SkyCam: A Dataset of Sky Images and their Irradiance values

TL;DR

SkyCam provides a comprehensive sky image dataset paired with precise irradiance measurements, facilitating the development of deep learning models for accurate, short-term solar radiation prediction at localized sites.

Contribution

The paper introduces a novel, high-resolution sky image dataset with synchronized irradiance data, enabling advanced deep learning research for solar radiation forecasting.

Findings

Dataset includes images from three locations over a year.

Images are paired with high-accuracy irradiance measurements.

HDR images are created from multiple exposures.

Abstract

Recent advances in Computer Vision and Deep Learning have enabled astonishing results in a variety of fields and applications. Motivated by this success, the SkyCam Dataset aims to enable image-based Deep Learning solutions for short-term, precise prediction of solar radiation on a local level. For the span of a year, three different cameras in three topographically different locations in Switzerland are acquiring images of the sky every 10 seconds. Thirteen high resolution images with different exposure times are captured and used to create an additional HDR image. The images are paired with highly precise irradiance values gathered from a high-accuracy pyranometer.