Flood Monitoring App

A fully automated flood monitoring service designed to provide rapid and reliable flood detection and monitoring within pipeline protection zones, utilizing advanced radar and optical data from Sentinel-1 and Sentinel-2 satellites, along with water level monitoring data from the Latvian environment geology and meteorology centre.

 

Key Features:


 

Automated Detection and Monitoring: Completely automatic service that identifies current and potential future flooding events affecting customer properties.

Advanced Data Utilization: Integrates satellite imagery with public water level data for precise monitoring and forecasting.

Dual-Level Results: Provides simple flood polygons for GIS databases and detailed lists of impacted customer properties.

User-Friendly Interfaces: Accessible through various interfaces including API, ArcGIS, and a dedicated web portal.

Sentinel Satellite Integration: Employs flood extraction algorithms from Sentinel-1 and Sentinel-2 imagery for precise flood mapping.

GIS Compatibility: Offers tools for integration with ArcGIS databases and software, alongside REST API support for enterprise system integration.

Flood Prediction and Modeling: Utilizes state water level sensors and a precise DTM for forecasting and modeling flood extents based on specific elevation changes.

 

Key Benefits:


 

Comprehensive Coverage: Combines radar and optical data from satellites, integrating real-time flood data from state systems.

Precision Analysis: Employs a precise Digital Elevation Model (DEM) from LIDAR data to calculate flood-affected areas accurately.

Enterprise Integration: Easily integrates into gas company’s enterprise GIS system with tools for ArcGIS and a ready-to-use web application.

Automated Service Delivery: Ensures complete automation of the flood monitoring process, requiring no additional responsibilities for existing staff.

 

Feedback and Future Directions


 

Following extensive testing by over 10 different organizations, the app has received valuable feedback for future enhancements, including improved flood modeling from water station data and the integration of satellite time series analysis.

Plans include adapting the system to various industry needs, expanding the network of water measurement and hydrological modeling stations, and enhancing the spatial resolution of models.

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