Better models of urban heat islands

Advanced AI techniques are being used to improve predictions of temperature differences between cities and surrounding rural areas. This temperature difference, called Surface UHI (SUHI), is measured using Land Surface Temperature (LST). The paper explores how advanced AI techniques like Convolutional Neural Networks (CNNs) and generative adversarial networks (GANs) can predict SUHI, and analyze the relationship between different urban areas (called Local Climate Zones or LCZs) and their temperatures. By using AI to study these connections, city planners can make better decisions about how to design and build cities to minimize heat. For example, AI can predict how changes in building density or green spaces might affect temperature.