Cartography and GIS

Research activities of the CGIS group focus on:

Urban remote sensing

Research activities in the CGIS group mainly focus on land-use/land-cover mapping from remotely sensed data, with emphasis on urban areas.  Special attention in this research goes to the use of knowledge-based methods and machine learning approaches for image interpretation, relying on spectral, textural as well as contextual information.

More recently the lab built up expertise in hyperspectral remote sensing in different application domains, from characterizing ecotopes in ecologically valuable areas to detailed mapping of urban surface types. At present the group is also investigating the use of superresolution methods for improving information extraction from satellite data through multi-angle image acquisition. Developing methods to extract information from remotely sensed data that is useful for local and regional decision making is an important concern in much of the work done by the lab.

Monitoring and modeling of urban dynamics

Remote sensing and GIS-driven approaches are developed for monitoring and modelling of urban dynamics, in relation to urban ecology and urban sustainability issues. Specific research topics include mapping and monitoring of urban sprawl, remote-sensing driven calibration of urban growth models, urban green monitoring, urban quality-of-life assessment, analysis of urban form, and impacts of urban growth on the water balance in urbanised areas.

Error modeling and error propagation in GIS

Research activities in the domain of error modeling and error propagation focus on the modeling of uncertainty in categorical data (area-class maps, satellite derived land-cover data). Strategies are developed to explore the spatial structure of uncertainty in categorical GIS coverages and to incorporate this knowledge in the error modeling process.

Research results have been used to estimate the impact of uncertainty in categorical data on the outcome of environmental models that make use of these data (habitat modeling of endangered species, structural landscape classification …). Most of the work on spatial uncertainty modelling is done in collaboration with teams from other disciplines interested in the impact of spatial data uncertainty on the outcome of their models.

Map projection design

Being dominated for almost two centuries by the formulation of analytical solutions to increasingly complex map projection problems, computers cleared the way for a numerical treatment of map projection. Work done in this area focuses on the development of appropriate measures to characterize distortion in small-scale maps, and on the use of these measures for developing new tailor-made map projections with less distortion than standard map projections used for mapping at the global and the continental scale.