Abstract
The 21st century is experiencing simultaneous changes in global population, urbanization, and climate. These changes, along with the rapid growth of geospatial data and increasing popularity of data discovery, access, and analytics techniques, lead to the promising future of innovation and achievements in geospatial and spatiotemporal thinking, computing, and application. However, big geospatial data bring forth challenges that require the cutting-edge science and technology to address. In this chapter, we highlight some of the characteristics and challenges in geospatial and spatiotemporal data discovery, management, processing, and analytics, and provide solutions based on recent research achievements as case studies. These study cases provide concrete examples of challenges faced when handling geospatial and spatiotemporal big data and the potential solutions in high level of accuracy, interoperability, and scalability.
| Original language | English (US) |
|---|---|
| Title of host publication | Federal Data Science |
| Subtitle of host publication | Transforming Government and Agricultural Policy Using Artificial Intelligence |
| Publisher | Elsevier |
| Pages | 177-191 |
| Number of pages | 15 |
| ISBN (Electronic) | 9780128124437 |
| ISBN (Print) | 9780128124444 |
| DOIs | |
| State | Published - Jan 1 2017 |
All Science Journal Classification (ASJC) codes
- General Computer Science