kdmayer/3D-PV-Locator
📦 Open Source Projectkdmayer
A deep learning framework for large-scale detection and 3D mapping of rooftop photovoltaic systems using satellite imagery.
3D-PV-Locator provides a robust pipeline for the automated detection of rooftop-mounted photovoltaic (PV) systems. By integrating advanced computer vision models, specifically DeepLabv3 and Inception-v3, the framework processes high-resolution satellite imagery to segment and classify solar installations. The project is fully Dockerized, ensuring reproducibility and ease of deployment for researchers working on remote sensing and renewable energy analytics. Beyond simple detection, the tool focuses on 3D spatial awareness, allowing for the estimation of solar potential and system capacity at a city or regional scale. This technical approach is critical for grid operators and urban planners who require precise, large-scale datasets to manage the transition to renewable energy. The repository includes the necessary scripts and environment configurations to handle large datasets, making it a valuable asset for environmental data science and infrastructure monitoring.
💡Highlights
- ├─DeepLabv3 & Inception-v3 integration
- ├─Dockerized for easy deployment
- └─Large-scale satellite imagery analysis
🎯For
- ├─Environmental Data Scientists
- ├─Renewable Energy Researchers
- └─Urban Planners