A Generic Framework for Library-based Mapping
of Urban Areas
The main hypothesis of GENLIB is that a Generic Urban Library, once it becomes sufficiently representative, can be used to perform accurate mapping with any optical sensor, on any site and for any application, assuming that the used image data are reasonably suited for the task.
To test this hypothesis, we formulate the following operational objectives:
Define a metadata model that encompasses all the information needed for processing and querying.
Propose a hierarchical labeling scheme for urban cover types that is conform with the EAGLE framework.
Provide a toolset for dynamic use of the GUL, including expansion, management and optimization.
Build a first version of the GUL using a multi-site collection of urban hyperspectral imagery.
Deliver a proof of concept by performing a series of mapping experiments with the GUL.