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Sampling and statistical analyses of BTS measurements

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  • Alexander Brenning
  • Stephan Gruber
  • Martin Hoelzle

Abstract

Basal temperature of snow (BTS) data show characteristic spatial autocorrelations at distances typically less than 200 m, leading to non‐independent regression residuals. Systematic temporal variations may also introduce model bias resulting in a shift in the predicted lower limit of permafrost. Both phenomena are analysed. The selection of an appropriate sampling design for a BTS measurement program appears critical in order to minimize problems typical of observational data in complex terrain. Copyright © 2005 John Wiley & Sons, Ltd.

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  • Alexander Brenning & Stephan Gruber & Martin Hoelzle, 2005. "Sampling and statistical analyses of BTS measurements," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 16(4), pages 383-393, October.
    • Handle: RePEc:wly:perpro:v:16:y:2005:i:4:p:383-393
    DOI: 10.1002/ppp.541
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    1. Nussaïbah B. Raja & Ihsan Çiçek & Necla Türkoğlu & Olgu Aydin & Akiyuki Kawasaki, 2017. "Landslide susceptibility mapping of the Sera River Basin using logistic regression model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(3), pages 1323-1346, February.

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