Metadata-Version: 2.4
Name: autofloods
Version: 0.1.0a4
Summary: Automated flood mapping at scale from Sentinel-1 SAR imagery
Author-email: Pratyush Tripathy <tripathyshared@gmail.com>
License: MIT
Project-URL: Homepage, https://github.com/PratyushTripathy/AutoFloods
Project-URL: Repository, https://github.com/PratyushTripathy/AutoFloods
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: <3.11,>=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: geopandas==0.13.2
Requires-Dist: fiona==1.9.6
Requires-Dist: rioxarray==0.14.1
Requires-Dist: xarray==2023.6.0
Requires-Dist: pandas==1.5.0
Requires-Dist: rasterio==1.3.3
Requires-Dist: shapely==2.0.1
Requires-Dist: numpy==1.23.2
Requires-Dist: matplotlib==3.6.0
Requires-Dist: xarray-spatial==0.3.7
Requires-Dist: pystac==1.7.2
Requires-Dist: pystac-client==0.6.1
Requires-Dist: scikit-image==0.19.3
Requires-Dist: scikit-learn==1.1.3
Requires-Dist: planetary-computer==1.0.0
Requires-Dist: dask[array]==2023.6.0
Requires-Dist: requests==2.31.0
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Provides-Extra: docs
Requires-Dist: quartodoc; extra == "docs"
Requires-Dist: griffe<2; extra == "docs"
Dynamic: license-file

# AutoFloods

AutoFloods is a Python package for automated flood mapping at scale from Sentinel-1 SAR imagery, with pluggable data sources and detection methods.

## Quickstart

<!-- TODO: drop --pre once a stable (non-alpha/beta) 0.1.0 release exists -->
This is a pre-release — install with: `pip install --pre autofloods`

Basic usage:

```python
from autofloods import flood_mapper
from autofloods.sources import OPERASource

fm = flood_mapper(
    grid_shapefile='path/to/grid.gpkg',
    grid_id_list=[321],
    dry_years=[2024, 2024],
    slope_dir='resources/slope/',
    wet_duration=['2024/07', '2024/10'],
    source=OPERASource(),
    output_dir='output/my_run',
)

fm.get_dry_dates()
fm.generate_dry_date_ranges()
fm.get_s1_items(dry_wet='dry')
fm.read_scenes(dry_wet='dry')
fm.generate_mean_std_by_aoi()
fm.prepare_slope()
fm.prepare_wet_scenes()
fm.map_floods()
fm.merge_floods_by_date(export_raster=True)
```

See the documentation for full usage, API reference, and citation details: https://autofloods.readthedocs.io/en/latest/
