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  • This paper is attempting to shed light on the basic approaches and methods (observational, empirical and mechanistic approach) of assessing wind damage hazard using widely available GIS software. The paper describes data acquisition and building dataset, determination of dependant and independent (explanatory) variables, creation of sample units and application of basic statistical methods to assess windthrow risk. The statistical method of logistic regression is used to predict the probability of this hazard. Logistic regression is one of the most commonly used tools for applied statistics and data mining and has proven to be a useful tool to estimate the probability of windthrow. Variables and coefficients of logistic model are calculated using statistical software SAS 9.1. Stepwise method is applied to aid in the formulation of model and finding the most important explanatory variables. Logistic regression formulas are incorporated into GIS and a windthrow hazard map is then derived from the model
  • This paper is attempting to shed light on the basic approaches and methods (observational, empirical and mechanistic approach) of assessing wind damage hazard using widely available GIS software. The paper describes data acquisition and building dataset, determination of dependant and independent (explanatory) variables, creation of sample units and application of basic statistical methods to assess windthrow risk. The statistical method of logistic regression is used to predict the probability of this hazard. Logistic regression is one of the most commonly used tools for applied statistics and data mining and has proven to be a useful tool to estimate the probability of windthrow. Variables and coefficients of logistic model are calculated using statistical software SAS 9.1. Stepwise method is applied to aid in the formulation of model and finding the most important explanatory variables. Logistic regression formulas are incorporated into GIS and a windthrow hazard map is then derived from the model (en)
Title
  • Empirical modelling of windthrow risk using GIS and logistic regression.
  • Empirical modelling of windthrow risk using GIS and logistic regression. (en)
skos:prefLabel
  • Empirical modelling of windthrow risk using GIS and logistic regression.
  • Empirical modelling of windthrow risk using GIS and logistic regression. (en)
skos:notation
  • RIV/62156489:43410/10:00170220!RIV11-MSM-43410___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6215648902)
http://linked.open...iv/cisloPeriodika
  • 1
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 257041
http://linked.open...ai/riv/idVysledku
  • RIV/62156489:43410/10:00170220
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • GIS; logistic regression; windthrow (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • RO - Rumunsko
http://linked.open...ontrolniKodProRIV
  • [F9894BA3C0C1]
http://linked.open...i/riv/nazevZdroje
  • Geographia Technica
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 9
http://linked.open...iv/tvurceVysledku
  • Krejčí, Lukáš
http://linked.open...n/vavai/riv/zamer
issn
  • 1842-5135
number of pages
http://localhost/t...ganizacniJednotka
  • 43410
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