KAUST's Sami Al-Ghamdi is conducting multidisciplinary research on urban sustainability to mitigate climate change and optimize resource consumption. His work supports Saudi Arabia’s Vision 2030, particularly urban gigaprojects like NEOM and Saudi Downtown. He develops computational models to assess the environmental impact of various aspects of the built environment. Why it matters: This research is crucial for advancing sustainable urban development in Saudi Arabia and achieving its ambitious environmental goals.
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.
In a 2018 KAUST lecture, MIT professor Kamal Youcef-Toumi discussed the case of Ordos Kangbashi, a Chinese city designed for a million residents that became a near-ghost town. Despite government incentives, the city struggled due to an economic downturn and lack of social and economic balance. Youcef-Toumi emphasized the importance of the public realm and a balance between social and economic development for successful cities. Why it matters: The analysis provides insights relevant to urban planning in Saudi Arabia and the broader GCC region, where new cities and megaprojects are being developed.