This proceedings volume introduces recent work on the storage, retrieval
and visualization of spatial Big Data, data-intensive geospatial
computing and related data quality issues. Further, it addresses
traditional topics such as multi-scale spatial data representations,
knowledge discovery, space-time modeling, and geological applications.
Spatial analysis and data mining are increasingly facing the challenges
of Big Data as more and more types of crowd sourcing spatial data are
used in GIScience, such as movement trajectories, cellular phone calls,
and social networks. In order to effectively manage these massive data
collections, new methods and algorithms are called for. The book
highlights state-of-the-art advances in the handling and application of
spatial data, especially spatial Big Data, offering a cutting-edge
reference guide for graduate students, researchers and practitioners in
the field of GIScience.