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.
