  Geospatial big data plays a major role in the era of big data, as most data
today are inherently spatial, collected with ubiquitous location-aware sensors.
Efficiently collecting, managing, storing, and analyzing geospatial data
streams enables development of new decision-support systems and provides
unprecedented opportunities for business, science, and engineering. However,
handling the "Vs" (volume, variety, velocity, veracity, and value) of big data
is a challenging task. This is especially true for geospatial big data, since
the massive datasets must be analyzed in the context of space and time. High
performance computing (HPC) provides an essential solution to geospatial big
data challenges. This chapter first summarizes four key aspects for handling
geospatial big data with HPC and then briefly reviews existing HPC-related
platforms and tools for geospatial big data processing. Lastly, future research
directions in using HPC for geospatial big data handling are discussed.
