Abstract
The increasing availability of geospatial data offers great opportunities for advancing scientific discovery and practices in society. Effective and efficient processing of geospatial data is essential for a wide range of Digital Earth applications such as climate change, natural hazard prediction and mitigation, and public health.However, the massive volume, heterogeneous, and distributed nature of global geospatial data pose challenges in geospatial information processing and computing. This chapter introduces three technologies for geospatial data processing: highperformance computing, online geoprocessing, and distributed geoprocessing, with each technology addressing one aspect of the challenges. The fundamental concepts, principles, and key techniques of the three technologies are elaborated in detail, followed by examples of applications and research directions in the context of Digital Earth. Lastly, a Digital Earth reference framework called discrete global grid system (DGGS) is discussed.
| Original language | English (US) |
|---|---|
| Title of host publication | Manual of Digital Earth |
| Publisher | Springer Nature |
| Pages | 191-227 |
| Number of pages | 37 |
| ISBN (Electronic) | 9789813299153 |
| ISBN (Print) | 9789813299146 |
| DOIs | |
| State | Published - Jan 1 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
All Science Journal Classification (ASJC) codes
- General Earth and Planetary Sciences
- General Environmental Science
- General Energy
- General Computer Science
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