An investigation on the role of effective factors in the formation of sinkholes on the karstic formation with using multivariate linear regression model, GIS, and SPSS

Authors

1 University of Mohaghegh Ardabili

2 Karazmi university of Tehran

Abstract

karstic zones in dealing with diversity and complexity factor and their mechanisms in related to each other، with respect to their roles in the evolution and karstification sensitivity are avery different reaction. Therefore today’s led to Special pay attention in the initial studies and preparing karstification maps on the environmental planning to theresearcher. The study zone with karst formations is the part of the folded limestone formations and tectonic crushed zones and that is very prone to formation of various karstic landforms. The main purpose of study factors in the development of karst sinkhole and Zoning emphasizing talent development and sensitive karst area Inscription based on the effects of these factors. Therefore, all data layers were processed using Arc GIS software and the relationships between variables and their effect on the dependent variable using multivariate linear regression analysis was conducted in SPSS. The results of the regression equation and multivariate linear regression and influence of regression coefficients on the data matrix variables due to thePotential occurrence of sinkholes indicated the spectral coefficients are obtained numerically positive and negative. Positive numbers indicate the suitable conditions for karst development and negative indicated unsuitable conditions for the development of karst. The numerical range of the spectrum, the three-class quality, including low talent, talent, and more talent into the medium. Interpretation of the coefficients and the results of this study showed that lithology is the most important roles in karst development and then the layers faults, rainfall, elevation, temperature, dip and dip direction, the next levels are important.

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History

  • Receive Date: 26 November 2016
  • Revise Date:
  • Accept Date: 26 November 2016

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