Air Quality Categorization
Our advanced categorization system automatically classifies monitoring sites based on surrounding land use, traffic patterns, and environmental factors to provide context for your air quality data.
Categorization AI Technology
Our Categorization AI uses machine learning to classify monitoring sites based on their surroundings. The system analyzes:
- •Land use patterns (residential, commercial, industrial)
- •Proximity to roads and traffic density
- •Natural features like vegetation and water bodies
- •Building density and urban morphology
- •Known pollution sources in the vicinity
The AI model categorizes sites into standardized classes including:
- •Urban Background: Residential areas away from major roads
- •Urban Traffic: Sites near major roads with high traffic
- •Industrial: Areas dominated by industrial activities
- •Rural: Areas with minimal human influence
- •Mixed Use: Areas with multiple land use types
How It Works
Select Locations
Click on the map, upload coordinates, or enter them manually to select locations for categorization.
AI Analysis
Our AI analyzes the surrounding area using OpenStreetMap data and environmental factors.
Get Categorization
Receive detailed categorization for each location, including area type and land use.
Key Benefits
Contextual Understanding
Understand the context of your air quality readings based on the surrounding environment.
Standardized Classification
Use consistent categories across your monitoring network for better comparability.
Batch Processing
Categorize multiple locations at once, saving time and effort.
Data Export
Export categorization results as CSV for further analysis or integration with other tools.