- Explore the potential of innovative approaches for spectral unmixing for improved land cover parameterisation of urban biophysical models, using airborne hyperspectral data, and assess the transferability of the approaches proposed to imagery of lower spatial and/or spectral resolution acquired by current and future spaceborne multispectral and hyperspectral sensors.
- Examine the use of spectral and LiDAR remote sensing data for characterising chemical and structural properties of urban vegetation for improved land cover parameterisation of urban biophysical models.
- Consolidate chemical and structural properties of the urban environment, derived by remote sensing, by defining a local climate zone (LCZ) typology that is far better suited to characterize urban climatic conditions than traditional land cover datasets typically employed for urban climate modelling.
- Develop a quantitative ecosystem service mapping tool on urban water regulation making optimal use of the detailed, high-resolution remote sensing based characterisation of the urban ecosystem.
- Develop a simulation framework for assessing impacts of urban growth and alternative urban planning scenarios on urban heat and water regulation, based on an integration of agent-based modelling of human activities at neighbourhood level, and grid-based, remote sensing supported modelling of biophysical processes.