Recent years have seen the emergence of many new and valuable spatial datasets such as
trajectories of cell-phones and Global Positioning System (GPS) devices, vehicle engine …

This vision paper reviews the current state-ofart and lays out emerging research challenges
in parallel processing of spatial-temporal large datasets relevant to a variety of scientific …

The increasing availability of geospatial data offers great opportunities for advancing
scientific discovery and practices in society. Effective and efficient processing of geospatial …

An R-tree is a data structure for organizing and querying multi-dimensional non-uniform and
overlap** data. Efficient parallelization of R-tree is an important problem due to societal …

In this paper, we introduce our hierarchical filter and refinement technique that we have
developed for parallel geometric intersection operations involving large polygons and …

We summarize the need and present our vision for accelerating geo-spatial computations
and analytics using a combination of shared and distributed memory parallel platforms, with …

Geospatial Data Science Techniques and Applications Page 1 1 1 Geospatial Data Science:
A Transdisciplinary Approach Emre Eftelioglu, Reem Y. Ali, Xun Tang, Yiqun **e, Yan Li …

Geometric intersection algorithms are fundamental in spatial analysis in Geographic
Information System (GIS). This dissertation explores high performance computing solution …

Discovery of interesting paths and regions in spatio-temporal data sets is important to many
fields such as the earth and atmospheric sciences, GIS, public safety and public health both …

Over the last decade, there has been a significant growth in the availability of cheap raw
spatial data in the form of GPS trajectories, activity/event locations, temporally detailed road …