Although the use of remote sensing data for urban areas was demonstrated in various studies, mapping urban land use and land cover is challenging. Among others the spectral heterogeneity in urban imagery is very high and spectrally similar materials might occur on different surface types. Besides spectral ambiguities, high frequent spatial patterns of urban land cover categories result in a relatively high number of mixed pixels. Behind these facts common multispectral sensors can be limited to differentiate urban land use cover categories, while hyperspectral imaging is probably the most valuable single data source.
With the Environmental Mapping and Analysis Program (EnMAP), an upcoming German satellite mission, a new imaging spectrometer with high signal-to-noise ratio at medium spatial resolution will become available. The 232 bands of the instrument cover the 420 –2.450 nm range of the electromagnetic spectrum, with a spatial resolution of 30 m x 30m. Regarding the expected high data quality, the wide spatial coverage of 900 km2 per scene and the global revisit rate of 21 days, EnMap data become even more attractive. Nevertheless, it is well known that increasing data dimensionality and high redundancy of hyperspectral data might cause problems during data analysis. Hence, the development of adequate methods for image analysis is an important ongoing research topic in the field of remote sensing.
The main objective of the joint research project is the development of adequate methods for analyzing EnMap data and focus on the enhanced monitoring of urban areas. The project takes place in close cooperation with project partners at the University Bochum. The subproject at the Freie Universität Berlin aims at the development of adequate methods for (i) (subpixel)-classification of urban areas, using hyperspectral data and (ii) fusion of hypespectral data with TerraSAR-X and RapidEye data.
Prof. Dr. Carsten Jürgens, Ruhr-Universität Bochum, Geographisches Institut, AG Geomatik
Dr. Uta Heiden, Deutsches Fernerkundungsdatenzentrum (DLR-DFD), Team „Angewandte Spektroskopie“