https://github.com/sarwanshah/flood-mapping-using-google-earth-engine-2024

A remote-sensing based application using Google Earth Engine for flood mapping and impact assessment.
https://github.com/sarwanshah/flood-mapping-using-google-earth-engine-2024

environmental-engineering flood-mapping google-earth-engine javascript remote-sensing

Last synced: 3 months ago
JSON representation

A remote-sensing based application using Google Earth Engine for flood mapping and impact assessment.

• Host: GitHub
• URL: https://github.com/sarwanshah/flood-mapping-using-google-earth-engine-2024
• Owner: SarwanShah
• License: cc0-1.0
• Created: 2025-02-09T23:11:14.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2025-02-10T00:37:52.000Z (8 months ago)
• Last Synced: 2025-06-30T11:50:31.675Z (3 months ago)
• Topics: environmental-engineering, flood-mapping, google-earth-engine, javascript, remote-sensing
• Language: JavaScript
• Homepage:
• Size: 15.4 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Flood Mapping and Impact Assessment Using Google Earth Engine  

## **Project Overview**  

This project was developed as part of the **SES 598 Cloud-Based Remote Sensing** course at **Habib University**, led by **Instructor Jiwei Li**. It leverages **Google Earth Engine (GEE)** to map flood events and assess their impacts on urban and agricultural land. Using satellite data from **Sentinel-1 SAR** and **MODIS**, the application enables near-real-time flood detection and impact analysis, empowering decision-makers in flood-prone areas to take informed actions.

**REPORT**: [Final_Report.pdf](Final_Report.pdf)  

**PRESENTATION**: [Final_Presentation.pptx](Final_Presentation.pptx)  

---

## **Project Motivation**  

The frequency of extreme weather events, such as flooding, has increased due to climate change. A striking example was the **2022 Pakistan floods**, which submerged one-third of the Sindh province. This project aims to provide a scalable solution to quickly map and assess flood impacts, helping communities prepare and respond to future events.  

---

## **Project Features**  

- **Flood Mapping**:

  - Utilizes **Sentinel-1 SAR** (Synthetic Aperture Radar) data with high spatial resolution (10m), capable of capturing flood events even under cloud cover.

  - Supports before-and-after analysis using user-defined date ranges.

- **Impact Assessment**:

  - Integrates **MODIS** land cover data to analyze flood effects on urban and crop land.

  - Generates statistics such as total flooded area and percentage of affected regions.

- **Speckle Noise Reduction**:

  - Applies a **Refined Lee Speckle Filter** to enhance image clarity by reducing radar noise.

- **User-Friendly Interface**:

  - Dynamic input panels for region selection, date inputs, and analysis parameters.

  - Customizable thresholds for flood and terrain filtering.

- **Visualization and Outputs**:

  - Displays flood extent, impacted urban/crop areas, and a detailed legend.

  - Outputs key statistics for decision-making.

---

## **How It Works**  

1. **Select Region**: Choose a country and state using administrative boundaries from the FAO GAUL dataset.  

2. **Define Timeframes**: Specify "before" and "after" flood event date windows.  

3. **Run Analysis**: The app processes Sentinel-1 and MODIS satellite data to detect flooded regions.  

4. **View Results**: Visual maps and statistical outputs appear on the interface, highlighting affected areas.  

---

## **Datasets Used**  

| Dataset              | Description                                  | Resolution  | Source               |

|----------------------|----------------------------------------------|-------------|----------------------|

| Sentinel-1           | C-band SAR for flood detection               | 10m         | ESA Copernicus       |

| MODIS                | Land cover data for impact assessment        | 500m        | NASA EOSDIS          |

| Global Surface Water | Seasonal water body data                     | Various     | European Commission  |

| HydroSHEDS           | Elevation model for slope filtering          | 3 arc-seconds | WWF                 |

---

## **Code Structure**  

| File                 | Description                                  |

|----------------------|----------------------------------------------|

| `main.js`            | Core analysis and flood mapping logic        |

| `ui.js`              | User interface code                          |

| `fetchregion.js`     | Fetches regional boundaries from FAO GAUL    |

| `specklefilter.js`   | Implements speckle noise reduction           |

---

## **Design Challenges & Future Work**  

- **Asynchronous Data Processing**: Managing Google Earth Engine's asynchronous tasks within a user interface posed challenges.  

- **Edge Case Testing**: Improving the robustness of flood detection in varying geographical and climatic conditions is ongoing.  

- **Enhanced Parameter Control**: Future versions aim to offer more dynamic user-defined parameters and visualization features.  

---

## **Cost Efficiency**  

As a cloud-based solution utilizing open-access satellite data, this project incurs minimal operational costs while offering scalability and global applicability.

---

## **How to Use**  

1. Install **Google Earth Engine** and ensure access to relevant datasets.  

2. Clone this repository.  

3. Run the app through GEE's code editor by uploading the provided scripts (`main.js`, `ui.js`, etc.).  

4. Follow on-screen prompts to configure and execute the flood analysis.  

---