Spatial Data Science

10.

Ethics and Privacy in Spatial Data Science

10.1.

Privacy Concerns

10.1.1.

Location Privacy

10.1.2.

Trajectory Privacy

10.1.3.

Geoprivacy Concepts

10.2.

Anonymization Techniques

10.2.1.

Spatial Generalization

10.2.2.

Temporal Generalization

10.2.3.

Suppression Methods

10.2.4.

Perturbation Methods

10.3.

Ethical Considerations

10.3.1.

Informed Consent

10.3.2.

10.3.3.

Surveillance Implications

10.3.4.

Algorithmic Bias

10.4.

Legal and Regulatory Framework

10.4.1.

Data Protection Laws

10.4.2.

Spatial Data Rights

10.4.3.

Cross-border Data Transfer

10.4.4.

Compliance Requirements

Previous

9. Big Data and Cloud Computing in Spatial Science

Go to top

Next

11. Applications and Case Studies