GIS-driven computer vision to improve power distribution monitoring using satellite images

• GIS-driven aerial remote sensing supports large-scale power distribution monitoring. • Satellite images enable detection of clandestine areas linked to energy theft. • Vegetation management can benefit from GIS-driven aerial remote sensing. • Automatic estimation of rooftop PV rated capacity to update utility database. Solutions enabled by recent technological advancements and the increased availability of free geospatial images and open-source tools have demonstrated the potential to enhance tasks in various areas; however, electric power delivery remains insufficiently explored. This paper presents a proof-of-concept study exploring novel integrations of satellite imagery and geographic information systems (GIS) data to support three key tasks of distribution utilities worldwide: identifying clandestine connections to the system (electricity theft), mapping vegetation encroachment that poses risks to the network, and detecting and estimating the installed capacity of rooftop photovoltaic systems for automatically feeding or updating the utility database. The solutions rely on open-source tools, including artificial intelligence, image processing, and color segmentation, and are validated using real data from a Brazilian utility. The results demonstrate that the integration of GIS-driven and image-based aerial remote sensing techniques offers scalable and cost-efficient alternatives to conventional inspection methods.