@misc{ShanGuanHubaceketal.2018,
  author    = {Shan, Yuli and Guan, Dabo and Hubacek, Klaus and Zheng, Bo and Davis, Steven J. and Jia, Lichao and Liu, Jianghua and Liu, Zhu and Fromer, Neil and Mi, Zhifu and Meng, Jing and Deng, Xiangzheng and Li, Yuan and Lin, Jintai and Schroeder, Heike and Weisz, Helga and Schellnhuber, Hans Joachim},
  title     = {City-level climate change mitigation in China},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1096},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-47154},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-471541},
  pages     = {18},
  year      = {2018},
  abstract  = {As national efforts to reduce CO2 emissions intensify, policy-makers need increasingly specific, subnational information about the sources of CO2 and the potential reductions and economic implications of different possible policies. This is particularly true in China, a large and economically diverse country that has rapidly industrialized and urbanized and that has pledged under the Paris Agreement that its emissions will peak by 2030. We present new, city level estimates of CO2 emissions for 182 Chinese cities, decomposed into 17 different fossil fuels, 46 socioeconomic sectors, and 7 industrial processes. We find that more affluent cities have systematically lower emissions per unit of gross domestic product (GDP), supported by imports from less affluent, industrial cities located nearby. In turn, clusters of industrial cities are supported by nearby centers of coal or oil extraction. Whereas policies directly targeting manufacturing and electric power infrastructure would drastically undermine the GDP of industrial cities, consumption based policies might allow emission reductions to be subsidized by those with greater ability to pay. In particular, sector based analysis of each city suggests that technological improvements could be a practical and effective means of reducing emissions while maintaining growth and the current economic structure and energy system. We explore city-level emission reductions under three scenarios of technological progress to show that substantial reductions (up to 31\%) are possible by updating a disproportionately small fraction of existing infrastructure.},
  language  = {en}
}
@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}
}