Spatial Data Science

9.

Big Data and Cloud Computing in Spatial Science

9.1.

Distributed Spatial Computing

9.1.1.

Parallel Processing Concepts

9.1.2.

MapReduce for Spatial Data

9.1.3.

Spark for Spatial Analytics

9.1.4.

Distributed Spatial Databases

9.2.

Cloud-based Spatial Platforms

9.2.1.

Infrastructure as a Service

9.2.2.

Platform as a Service

9.2.3.

Software as a Service

9.2.4.

Scalability Considerations

9.3.

Big Spatial Data Challenges

9.3.1.

Volume Challenges

9.3.2.

Velocity Challenges

9.3.3.

Variety Challenges

9.3.4.

Veracity Challenges

9.4.

Streaming Spatial Data

9.4.1.

Real-time Processing

9.4.2.

Event Detection

9.4.3.

Continuous Queries

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8. Advanced Spatial Analysis Topics

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10. Ethics and Privacy in Spatial Data Science