@misc{SmithBookhagenCannon2015,
  author    = {Smith, Taylor and Bookhagen, Bodo and Cannon, Forest},
  title     = {Improving semi-automated glacier mapping with a multi-method approach},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {510},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-40847},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-408471},
  pages     = {13},
  year      = {2015},
  abstract  = {Studies of glaciers generally require precise glacier outlines. Where these are not available, extensive manual digitization in a geographic information system (GIS) must be performed, as current algorithms struggle to delineate glacier areas with debris cover or other irregular spectral profiles. Although several approaches have improved upon spectral band ratio delineation of glacier areas, none have entered wide use due to complexity or computational intensity. In this study, we present and apply a glacier mapping algorithm in Central Asia which delineates both clean glacier ice and debris-covered glacier tongues. The algorithm is built around the unique velocity and topographic characteristics of glaciers and further leverages spectral and spatial relationship data. We found that the algorithm misclassifies between 2 and 10\% of glacier areas, as compared to a similar to 750 glacier control data set, and can reliably classify a given Landsat scene in 3-5 min. The algorithm does not completely solve the difficulties inherent in classifying glacier areas from remotely sensed imagery but does represent a significant improvement over purely spectral-based classification schemes, such as the band ratio of Landsat 7 bands three and five or the normalized difference snow index. The main caveats of the algorithm are (1) classification errors at an individual glacier level, (2) reliance on manual intervention to separate connected glacier areas, and (3) dependence on fidelity of the input Landsat data.},
  language  = {en}
}
@misc{TostEhmelHeidmannetal.2018,
  author    = {Tost, Jordi and Ehmel, Fabian and Heidmann, Frank and Olen, Stephanie M. and Bookhagen, Bodo},
  title     = {Hazards and accessibility},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {710},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42785},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427853},
  pages     = {8},
  year      = {2018},
  abstract  = {The assessment of natural hazards and risk has traditionally been built upon the estimation of threat maps, which are used to depict potential danger posed by a particular hazard throughout a given area. But when a hazard event strikes, infrastructure is a significant factor that can determine if the situation becomes a disaster. The vulnerability of the population in a region does not only depend on the area's local threat, but also on the geographical accessibility of the area. This makes threat maps by themselves insufficient for supporting real-time decision-making, especially for those tasks that involve the use of the road network, such as management of relief operations, aid distribution, or planning of evacuation routes, among others. To overcome this problem, this paper proposes a multidisciplinary approach divided in two parts. First, data fusion of satellite-based threat data and open infrastructure data from OpenStreetMap, introducing a threat-based routing service. Second, the visualization of this data through cartographic generalization and schematization. This emphasizes critical areas along roads in a simple way and allows users to visually evaluate the impact natural hazards may have on infrastructure. We develop and illustrate this methodology with a case study of landslide threat for an area in Colombia.},
  language  = {en}
}