autofloods

Pre-release

This release is a pre-release and may not be stable for production use.

AutoFloods

AutoFloods is a Python package for automated flood mapping at scale from Sentinel-1 SAR imagery, with pluggable data sources (Microsoft Planetary Computer, NASA OPERA) and detection methods (Z-score, Otsu).

Quickstart

OPERASource requires a free NASA Earthdata Login; MPCSource works with no credentials at all (a free subscription key just raises rate limits) — see Authentication.

Pre-release: pip install --pre autofloods

Basic usage:

from autofloods import flood_mapper
from autofloods.sources import OPERASource

fm = flood_mapper(
    # AOI grid; needs id_col, dry_date_col, zone columns
    grid_shapefile='resources/india_utm_fishnet_buffer.gpkg',

    # which AOI IDs from the grid to process
    grid_id_list=[321],

    # dry-season years to build the baseline from
    dry_years=[2024, 2024],

    # where the terrain-slope mask is cached
    slope_dir='resources/slope/',

    # wet-season date range to classify
    wet_duration=['2024/07', '2024/10'],

    # or MPCSource() (the default)
    source=OPERASource(),

    # root dir for all outputs and caches
    output_dir='output/my_run',
)

# read each AOI's dry season into self.dry_months
fm.get_dry_dates()

# turn dry_months into per-year search date ranges
fm.generate_dry_date_ranges()

# STAC-search the source for dry-season scenes
fm.get_s1_items(dry_wet='dry')

# download + read those scenes
fm.read_scenes(dry_wet='dry', overview_level=None, max_workers=6)

# fit the dry-season Z-score baseline per AOI
fm.generate_mean_std_by_aoi()

# compute/cache the terrain-slope mask
fm.prepare_slope(dem_overview=0, buffer=500)

# search, read, reproject wet-season scenes
fm.prepare_wet_scenes(overview_level=None, max_workers=6)

# classify each scene against the baseline
fm.map_floods(vv_thd=-2.5, vh_thd=-2.5, rel_slope_thd=20,
              export_raster=False, export_vector=False, export_maps=False)

# collapse per-scene results into one band per date
fm.merge_floods_by_date(export_raster=True)

# per-pixel count of scenes with data gaps
fm.generate_number_of_scenes(export_raster=True)

# aggregate per-date results into per-month flood-day counts
fm.monthly_sum()

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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

autofloods-0.1.0a7.tar.gz (65.3 kB view details)

Uploaded Sep 3, 2026 Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

autofloods-0.1.0a7-py3-none-any.whl (63.6 kB view details)

Uploaded Sep 3, 2026 Python 3

File details

Details for the file autofloods-0.1.0a7.tar.gz.

File metadata

Download URL: autofloods-0.1.0a7.tar.gz
Upload date: Sep 3, 2026
Size: 65.3 kB
Tags: Source
Uploaded using Trusted Publishing? Yes
Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for autofloods-0.1.0a7.tar.gz
Algorithm	Hash digest
SHA256	`4a5045f0727ba2fb1ff577104ccbb166909ca688b1102d7fb3fca5cbaa58ec74`
MD5	`1057feab1425bccb99979f9fc5c861b5`
BLAKE2b-256	`6f2c60ffda9caa041beba7bf386f8fe80345580ac52648fd7cd5cbfc983a54b6`

See more details on using hashes here.

Provenance

The following attestation bundles were made for autofloods-0.1.0a7.tar.gz:

Publisher: publish.yml on PratyushTripathy/AutoFloods

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Statement:
- Statement type: https://in-toto.io/Statement/v1
- Predicate type: https://docs.pypi.org/attestations/publish/v1
- Subject name: autofloods-0.1.0a7.tar.gz
- Subject digest: 4a5045f0727ba2fb1ff577104ccbb166909ca688b1102d7fb3fca5cbaa58ec74
- Sigstore transparency entry: 2696396052
- Sigstore integration time: Sep 3, 2026
Source repository:
- Permalink: PratyushTripathy/AutoFloods@e7fb9ad22eb1bce13213b04fe5c94c0790d37a82
- Branch / Tag: refs/tags/v0.1.0a7
- Owner: https://github.com/PratyushTripathy
- Access: public
Publication detail:
- Token Issuer: https://token.actions.githubusercontent.com
- Runner Environment: github-hosted
- Publication workflow: publish.yml@e7fb9ad22eb1bce13213b04fe5c94c0790d37a82
- Trigger Event: release