Integrating camera imagery, crowdsourcing, and deep learning to improve high-frequency automated monitoring of snow at continental-to-global scales
Snow is important for local to global climate and surface hydrology, but spatial and temporal heterogeneity in the extent of snow cover make accurate, fine-scale mapping and monitoring of snow an enormous challenge. We took 184,453 daily near-surface images acquired by 133 automated cameras and processed them using crowdsourcing and […]