@article{MayrKleinRutzingeretal.2021,
  author    = {Mayr, Stefan and Klein, Igor and Rutzinger, Martin and Kuenzer, Claudia},
  title     = {Systematic water fraction estimation for a global and daily surface water time-series},
  series = {Remote Sensing},
  volume    = {13},
  journal   = {Remote Sensing},
  number    = {14},
  issn      = {2072-4292},
  doi       = {10.3390/rs13142675},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-242586},
  year      = {2021},
  abstract  = {Fresh water is a vital natural resource. Earth observation time-series are well suited to monitor corresponding surface dynamics. The DLR-DFD Global WaterPack (GWP) provides daily information on globally distributed inland surface water based on MODIS (Moderate Resolution Imaging Spectroradiometer) images at 250 m spatial resolution. Operating on this spatiotemporal level comes with the drawback of moderate spatial resolution; only coarse pixel-based surface water quantification is possible. To enhance the quantitative capabilities of this dataset, we systematically access subpixel information on fractional water coverage. For this, a linear mixture model is employed, using classification probability and pure pixel reference information. Classification probability is derived from relative datapoint (pixel) locations in feature space. Pure water and non-water reference pixels are located by combining spatial and temporal information inherent to the time-series. Subsequently, the model is evaluated for different input sets to determine the optimal configuration for global processing and pixel coverage types. The performance of resulting water fraction estimates is evaluated on the pixel level in 32 regions of interest across the globe, by comparison to higher resolution reference data (Sentinel-2, Landsat 8). Results show that water fraction information is able to improve the product's performance regarding mixed water/non-water pixels by an average of 11.6\% (RMSE). With a Nash-Sutcliffe efficiency of 0.61, the model shows good overall performance. The approach enables the systematic provision of water fraction estimates on a global and daily scale, using only the reflectance and temporal information contained in the input time-series.},
  language  = {en}
}
@article{WuerthnerNoll2021,
  author    = {W{\"u}rthner, Frank and Noll, Niklas},
  title     = {A Calix[4]arene-Based Cyclic Dinuclear Ruthenium Complex for Light-Driven Catalytic Water Oxidation},
  series = {Chemistry - A European Journal},
  volume    = {27},
  journal   = {Chemistry - A European Journal},
  number    = {1},
  doi       = {10.1002/chem.202004486},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-230030},
  pages     = {444-450},
  year      = {2021},
  abstract  = {A cyclic dinuclear ruthenium(bda) (bda: 2,2'-bipyridine-6,6'-dicarboxylate) complex equipped with oligo(ethylene glycol)-functionalized axial calix[4]arene ligands has been synthesized for homogenous catalytic water oxidation. This novel Ru(bda) macrocycle showed significantly increased catalytic activity in chemical and photocatalytic water oxidation compared to the archetype mononuclear reference [Ru(bda)(pic)\(_2\)]. Kinetic investigations, including kinetic isotope effect studies, disclosed a unimolecular water nucleophilic attack mechanism of this novel dinuclear water oxidation catalyst (WOC) under the involvement of the second coordination sphere. Photocatalytic water oxidation with this cyclic dinuclear Ru complex using [Ru(bpy)\(_3\)]Cl\(_2\) as a standard photosensitizer revealed a turnover frequency of 15.5 s\(^{-1}\) and a turnover number of 460. This so far highest photocatalytic performance reported for a Ru(bda) complex underlines the potential of this water-soluble WOC for artificial photosynthesis.},
  language  = {en}
}