Terra

Terra enables integrated access, analysis, and transformation of large-scale spatio-temporal raster and vector datasets for geospatial science and big-data research.

Key Features:

• Unified Framework: Integrates raster and vector data structures to support combined analysis on big-data platforms.
• Spatio-Temporal Analysis: Integrates big spatial data repositories with computation platforms to enable spatio-temporal analysis of geospatial datasets.
• Scalability: Incorporates scalable geospatial platforms to address data processing and analysis bottlenecks as data volumes grow.
• Comparative Platform Analysis: Performs comparative studies between PostgreSQL with PostGIS and SciDB, identifying SciDB as preferable for scalable raster zonal analyses within the IPUMS-Terra infrastructure.

Scientific Applications:

• Environmental Science: Enables analysis of spatio-temporal environmental datasets to study spatial patterns and temporal changes.
• Urban Planning: Supports urban planning studies requiring integrated spatial and temporal analysis of urban datasets.
• Public Health: Supports public health research that examines spatial patterns and temporal changes in health-related geospatial data.

Methodology:

The methodology involves development of a cyberinfrastructure that harmonizes disparate raster and vector data structures and enhances computational capabilities for large datasets. It also uses comparative platform analyses between PostgreSQL with PostGIS and SciDB to identify optimal solutions (for example, SciDB for scalable raster zonal analyses) within the IPUMS-Terra infrastructure.