
[](https://pypi.org/project/cyfi/)
[](https://anaconda.org/conda-forge/cyfi)
[](https://github.com/drivendataorg/cyfi/actions?query=workflow%3Atests+branch%3Amain)
[](https://codecov.io/gh/drivendataorg/cyfi)
CyFi is a command line tool that uses satellite imagery and machine learning to estimate cyanobacteria levels in small, inland water bodies. The goal of CyFi is to help water quality managers better allocate resources for in situ sampling, and make more informed decisions around public health warnings for critical resources like lakes and reservoirs.
Read more at [cyfi.drivendata.org](https://cyfi.drivendata.org)
## Quickstart
### Install
> [!NOTE]
> There is a known [issue](https://github.com/drivendataorg/cyfi/issues/114) with the pip installation on M1 Macs due to LightGBM. If you're on a Mac, we recommend installing CyFi with conda, shown in the second option below.
Install CyFi with pip:
```
pip install cyfi
```
Alternatively, CyFi can be installed with conda:
```
conda install -c conda-forge cyfi
```
For detailed instructions for those installing python for the first time, see the [Installation](https://cyfi.drivendata.org/installation/) page.
### Generate batch predictions
Generate batch predictions at the command line with `cyfi predict`.
First, specify your sample points in a csv with the following columns:
* latitude
* longitude
* date
For example,
```
# sample_points.csv
latitude,longitude,date
41.424144,-73.206937,2023-06-22
36.045,-79.0919415,2023-07-01
35.884524,-78.953997,2023-08-04
```
Then run:
```
cyfi predict sample_points.csv
```
This will output a `preds.csv` that contains a column for cyanobacteria density and a column for the associated severity level based on WHO thresholds.
```
# preds.csv
sample_id,date,latitude,longitude,density_cells_per_ml,severity
7ff4b4a56965d80f6aa501cc25aa1883,2023-06-22,41.424144,-73.206937,34173.0,moderate
882b9804a3e28d8805f98432a1a9d9af,2023-07-01,36.045,-79.0919415,7701.0,low
10468e709dcb6133d19a230419efbb24,2023-08-04,35.884524,-78.953997,4053.0,low
```
To see all of the available options, run `cyfi predict --help`.
### Generate prediction for a single point
Or, generate a cyanobacteria estimate for a single point on a single date using `cyfi predict-point`.
Just specify the latitude, longitude, and date as arguments at the command line.
```
cyfi predict-point --lat 41.2 --lon -73.2 --date 2023-09-14
```
This will print out the estimated cyanobacteria density and associated severity level based on WHO thresholds.
```
2023-10-04 16:25:40.581 | SUCCESS | cyfi.cli:predict_point:154 - Estimate generated:
date 2023-09-14
latitude 41.2
longitude -73.2
density_cells_per_ml 32,820
severity moderate
```
To see all of the available options, run `cyfi predict-point --help`.
### A note on severity levels
Severity levels are based on World Health Organization (WHO) cyanobacteria density thresholds.
- Low: 0 - 20,000 cells/ml
- Moderate: 20,000 - 100,000 cells/ml
- High: > 100,000 cells/ml
However users should feel free to to use their own thresholds as makes sense for their needs.
### Visualizing predictions
Launch the [CyFi Explorer](https://cyfi.drivendata.org/explorer/) to view the Sentinel-2 imagery used to generate each cyanobacteria estimate!
## Reference paper
Dorne, E., Wetstone, K., Cerquera, T. B., & Gupta, S. (2024). Cyanobacteria detection in small, inland water bodies with CyFi. In Proceedings of the 23nd Python in Science Conference (pp. 154–173).