Atlas of Lighting is an interactive mapping tool that provides an integrated, scientific understanding of the dynamics of metropolitan areas around the world. The technology merges both qualitative and quantitative understanding of how cities operate and makes comparative analysis of city dynamics more accessible. The tool can be geared towards business analytics by helping companies identify hot and cold spots in urban environments and analyze social media for market trends. It can be used by researchers to visualize human activity and develop a deeper understanding of demographics. Additionally, it can be used to facilitate integrated, science-based policy making.
Atlas of Lighting taps into the smart city movement and helps city makers better understand the data they already have by providing visualizations. Other “atlas” systems exist that serve to process citywide data and display curated graphics and maps; however, Atlas of Lighting surpasses these technologies by providing interactive visualization techniques that let users interact with the data and display it to their preferences. This can include changing the mode of display, selecting and querying data, or simultaneously visualizing data as a chart and a map to see dynamic relationships between datasets and/or particular geographic areas. With its customizable nature, the tool helps users to investigate different datasets faster and more efficiently. The tool also integrates several case studies in order to provide motivation and detailed guidance on research methods to a user of the tool.
Atlas of Lighting collects datasets using Open Data platforms and APIs from various sources. These sources include: The American Community Survey 2014; 5 Year Estimate; National Land Cover Database 2011; VIIRS Nighttime Lights dataset of Earth Observation Group; Google Places API; Instagram API; Street View Image API; and Google Cloud Vision API documentation.
The data are collected, automatically analyzed and pre-processed. Then, based on the desired type of data, the data is sent to a GIS software for further analysis and processing. This allows data to be merged into grid cells which are then fed into the web application through .csv files. The tool is composed of a database, a web application, a web server, and a migration/data service app and uses Google Cloud Platform's Compute Engine Service VM. The Inventors build their own development, deployment and management systems on top of this, and opt to use microservices architecture instead of serving database and application from different platforms. Through container technology, each of these components run independently but in a coordinated way.
- Tool allows for numerous interactive and application-specific methods of data visualization
- Customizable nature allows users to investigate different datasets faster and more efficiently
- Users provided with motivation and detailed guidance on research methods that may be employed for specific data