Aerial view of photovoltaic panels on rooftop

How to identify solar panels on rooftops from satellite imagery?

In this post, we discuss how you can identify solar panels on rooftops from satellite imagery using Amazon Rekognition Custom Labels. High-resolution satellite imagery of urban areas provides an aerial view of rooftops. You can use these images to identify solar panel installations.

Can high-resolution satellite imagery be used to identify solar panels?

High-resolution satellite imagery of urban areas provides an aerial view of rooftops. You can use these images to identify solar panel installations. But it is a challenging task to automatically identify solar panels with high accuracy, low cost, and in a scalable way.

Which Visualization Library is used for rooftop photovoltaics?

The library for visualization is matplotlib. The project target is to segment in aerial images of Switzerland (Geneva) the area available for the installation of rooftop photovoltaics (PV) panels, namely the area we have on roofs after excluding chimneys, windows, existing PV installations and other so-called ‘superstructures’.

Can U-nets be used to segment roof-top PV panels in satellite images?

In 2020, Zhuang et al. proposed a cross-learning driven U-Net (CrossNets) method to segment roof-top PV panels in satellite images. However, the above studies focused on using the universal machine learning frameworks such as CNN, U-Net, DeepLabv3 and etc., lacking analyzing the characteristics of PV image data and improving the models.

How many annotated solar panels are there?

The dataset of 2,542 annotated solar panels may be used independently to develop detection models uniquely applicable to satellite imagery or in conjunction with existing solar panel aerial imagery datasets to support generalized detection models.

Can solar panels be segmented from images?

A field survey with manual data collection can obtain rooftop PV panel installation capacity with high precision but labor-intensive, time-consuming, and expensive. Using a satellite/aerial-image-based approach offers a new way to solve large-scale PV panel installation – segmenting solar panels from images, and has been widely discussed recently.