Automatically extract building footprints with 95%+ accuracy using our advanced AI/ML models (YOLO, DeepLab3, SAM, UNet). Perfect for urban planning, 3D city modeling, and GIS applications.
Accuracy Rate
Buildings Processed Daily
Countries Covered
Time Savings (%)
Our building footprint generation leverages multiple state-of-the-art machine learning models for optimal results.
Real-time object detection for initial building identification with high precision and speed.
Semantic segmentation for precise building boundary extraction with atrous convolution.
Zero-shot generalization for building segmentation across diverse architectural styles.
Encoder-decoder network for precise building segmentation with skip connections.
Advanced algorithms for polygon simplification, edge refinement, and topology correction.
Scalable infrastructure for processing large areas with distributed computing.
Our integration with Meta's Segment Anything Model (SAM) allows for precise building segmentation with minimal input. Search by coordinates to see SAM in action:
Enter latitude and longitude coordinates to center the map on your area of interest.
High-resolution satellite imagery provides the visual context for building detection.
Our system runs SAM on the satellite imagery to identify and segment building footprints.
View segmented building footprints overlaid on the satellite imagery with detailed metrics.
Download results in multiple formats or integrate with your existing GIS workflows.
From satellite imagery to clean vector building footprints in 5 simple steps:
Upload satellite/aerial imagery (RGB, multispectral, or LiDAR) in various formats and resolutions.
Our ensemble of models identifies buildings with high confidence scores, filtering out false positives.
Precise boundary extraction using semantic segmentation models adapted to various building types.
Conversion of raster masks to clean vector polygons with optimized vertex placement.
Automated validation against ground truth data with optional human review for critical projects.
Our building footprint data powers diverse applications across multiple industries.
Analyze urban growth patterns, density metrics, and zoning compliance with accurate building data.
Calculate rooftop solar potential by analyzing building footprints and orientations.
Enhance digital maps with building footprints for better routing and location services.
Analyze property sizes, shapes, and neighborhood characteristics for valuation.
Assess building damage post-disaster and plan emergency response routes.
Optimize cell tower placement by analyzing building density and distribution.
Hear directly from organizations transforming their operations with our building footprint technology.
"The accuracy of Atlas Geotech's building footprints saved us months of manual digitization work for our city's 3D modeling project."
GIS Manager, City Planning Department
"We processed 50,000 buildings in 24 hours with 94% accuracy - something that would have taken our team 6 months manually."
CTO, Solar Energy Startup
"The AI models adapt surprisingly well to different architectural styles across our 12-country coverage area."
Director, International Mapping Consortium
Transform your geospatial workflows with our AI-powered building extraction. Request a demo or contact our team to discuss your project.
High-resolution satellite or aerial imagery (0.3m-1m resolution)
AI models analyze and extract building features
Clean vector building footprints
