Enhanced Solar Energy Management in the Azores Using Automated Satellite Detection
About this good practice
Automatic detection of solar panels using VHR and HR satellite imagery enhances monitoring and management of solar installations in the Azores, supporting renewable energy, resource optimization, and sustainability goals.
Problem and Context
The Azores lack up-to-date data on solar panel installations, complicating planning and expansion. As the region advances renewable energy, accurate data is vital to optimizing solar potential and minimizing environmental impact. The challenge of manual surveys across dispersed islands underscores the need for innovative solutions.
Implementation and Objective
Rooftop panels are detected using VHR satellite imagery with 0.3 meters/pixel resolution (e.g., WorldView-3 RGB), while HR data at 10 meters/pixel (e.g., Sentinel-2 RGB) identifies large photovoltaic parks. Machine learning algorithms, such as YOLO or SAM by Meta AI, detect and classify solar panels. These models are trained on existing datasets and updated with new Azorean data. Cloud masks and targeted analysis reduce false detections.
Data is integrated into a GIS for detailed analysis, visualization, and updates with new imagery. This system aids in monitoring changes, site selection, planning, and performance monitoring through long-term data analysis and solar power potential mapping.
Stakeholders and Beneficiaries
Government bodies, energy companies, local communities, and environmental groups.
Resources needed
Approximate effort of 6 PM, total costs of about 30k to 100k euros depending on availability of VHR imagery up to date from the region.
Evidence of success
Automatic detection has been shown feasible with a live demonstration performed publicly on the 3ºLDD SATSDIFACTION project 27-7-24. Its expansion to a wider scale and to all regions of Azores and integration with existing databases is possible.
Potential for learning or transfer
Other regions may adopt this good practice as means to promote efficient solar energy deployment practices, which is considered of key importance for regions requiring energy independence or renewable energy practices with ambitious targets.
Further information
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Good practice owner
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