Sit-C a new method using heterogeneous imagery datasets and astronomical tools to detect air pollution.
The OMS estimates that over 7 million people die every year of complications attributed to atmospheric pollution. Air quality has degraded progressively and dramatically in urban environments over the last couple of decades, being a current concern in most metropolitan areas, and the focus of public policy as well as public/private scientific innovation for better diagnostics and better solutions.
At SIC we are developing a method for 3D mapping the sources, affected locations, density, motion, translation, and potential composition of polluted air masses in close to real-time. We do this by leveraging a multidisciplinary approach that encompasses urban and architectural simulation with data science and astronomical techniques, producing a data visualization that enables novel research in air quality, urban policy, private investment, sustainability efforts, and smart transportation.
Our approach, Sit-C, combines satellite remote sensing of air masses and atmospheric conditions, with data obtained from traffic and urban surveillance cameras deployed throughout the city of Santiago, in Chile. These cameras, oftentimes open to public access, are usually placed linearly along main avenues, or scattered around urban milestones, providing walk-though perspectives and locally situated POVs to observe the city, analog to series of cross-sections through urban areas. Satellite sensing provides a large-scale plan view, allowing for precise location of specific conditions across a region.
This collaboration between architects, designers, engineers, and meteorologists, from Chile and Finland, combines digital design, data science, and remote sensing techniques to study air quality. We study suspended particulate matter (SPM) and other molecules, and its spatial behavior over time, through light-occlusion analysis, producing a threedimensional map of the air over a city.
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