Urban expansion and densification pose a challenge to urban biodiversity. Rapid estimation of biodiversity could help urban planners balance development and conservation goals. While the Normalised Difference Vegetation Index (NDVI) has proven useful for predicting urban bird diversity, new products derived from remote sensing, such as vegetation volume, could provide more detailed descriptions of available habitat, potentially improving biodiversity predictions. We evaluated the effectiveness of NDVI and vegetation volume as predictors of urban bird diversity and local community composition for different buffers around 86 sampling points in Munich, Germany. Using linear models, we showed that a 100 m buffer best described bird diversity (highest R²) for both NDVI and vegetation volume compared to the other buffers. Contrary to expectations, NDVI was better than vegetation volume in predicting bird diversity (mean R² NDVI = 0.47, mean R² vegetation volume 0.37). We found a shift in community composition from species associated with human-modified landscapes to those associated with forests along an urban greenness gradient. In contrast to diversity, we found that vegetation volume was slightly better at predicting community composition. Using NDVI to predict bird diversity across Munich, we demonstrated its potential for predicting city-wide bird diversity. We discuss how such predictive maps can be used for urban planning and conservation. As urbanisation continues to impact global biodiversity, refining ecological models for urban planning will be crucial to developing more biodiverse urban environments.

Ongoing global warming causes dramatic changes globally, especially with respect to Polar Regions. In this context, digital elevation data is of high importance for most glaciological applications. In this paper, we investigate TanDEM-X penetration depth over snow and ice on the Greenland ice sheet. In particular, the relation of backscatter intensity and interferometric coherence to penetration depth of the X-band InSAR signal is explored in order to improve the reliability of TanDEM-X elevation data. The analyses showed a distinct relationship of backscatter intensity, coherence and penetration depth. In addition, the influence of the height of ambiguity of the interferometric TanDEM-X data is presented. On an experimental test site in Northern Greenland, we demonstrated the estimation of TanDEM-X penetration depth based on backscatter intensity and interferometric coherence utilizing a linear regression model.

Today's SAR sensors provide a variety of different image modes particularly with regard to multipolarised acquisitions. Until now, each polarisation mode requires a special decomposition which is a severe drawback when designing processing chains. Therefore, a new description for multipolarized SAR data based on the well-known Kennaugh matrix was developed that enables the uniform description and processing of SAR data independent of its polarisation by separating backscattering strength from polarimetric information. This mathematical approach subsequently is extended to the processing of multitemporal SAR data in order to stabilize the polarimetric information over longer periods of time and to enhance temporal changes in the polarimetric backscattering. Because of the high sensitivity of the Kennaugh elements a novel multilooking technique based on the Gaussian pyramid is used that locally adapts the look factor and thus selects the optimal balance between radiometric accuracy and geometric resolution. This methodology is applied to two dual-co-polarized TerraSAR-X acquisitions over the RAMSAR testsite "Upper Rhine" in order to generate value-added products that help to map land cover and land cover changes in consequence of water level changes. The first results are very promising although the interpretation of the observed polarimetric changes is not yet validated. The aim of this paper is to present a further application of the (Differential) Kennaugh matrix which will be the kernel of a polarimetry and change detection processor to be implemented in the coming years.