Flood Damage Assessment and Repair Cost Estimation
Overview
This project demonstrates a workflow for assessing flood-related road damage and estimating both economic loss and repair cost. The study was carried out for Cardinal Gracias Road, Chakala, Andheri East, Mumbai, using Sentinel-1 SAR imagery, flood-depth information, road construction costs, and damage assessment methods.
Key Features
- Flood extent mapping using Sentinel-1 SAR
- Before-and-after flood image comparison
- Road flood damage assessment
- Flood depth-based damage ratio estimation
- Economic loss estimation
- Road repair cost estimation
- Integration of remote sensing and infrastructure cost data
Workflow
- Define the study area and road asset.
- Process Sentinel-1 SAR imagery before and after the flood event.
- Map the flood extent using SAR change detection in Google Earth Engine.
- Estimate the flood depth from available reference data.
- Derive the road damage ratio using depth-damage curves.
- Estimate the road replacement value using Maharashtra SSR rates.
- Calculate the economic loss.
- Estimate the repair cost using road repair rates.
Technologies Used
- Google Earth Engine
- Sentinel-1 SAR
- Remote Sensing
- Flood Change Detection
- GIS
- Python
- Damage Assessment
- Economic Loss Estimation
Dataset
- Study Area: Cardinal Gracias Road, Chakala, Andheri East, Mumbai
- Event: Mumbai Floods, July 2026
- Before-Flood Image: Sentinel-1, 26 June 2026
- After-Flood Image: Sentinel-1, 08 July 2026
- Road Area: 3,356.87 m²
- Road Length: 460 m
- Road Width: 7.5 m
- Buffer: 50 m
Results

The estimated average flood depth was approximately 1.75 ft (0.53 m), corresponding to a 0.22 damage ratio based on the selected road depth-damage curve.
| Metric | Value |
|---|---|
| Estimated Flood Depth | 1.75 ft (0.53 m) |
| Damage Ratio | 22% |
| Road Replacement Cost | ₹1,809/m² |
| Estimated Economic Loss | ₹13,35,965 |
| Road repair rate | ₹715/m² |
| Estimated Repair Cost | ₹5,28,035 |
Economic Loss vs Repair Cost
- Economic Loss: Estimates the monetary value of the damaged road asset.
- Repair Cost: Estimates the cost required to restore the damaged road.
Future Improvements
- Integrate high-resolution imagery for more accurate inundation and damage-area measurement.
- Integrate field-verified flood depth and road condition information.
- Automate road asset valuation and repair cost estimation.
- Extend the workflow to larger urban areas and multiple flood events.
- Integrate the workflow into a flood damage assessment platform.