@book{JordanPietruskaSiemeretal.2017,
  author    = {Jordan, Peter and Pietruska, Franz and Siemer, Julia and Rolfes, Manfred and Borg, Erik and Fichtelmann, Bernd and Jaumann, Ralf and Naß, Andrea and Bamberg, Marlene},
  title     = {Geoinformation \& Visualisierung},
  number    = {12},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  organization    = {Fachgruppe Geoinformatik des Instituts f{\"u}r Geographie der Universit{\"a}t Potsdam},
  isbn      = {978-3-86956-389-3},
  issn      = {2194-1599},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-100787},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {122},
  year      = {2017},
  abstract  = {Hartmut Asche pr{\"a}gte {\"u}ber ein Vierteljahrhundert maßgeblich die Forschungsfelder der Geoinformation, Visualisierung und Kartographie. Die vorliegende Festschrift stellt eine w{\"u}rdige Gabe von Mitarbeiterinnen und Mitarbeitern des Institutes f{\"u}r Geographie der Universit{\"a}t Potsdam anl{\"a}sslich seiner Emeritierung im M{\"a}rz 2017 dar. International renommierte, Herrn Asches Karriere begleitende Autorinnen und Autoren, konnten f{\"u}r Fachbeitr{\"a}ge aus den Bereichen Geographie, Geoinformatik, Kartographie und Fernerkundung gewonnen werden. Es werden in fachlich hervorragender Weise Schwerpunkte umrissen, mit welchen Herr Asche sich in seiner von zahlreichen H{\"o}hepunkten gepr{\"a}gten wissenschaftlichen Karriere besch{\"a}ftigte.},
  language  = {de}
}
@book{Trauth2022,
  author    = {Trauth, Martin H.},
  title     = {Python Recipes for Earth Sciences},
  series = {Springer Textbooks in Earth Sciences, Geography and Environment},
  journal   = {Springer Textbooks in Earth Sciences, Geography and Environment},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-07719-7},
  issn      = {2510-1307},
  doi       = {10.1007/978-3-031-07719-7},
  pages     = {453},
  year      = {2022},
  abstract  = {Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book.},
  language  = {en}
}