{"id":25229034,"url":"https://github.com/SarwanShah/Flood-Mapping-Using-Google-Earth-Engine-2024","last_synced_at":"2025-10-26T06:31:20.642Z","repository":{"id":276704391,"uuid":"930021345","full_name":"SarwanShah/ASU_2024_Flood-Mapping-Using-GEE","owner":"SarwanShah","description":"A remote-sensing based application using Google Earth Engine for flood mapping and impact assessment.","archived":false,"fork":false,"pushed_at":"2025-02-09T23:45:06.000Z","size":16102,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-10T00:23:58.285Z","etag":null,"topics":["environmental-engineering","flood-mapping","google-earth-engine","javascript","remote-sensing"],"latest_commit_sha":null,"homepage":"","language":"JavaScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc0-1.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/SarwanShah.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-02-09T23:11:14.000Z","updated_at":"2025-02-10T00:13:17.000Z","dependencies_parsed_at":"2025-02-10T00:34:58.778Z","dependency_job_id":null,"html_url":"https://github.com/SarwanShah/ASU_2024_Flood-Mapping-Using-GEE","commit_stats":null,"previous_names":["sarwanshah/asu_2024_flood-mapping-using-gee"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SarwanShah%2FASU_2024_Flood-Mapping-Using-GEE","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SarwanShah%2FASU_2024_Flood-Mapping-Using-GEE/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SarwanShah%2FASU_2024_Flood-Mapping-Using-GEE/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SarwanShah%2FASU_2024_Flood-Mapping-Using-GEE/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SarwanShah","download_url":"https://codeload.github.com/SarwanShah/ASU_2024_Flood-Mapping-Using-GEE/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":238281243,"owners_count":19446081,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["environmental-engineering","flood-mapping","google-earth-engine","javascript","remote-sensing"],"created_at":"2025-02-11T10:46:58.473Z","updated_at":"2025-10-26T06:31:19.592Z","avatar_url":"https://github.com/SarwanShah.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Flood Mapping and Impact Assessment Using Google Earth Engine  \n\n## **Project Overview**  \nThis 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.\n\n**REPORT**: [Final_Report.pdf](Final_Report.pdf)  \n**PRESENTATION**: [Final_Presentation.pptx](Final_Presentation.pptx)  \n\n---\n\n## **Project Motivation**  \nThe 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.  \n\n---\n\n## **Project Features**  \n- **Flood Mapping**:\n  - Utilizes **Sentinel-1 SAR** (Synthetic Aperture Radar) data with high spatial resolution (10m), capable of capturing flood events even under cloud cover.\n  - Supports before-and-after analysis using user-defined date ranges.\n\n- **Impact Assessment**:\n  - Integrates **MODIS** land cover data to analyze flood effects on urban and crop land.\n  - Generates statistics such as total flooded area and percentage of affected regions.\n\n- **Speckle Noise Reduction**:\n  - Applies a **Refined Lee Speckle Filter** to enhance image clarity by reducing radar noise.\n\n- **User-Friendly Interface**:\n  - Dynamic input panels for region selection, date inputs, and analysis parameters.\n  - Customizable thresholds for flood and terrain filtering.\n\n- **Visualization and Outputs**:\n  - Displays flood extent, impacted urban/crop areas, and a detailed legend.\n  - Outputs key statistics for decision-making.\n\n---\n\n## **How It Works**  \n1. **Select Region**: Choose a country and state using administrative boundaries from the FAO GAUL dataset.  \n2. **Define Timeframes**: Specify \"before\" and \"after\" flood event date windows.  \n3. **Run Analysis**: The app processes Sentinel-1 and MODIS satellite data to detect flooded regions.  \n4. **View Results**: Visual maps and statistical outputs appear on the interface, highlighting affected areas.  \n\n---\n\n## **Datasets Used**  \n| Dataset              | Description                                  | Resolution  | Source               |\n|----------------------|----------------------------------------------|-------------|----------------------|\n| Sentinel-1           | C-band SAR for flood detection               | 10m         | ESA Copernicus       |\n| MODIS                | Land cover data for impact assessment        | 500m        | NASA EOSDIS          |\n| Global Surface Water | Seasonal water body data                     | Various     | European Commission  |\n| HydroSHEDS           | Elevation model for slope filtering          | 3 arc-seconds | WWF                 |\n\n---\n\n## **Code Structure**  \n| File                 | Description                                  |\n|----------------------|----------------------------------------------|\n| `main.js`            | Core analysis and flood mapping logic        |\n| `ui.js`              | User interface code                          |\n| `fetchregion.js`     | Fetches regional boundaries from FAO GAUL    |\n| `specklefilter.js`   | Implements speckle noise reduction           |\n\n---\n\n## **Design Challenges \u0026 Future Work**  \n- **Asynchronous Data Processing**: Managing Google Earth Engine's asynchronous tasks within a user interface posed challenges.  \n- **Edge Case Testing**: Improving the robustness of flood detection in varying geographical and climatic conditions is ongoing.  \n- **Enhanced Parameter Control**: Future versions aim to offer more dynamic user-defined parameters and visualization features.  \n\n---\n\n## **Cost Efficiency**  \nAs a cloud-based solution utilizing open-access satellite data, this project incurs minimal operational costs while offering scalability and global applicability.\n\n---\n\n## **How to Use**  \n1. Install **Google Earth Engine** and ensure access to relevant datasets.  \n2. Clone this repository.  \n3. Run the app through GEE's code editor by uploading the provided scripts (`main.js`, `ui.js`, etc.).  \n4. Follow on-screen prompts to configure and execute the flood analysis.  \n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FSarwanShah%2FFlood-Mapping-Using-Google-Earth-Engine-2024","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FSarwanShah%2FFlood-Mapping-Using-Google-Earth-Engine-2024","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FSarwanShah%2FFlood-Mapping-Using-Google-Earth-Engine-2024/lists"}