Big data is currently the hottest topic for data researchers and scientists with huge interests from the industry and federal agencies alike, as evident in the recent White House initiative on "Big data research and development". Within the realms of big data, spatial and spatio-temporal data is one of fastest growing types of data and poses a massive challenge to researchers who deal with analyzing such data. With advances in remote sensors, sensor networks, and the proliferation of location sensing devices in daily life activities and common business practices, the generation of disparate, dynamic, and geographically distributed spatiotemporal data has exploded in recent years. In addition, significant progress in ground, air- and space-borne sensor technologies has led to an unprecedented access to earth science data for scientists from different disciplines, interested in studying the complementary nature of different parameters.

The 6th workshop on Analytics for Big Geospatial Data aims to bring together researchers from academia, government and industrial research labs who are working in the area of spatial analytics with an eye towards massive data sizes. The objective of this workshop is to provide a platform for researchers engaged in addressing the big data aspect of spatial and spatio-temporal data analytics to present and discuss their ideas. We invite participants from industry, academia, and government to participate in this event and share, contribute, and discuss the emerging big data challenges in the context of spatial and spatio-temporal data analysis.

The main motivation for this workshop stems from the increasing need for a forum to exchange ideas and recent research results, and to facilitate collaboration and dialog between academia, government, and industrial stakeholders.

We solicit high quality papers in the general areas of data analytics for large scale geospatial data.

All submitted papers will be peer reviewed. If accepted, at least one of the authors must attend the workshop to present the work. Selected accepted papers will be recommended for submission to special issues of journals.