This paper introduces a novel two-step method for predicting urban expansion using time-series satellite imagery. The approach combines semantic image segmentation with a CNN-LSTM model to learn temporal features. Experiments on satellite images from Riyadh, Jeddah, and Dammam in Saudi Arabia demonstrate improved performance compared to existing methods based on Mean Square Error, Root Mean Square Error, Peak Signal to Noise Ratio, Structural Similarity Index, and overall classification accuracy.
Dr. Tarek Ali Fadaak, a Shura Council member, discussed the importance of environmental balance and improved resource management in Saudi urban planning during a 2018 KAUST lecture. He highlighted challenges like insufficient and poorly utilized open spaces in Saudi cities, emphasizing the need for aesthetic improvements and more public spaces. Fadaak stressed the importance of investing in the education of Saudi youth to drive future development and address these urban planning challenges. Why it matters: This underscores the ongoing focus on sustainable urban development and the role of Saudi talent in shaping future cities within the Kingdom, aligning with Vision 2030 goals.
Siemens CTO Rainer Speh spoke at KAUST about smart cities, noting that urban populations are growing, especially in cities like Riyadh and Jeddah. Cities consume two-thirds of the world's energy and generate 70% of CO2 emissions. Siemens is working on a driverless subway system in Riyadh as part of its smart city initiatives. Why it matters: Smart city initiatives are crucial for managing resources and reducing emissions in rapidly growing urban centers in Saudi Arabia.
MIT researchers have developed a new AI system that uses satellite imagery and street-level photos to add details to digital maps. The AI model can identify features like building footprints, road networks, and vegetation cover with high accuracy. It then enriches existing maps by adding these features, improving their usability for navigation and urban planning. Why it matters: This technology can significantly enhance the quality and detail of digital maps, particularly in areas where up-to-date map data is lacking, enabling better AI-powered applications.
Khaled Alrashed, president and CEO of Saudi Electricity Company for Projects Development, discussed the challenges of future smart cities at a KAUST event. He emphasized the importance of smart grids, AI, and large-scale optimization for improving urban living. The Saudi Electricity Company is partnering with KAUST, including using the Shaheen supercomputer, to develop these technologies and predict grid load. Why it matters: This collaboration highlights Saudi Arabia's ambition to become a leader in smart city technology and renewable energy, leveraging local expertise and resources.
This article discusses the evolution of mobile extended reality (MEX) and its potential to revolutionize urban interaction. It highlights the convergence of augmented and virtual reality technologies for mobile usage. A novel approach to 3D models, characterized as urban situated models or “3D-plus-time” (4D.City), is introduced. Why it matters: The development of MEX and 4D.City could significantly enhance user experience and analog-digital convergence in urban environments, offering new possibilities for human-computer interaction.