@misc{RungeGrosse2019,
  author    = {Runge, Alexandra and Grosse, Guido},
  title     = {Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {767},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43866},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-438660},
  pages     = {29},
  year      = {2019},
  abstract  = {The Arctic-Boreal regions experience strong changes of air temperature and precipitation regimes, which affect the thermal state of the permafrost. This results in widespread permafrost-thaw disturbances, some unfolding slowly and over long periods, others occurring rapidly and abruptly. Despite optical remote sensing offering a variety of techniques to assess and monitor landscape changes, a persistent cloud cover decreases the amount of usable images considerably. However, combining data from multiple platforms promises to increase the number of images drastically. We therefore assess the comparability of Landsat-8 and Sentinel-2 imagery and the possibility to use both Landsat and Sentinel-2 images together in time series analyses, achieving a temporally-dense data coverage in Arctic-Boreal regions. We determined overlapping same-day acquisitions of Landsat-8 and Sentinel-2 images for three representative study sites in Eastern Siberia. We then compared the Landsat-8 and Sentinel-2 pixel-pairs, downscaled to 60 m, of corresponding bands and derived the ordinary least squares regression for every band combination. The acquired coefficients were used for spectral bandpass adjustment between the two sensors. The spectral band comparisons showed an overall good fit between Landsat-8 and Sentinel-2 images already. The ordinary least squares regression analyses underline the generally good spectral fit with intercept values between 0.0031 and 0.056 and slope values between 0.531 and 0.877. A spectral comparison after spectral bandpass adjustment of Sentinel-2 values to Landsat-8 shows a nearly perfect alignment between the same-day images. The spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to Landsat-8 very well in Eastern Siberian Arctic-Boreal landscapes. After spectral adjustment, Landsat and Sentinel-2 data can be used to create temporally-dense time series and be applied to assess permafrost landscape changes in Eastern Siberia. Remaining differences between the sensors can be attributed to several factors including heterogeneous terrain, poor cloud and cloud shadow masking, and mixed pixels.},
  language  = {en}
}
@article{RungeGrosse2019,
  author    = {Runge, Alexandra and Grosse, Guido},
  title     = {Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions},
  series = {Remote Sensing},
  volume    = {11},
  journal   = {Remote Sensing},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs11141730},
  pages     = {29},
  year      = {2019},
  abstract  = {The Arctic-Boreal regions experience strong changes of air temperature and precipitation regimes, which affect the thermal state of the permafrost. This results in widespread permafrost-thaw disturbances, some unfolding slowly and over long periods, others occurring rapidly and abruptly. Despite optical remote sensing offering a variety of techniques to assess and monitor landscape changes, a persistent cloud cover decreases the amount of usable images considerably. However, combining data from multiple platforms promises to increase the number of images drastically. We therefore assess the comparability of Landsat-8 and Sentinel-2 imagery and the possibility to use both Landsat and Sentinel-2 images together in time series analyses, achieving a temporally-dense data coverage in Arctic-Boreal regions. We determined overlapping same-day acquisitions of Landsat-8 and Sentinel-2 images for three representative study sites in Eastern Siberia. We then compared the Landsat-8 and Sentinel-2 pixel-pairs, downscaled to 60 m, of corresponding bands and derived the ordinary least squares regression for every band combination. The acquired coefficients were used for spectral bandpass adjustment between the two sensors. The spectral band comparisons showed an overall good fit between Landsat-8 and Sentinel-2 images already. The ordinary least squares regression analyses underline the generally good spectral fit with intercept values between 0.0031 and 0.056 and slope values between 0.531 and 0.877. A spectral comparison after spectral bandpass adjustment of Sentinel-2 values to Landsat-8 shows a nearly perfect alignment between the same-day images. The spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to Landsat-8 very well in Eastern Siberian Arctic-Boreal landscapes. After spectral adjustment, Landsat and Sentinel-2 data can be used to create temporally-dense time series and be applied to assess permafrost landscape changes in Eastern Siberia. Remaining differences between the sensors can be attributed to several factors including heterogeneous terrain, poor cloud and cloud shadow masking, and mixed pixels.},
  language  = {en}
}
@article{LebedevaGrothHermanussenetal.2019,
  author    = {Lebedeva, Lidia and Groth, Detlef and Hermanussen, Michael and Scheffler, Christiane and Godina, Elena},
  title     = {The network effects on conscripts' height in the central provinces of Russian empire in the middle of XIX century},
  series = {Journal of biological and clinical anthropology : Anthropologischer Anzeiger ; Mitteilungsorgan der Gesellschaft f{\"u}r Anthropologie},
  volume    = {76},
  journal   = {Journal of biological and clinical anthropology : Anthropologischer Anzeiger ; Mitteilungsorgan der Gesellschaft f{\"u}r Anthropologie},
  number    = {5},
  publisher = {Schweizerbart},
  address   = {Stuttgart},
  issn      = {0003-5548},
  doi       = {10.1127/anthranz/2019/0984},
  pages     = {371 -- 377},
  year      = {2019},
  abstract  = {Background: We investigated average body height in the central provinces of the Russian empire in the middle of XIX century in view of the concept of "community effects on height". We analyzed body height correlations between neighboring districts at this time. We added information about secular changes in body height during the 19th century of this territory. Material and methods: The study used height data of conscripts, which were born in the years 1853-1863, and age 21 at the time of measurement. The territory of seven provinces was considered as a network with 105 nodes, each node representing one district with information on average male body height. In order to define neighboring districts three different approaches were used: based on the "common borders" method, based on Euclidean distances (from 60 to 120 km), based on real road connections. Results: Small but significant correlation coefficients were observed between 1st order districts in the network based on Euclidean distance of 100 km (r = 0.256, p-value = 0.006) and based on "the common borders" approach (r = 0.25, p-value = 0.02). Wherein no significant correlations were observed in the network based on road connections and between second order neighbors regardless of the method. Conclusion: Height correlation coefficients between 1st order neighboring districts observed in the Russian districts were very similar to values observed in the Polish study (r = 0.24). The considered Russian territory and the territory of Poland have a lot in common. They consist of both plains without mountains. In contradistinction to Poland the transport infrastructure in Russia was weakly developed in the middle of XIX century. In addition, the mobility of people was limited by serfdom. In this context the absent of significant correlation of second order neighbors can be explained by low population density and lack of migration and communication between the districts.},
  language  = {en}
}