Day time and Nighttime Dust Event Segmentation using Deep Convolutional Neural Networks

Airborne dust is known to have detrimental effects on human health, the environment, and aviation. Earth-observing satellites have been used to monitor dust events using visible and infrared bands, but the presence of clouds and smoke makes it a difficult phenomenon to identify. Moreover, nighttime dust has similar radioactive properties to that of cooler underlying surfaces. We propose a dust det...