This study examines the multiple determinants of public satisfaction with high-rise urban forms in Muscat, Oman, in the context of rapid urbanization and the need to protect and conserve culture. Based on a conceptual framework that included six latent variables—Cultural Harmony, Economic Benefit, Environmental Experience, Social Perception, Urban Connectivity, and Visual Appeal—data collected from city residents were analyzed using the quantitative technique of Partial Least Squares Structural Equation Modeling (PLS-SEM). The model results showed that all relationships were supported, with Urban Connectivity, Cultural Harmony, and Visual Appeal having the strongest effects on satisfaction. These findings indicate that public satisfaction with high-rise developments is influenced by the perceived integration of infrastructure, harmony with local architectural traditions, and coherently attractive views. Environmental Experience, Social Perception, and Economic Benefit had smaller, though still significant, effects, confirming the multidimensional nature of urban appraisal. This study therefore calls for a development approach that balances technical, environmental, cultural and tourism-oriented objectives. As such, this work contributes to the existing literature on urban and societal studies by examining a multifaceted model of urban satisfaction and providing beneficial recommendations to enhance the continuing debate on sustainable and contextual urbanism in the Gulf states.

Climate change has already begun to take visible effect globally in recent years. Given the climate change paradox and urbanization trends, cities' success would not only depend on smartness and sustainability, but also resilience to all forthcoming economic, environmental, or behavioral changes. Numerous technologies have surfaced and proved effective in CO₂ removal from the local environment. However, the optimal placement of these smart filters is a complex task and require logical and strategic decision-making. Determining the optimal location is one of the key factors for establishing a network of smart air filters. This study used a GIS-based suitability analysis for identifying optimal locations for smart filters based on pollution hotspots (population and spatial proximity to industry, commercial centers, roads, high-traffic areas, and intersections). The spatial analysis involves the determination and preparation of input layers, ranking layers, assigning weights to each criterion, and generation of a suitability map. The sites with a higher suitability score (7 or above) are optimum sites for air filters. The sites are spatially distributed over different regions. The findings revealed that GIS-based suitability analysis can be an effective technique for placing smart filters within an urban environment. These findings can help decision-makers to prioritize the location considering environmental constraints. The proposed solution aims to pave the way for fostering resilient, smart, and sustainable cities through a community sensing platform targeting hotspots within spatial variations.