Knowledge about the existing materials in urban areas has, in recent times, increased in importance. With the use of imaging spectroscopy and hyperspectral remote sensing techniques, it is possible to measure and collect the spectra of urban materials. Most spectral libraries consist of either spectra acquired indoors in a controlled lab environment or of spectra from afar using airborne systems accompanied with in situ measurements. Furthermore, most publicly available spectral libraries have, so far, not focused on facade materials but on roofing materials, roads, and pavements. In this study, we present an urban spectral library consisting of collected in situ material spectra with imaging spectroscopy techniques in the visible and near-infrared (VNIR) and short-wave infrared (SWIR) spectral range, with particular focus on facade materials and material variation. The spectral library consists of building materials, such as facade and roofing materials, in addition to surrounding ground material, but with a focus on facades. This novelty is beneficial to the community as there is a shift to oblique-viewed Unmanned Aerial Vehicle (UAV)-based remote sensing and thus, there is a need for new types of spectral libraries. The post-processing consists partly of an intra-set solar irradiance correction and recalculation of reference spectra caused by signal clipping. Furthermore, the clustering of the acquired spectra was performed and evaluated using spectral measures, including Spectral Angle and a modified Spectral Gradient Angle. To confirm and compare the material classes, we used samples from publicly available spectral libraries. The final material classification scheme is based on a hierarchy with subclasses, which enables a spectral library with a larger material variation and offers the possibility to perform a more refined material analysis. The analysis reveals that the color and the surface structure, texture or coating of a material plays a significantly larger role than what has been presented so far. The samples and their corresponding detailed metadata can be found in the Karlsruhe Library of Urban Materials (KLUM) archive.

To improve the ability of avian radar to process bird information, a statistical analysis method for the bird situation around airport is proposed based on avian radar data. By accumulating a large amount of avian radar data, hotspots of the activity area of bird targets can be determined and taken as a reference point to realise lifecycle management of each bird target from initiation to continuation and finally death. In the process of target tracking, combined with the particle filter method, the probability of several possible events is estimated, leading to completion of the data association and real-time statistics for the number of targets. The simulation results reveal that this method is superior to the traditional logic method regarding the timeliness of multi-target initiation. With the application of the proposed method to avian radar data, the bird population and its basic activity rules can be discovered by fixing the bird habitats around the airport.

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