Integrity Measures for Hierarchical and Incremental Map Data Acquisition

Qianqian Zou, M. Sc.

Main Supervisor:  M. Sester

Data acquired collaboratively by several traffic participants is characterized by different levels of detail, accuracy and completeness. Integrating and assembling this information to a consistent dynamic map requires integrating and propagating quality and integrity measures across the different levels of representation. The project involves the definition of multiscale representations of quality measures, as well as mechanisms for the propagation of those measures across the different representations. Methods from cartographic generalization, machine learning and optimization will be required.