Research activities in the Cartography and GIS Research Group (CGIS) mainly focus on land-use/land-cover mapping from remotely sensed data, with emphasis on urban areas, and on spatial analysis of urban dynamics. Special attention in the remote sensing work goes to the use of knowledge-based methods and machine learning approaches for image interpretation, relying on spectral, textural as well as contextual information. 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. Developing methods to extract information from remotely sensed data that is useful for local and regional decision making is an important concern in most of the work done by the lab. In recent years, CGIS also built up expertise in hyperspectral remote sensing in different application domains, from characterizing ecotopes in ecologically valuable areas (Natura 2000) to detailed mapping of man-made surface types in urban areas. We also investigated the use of superresolution methods for improving information extraction from satellite data through multi-angle image acquisition. Recently a new line of research was initiated, focusing on the improvement of urban growth models through integration of information on the density of residential, industrial and commercial activities in the modelling. Time series of remote sensing data are used as a input source for the modelling, together with various socio-economic data. Specific attention in this research goes to agent-based modelling approaches for simulation of urban dynamics and to the interaction between urban growth and mobility.