As cities and urban areas around the world continue to grow in population size, many regions are seeking sustainable and efficient methods for handling infrastructural issues.
Geospatial data is a trending source for properly optimizing common urban processes including traffic management and sprawl analysis.
Despite its various benefits, many cities do not yet know how to efficiently handle this advanced data, expressing a need for modern methods of computing and algorithmic approaches.
Urban Spatial Data Handling and Computing provides emerging research exploring the theoretical and practical aspects of advanced computing mechanisms and algorithms for handling geospatial data in urban environments.
Featuring coverage on a broad range of topics such as crowd modeling, location-based services, and cloud-based storage, this book is ideally designed for researchers, practitioners, urban planners, data analysts, civil engineers, developers, scientists, academicians, and students seeking current research on using spatial data for sustainable urban management.