A crowdsourced dataset of aerial images with annotated solar photovoltaic arrays and installation metadata.

ABSTRACT: Photovoltaic (PV) energy generation plays a crucial role in the energy transition. Small-scale, rooftop PV installations are deployed at an unprecedented pace, and their safe integration into the grid requires up-to-date, high-quality information. Overhead imagery is increasingly being used to improve the knowledge of rooftop PV installations with machine learning models capable of automatically mapping these installations. However, these models cannot be reliably transferred from one region or imagery source to another without incurring a decrease in accuracy. To address this issue, known as distribution shift, and foster the development of PV array mapping pipelines, we propose a dataset containing aerial images, segmentation masks, and installation metadata (i.e., technical characterist

SUBMITTER: Kasmi G 

PROVIDER: S-EPMC9884299 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature