The field of urban intelligence and collaborative perception is witnessing significant developments, with a focus on creating unified simulation platforms, synthesizing immersive 3D urban scenes, and improving air quality management. Researchers are exploring innovative approaches to integrate multi-modal data, enable seamless perception across heterogeneous multi-agent systems, and develop pragmatic heterogeneous collaborative perception mechanisms. Noteworthy papers in this area include TranSimHub, which presents a unified simulation platform for air-ground collaborative intelligence, and Skyfall-GS, which proposes a framework for synthesizing large-scale 3D urban scenes from satellite imagery. Additionally, papers like CityAQVis and SmartSustain Recommender System demonstrate the potential of ML-driven visual analytics and user-centric interfaces in improving situational awareness and supporting data-driven decision-making in air quality management and sustainable city trip planning. Other notable works, such as Background Fades, Foreground Leads and Pragmatic Heterogeneous Collaborative Perception via Generative Communication Mechanism, highlight the effectiveness of context-enriched foreground sharing and generative communication mechanisms in enhancing collaborative perception capabilities.