ABSTRACT
Urban environments and precincts suffer from urban anomalies such as air and noise pollution. This chapter discusses the value of urban environmental sustainability and provides the application of big data techniques in its regeneration through intelligent monitoring and design procedures. It also delivers a detailed analysis on how the technologies such as fixed stations, WSNs, mobile phone applications and social media enable the identification of urban pollution patterns. With respect to the current environmental pollution analysis of Tehran, as one of the world’s most polluted capital cities which experiences a high level of air and noise pollution, the patterns of PM 2.5 pollution and spatial variation are mostly analyzed through real-time fixed stations data. ArcGIS models are also applied for the analysis of the impacts of urban planning factors including land uses, green spaces, physical forms and transportation in the increase and decrease of PM 2.5 concentration. This chapter, hence, presents the big data-based regeneration opportunities for Tehran by specifying critical regions which are exposed to the highest levels of PM 2.5 concentration. Finally, based on the Geographically Weighted Regression (GWR) analysis, and linear regression, the new areas are proposed for reducing the annual average of PM 2.5 pollution and new urban interventions are developed according to the design principles.
