floodrisk 1.0.0

Flood detection and damage assessment using Sentinel-1 SAR and OSM data with Google Earth Engine

🌊 FloodRisk

---

📌 Overview

FloodRisk is a Python package for flood detection and damage assessment using:

• Sentinel-1 SAR imagery (via Google Earth Engine)
• Otsu thresholding for flood extent mapping
• OpenStreetMap (OSM) data for infrastructure damage analysis
• CSV & GeoTIFF export
• Visualization of flood extent and results

---

✅ Key Features

✔ Flood inundation mapping with Sentinel-1 SAR ✔ Automatic thresholding using Otsu method ✔ Compute inundation percentage and area statistics ✔ Damage assessment for roads and buildings using OSM data ✔ Export results (CSV, GeoTIFF) ✔ Visualization of flood maps

---

🔍 Installation

Install from PyPI:

pip install floodrisk

From source:

git clone https://github.com/MeawMan/floodrisk.git
cd floodrisk
pip install -e .

---

🚀 Quick Start

1. Initialize Google Earth Engine

from floodrisk import initialize

# Authenticate GEE
initialize(project_id="your-project-id")

---

2. Detect Flood (Sentinel-1 via GEE)

from floodrisk import detect_flood, export_map

# Detect flood inundation
result = detect_flood(
    aoi_name="Feni",
    before_start="2025-01-01", before_end="2025-01-31",
    after_start="2025-07-01", after_end="2025-07-12"
)

print("Flooded Area (ha):", result['Flooded Area (ha)'].getInfo())

# Export flood map to Google Drive
export_map(result['flooded_image'], "Flood_Extent", "GEE_Flood")

---

3. Damage Assessment

from shapely.geometry import Polygon
from floodrisk import download_osm_data, compute_flood_damage, export_csv

# Define AOI polygon
aoi_polygon = Polygon([(91.15, 23.40), (91.20, 23.40), (91.20, 23.45), (91.15, 23.45)])

# Download OSM roads & buildings
roads, buildings = download_osm_data(aoi_polygon)

# Flood raster (GeoTIFF from GEE export)
flood_tif_path = "Flood_Extent.tif"

# Compute flood damage
damage_result = compute_flood_damage(roads, buildings, flood_tif_path)

print(damage_result['road_stats'])
print(damage_result['building_stats'])

# Export results as CSV
export_csv(damage_result['road_stats'], damage_result['building_stats'], "output/reports")

---

4. Visualization

from floodrisk import visualize_map

visualize_map("Flood_Extent.tif", aoi_shapefile="aoi.shp")

---

✅ Output Example

AOI: Feni
Otsu Threshold: 1.21
Total Area: 88,029 ha
Flooded Area: 18,647 ha
Inundation: 21%

Road Damage Summary:
Category           Total Length (km)  Flooded Length (km)  Flooded %
National Highways             207.05                 4.03       1.94
Regional Roads                322.97                14.40       4.46
Local Roads                  1909.71               111.38       5.83

Building Damage Summary:
{'Total Buildings': 161204, 'Flooded Buildings': 5242, 'Flooded %': 3.25}

---

✅ CLI Usage

Run from terminal:

floodrisk --aoi Feni --before_start 2025-01-01 --before_end 2025-01-31 --after_start 2025-07-01 --after_end 2025-07-12 --flood_raster Flood_Extent.tif --output results --visualize

---

📜 Citation

Rahman, M.R. (2025). FloodRisk: A Python Package for Flood Detection and Damage Assessment.
Zenodo. https://doi.org/10.5281/zenodo.16407193

---

✅ License

MIT License. See LICENSE.