Cities are critical research subjects in carbon neutrality, considering they produce more than
70% of greenhouse gas emissions and their crucial role in taking climate actions. The …

The growing interest in artificial intelligence (AI) and Large Language Models (LLMs) in
particular, such as Generative Pre-trained Transformers (GPT) and Bidirectional Encoder …

Climate change and rapid urbanisation exacerbated multiple urban issues threatening
urban sustainability. Numerous studies integrated machine learning and remote sensing to …

Urban scene understanding and functional identification are essential for accurately
characterizing the spatial structure and optimizing the city layouts during rapid urbanization …

Increasing data generated in cities provide new opportunities for analyzing urban
characteristics at high resolution. Data integration can enhance our understanding in urban …

The Internet of Things (IoT), inspired by the tremendous growth of connected heterogeneous
devices, has pioneered the notion of smart city. Various components, ie, smart …

Smart Cities already surround us, and yet they are still incomprehensibly far from directly
impacting everyday life. While current Smart Cities are often inaccessible, the experience of …

Urban prediction tasks refer to predicting urban indicators (eg, traffic, temperature, etc.)
using urban big data, which is crucial for understanding the urban patterns, and further …

In recent years, the development of intelligent transportation systems (ITS) has involved the
input of various kinds of heterogeneous data in real time and from multiple sources, which …

Autonomous driving technology, a catalyst for revolutionizing transportation and urban
mobility, has the tend to transition from rule-based systems to data-driven strategies …