Idea
Our project is a web platform that allows citizens to actively report environmental risks by placing pins on an interactive map of Romania. Users can indicate whether their area is affected by drought, flooding, or waste/pollution issues.
The platform doesn’t rely only on subjective reports. Each user submission is validated and enriched using satellite data from the Copernicus program. By combining human input with objective Earth observation data, we create a more accurate and dynamic picture of environmental risks.
We then assess the severity of each situation and aggregate reports weekly. Based on both the number of complaints and the calculated risk level, validated alerts are automatically forwarded to the relevant government authorities, ensuring that critical issues receive attention. Our platform acts as a highly accurate, automated early-warning system that eliminates "false alarms" and directs government resources exactly where they are needed most.
EU Space Technologies
To validate user reports and assess the true severity of the situation, we heavily rely on the Copernicus program, specifically harnessing data from Sentinel-1, Sentinel-2, and Sentinel-3:
Value Brought:Integrating this space data is the backbone of our verification system. It transforms subjective citizen complaints into objective, scientifically backed alerts, ensuring authorities only spend resources on verified, high-risk situations. We than compare this data to label the pins into risk grades so that the pins with higher risk grades will have priority to be forwarded faster to the authorities.
We are tackling Challenge #3: Disaster Risk Monitoring. Our solution provides a comprehensive, 360-degree approach to managing and protecting water resources by monitoring the extremes of the water cycle alongside water quality. By actively tracking floods (water excess), droughts (water scarcity), and pollution/waste (water quality degradation), we create an early-warning safety net. Our platform bridges the gap between affected local communities and national policymakers, directly contributing to the proactive management of water resources and mitigating the destructive impacts of water-related disasters before they escalate into irreversible crises. The integration of satellite data ensures that water-related risks are not only reported but also scientifically validated. This helps authorities prioritize interventions where they are most needed.
Additionally, by aggregating reports every 7 days and ranking them based on severity and frequency, we provide decision-makers with actionable, structured insights instead of scattered complaints.
Team
· Mario Lapusteanu: Mario specializes in processing Copernicus satellite imagery and calculating the key environmental indicators (NDVI, NDWI).
Designed and implemented the web platform from scratch, including the interactive Mapbox integration, user interface, and backend logic for handling reports and data processing.
· CapbunAlex: Alex built the core architecture of our custom website and integrated the Mapbox mapping functionalities.
Responsible for integrating and processing Copernicus Sentinel data (Sentinel-1, Sentinel-2, Sentinel-3), extracting key indicators such as NDVI, NDWI, soil moisture, flood extent, and pollution metrics.
· Matei:Matei designed the logic for the 7-day aggregation system and the risk-degree calculation algorithm.
Developed the methodology for comparing satellite indicators with user reports and determining the severity levels (low, medium, high risk), as well as the logic for prioritizing alerts.
Focused on user experience and platform structure, ensuring the reporting process is simple, intuitive, and accessible while maintaining clarity in data visualization.
· Yusuf:Yusuf coordinated the project vision, designed the user interface for seamless pin-dropping, and ensured alignment with the hackathon's core challenges.
Managed the overall workflow, ensured alignment between technical components, and defined how validated reports are aggregated weekly and sent to authorities based on risk level and frequency.