Detecting and Analyzing Solar Panels in Switzerland using Aerial Imagery

Adrian Meyer

Deep Learning Machine-Learning

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A novel method for detecting solar panels and its geometry on aerial imagery is presented. Deep Learning with PyTorch is being used for segmentation. The goal is to know the exact locations, dimensions and potential of every solar installation in Switzerland. It is shown how we labelled the data and how we found a solution to distinguish different solar panel types.

Type: Talk (30 mins); Python level: Beginner; Domain level: Beginner

Adrian Meyer


Adrian F. Meyer is a data scientist for remote sensing and machine learning at the Institute Geomatics, Fachhochschule Nordwestschweiz (Univ.Appl.Sc. North-Western Switzerland).
Currently he is working on several projects mainly focusing on automated image analysis, telemetry, big data processing, deep learning and digital reconstruction. These interests of the animal biologist by training matured during the analysis of geotagged wildlife imagery in Cape Town, South Africa and pushed him to pursue a second career as a M.Sc. in Geoinformation Engineering. Since 2016 he is affiliated with the Institute Geomatics working in not only in active research, but also as a lecturer and drone pilot trainer.