Volume 75 (2022)
Volume 74 (2021)
Volume 73 (2020)
Volume 72 (2019)
Volume 71 (2018)
Volume 70 (2017)
Volume 69 (2016)
Volume 68 (2015)
Volume 67 (2014)
Volume 66 (2013)
Volume 65 (2012)
Volume 63 (2010)
Volume 62 (2009)
Comparison of machine learning models to prioritize susceptible areas to dust production

Serveh Darvand; Hassan Khosravi; Hamidreza Keshtkar; Gholamreza Zehtabian; Omid Rahmati

Volume 74, Issue 1 , June 2021, , Pages 53-68


  The purpose of this study was to compare machine learning models including Support Vector Machine, Classification and Regression Tree, Random Forest, and Multivariate Discriminate Analysis to prioritize susceptible areas to dust production. To determine the dust days, hourly meteorological data of Alborz ...  Read More

Evolution the efficiency of Random Forest in Gully erosion susceptibility mapping

Somayeh Movahedi; aboalhasan fathabadi; null null; Ali Heshmatpour

Volume 72, Issue 1 , June 2019, , Pages 241-261


  In this study using Frequency Ratio (FR), Statistical Index (SI), Weights Of Evidence(WOF), Logistic Regression (LR), Random Forest (RF) models the probability of gully formation was calculated in Aytamar watershed and susceptibility maps was prepared. First the thematic maps of 13 gully conditioning ...  Read More

Analysis of Geo-environmental parameters and gully erosion susceptibility mapping in toroud watershed using data-driven Evidential Belief Function method

ALIREZA Arabameri; khalil rezaei; mojtaba yamani

Volume 71, Issue 1 , June 2018, , Pages 97-114


  Gully erosion is one of the erosive processes that mostly change the shape of the earth surface and has severe environmental and economic damages. The aim of this research is modeling between geo-environmental parameters effective in gully erosion and gully occurrence in the study area and gully erosion ...  Read More

Modelling and Assessment of Landslide Susceptibility Zonation (Case Study: Semirom Basin)

ALIREZA Arabameri; kourosh shirani; khalil rezai; mojtaba yamani

Volume 70, Issue 4 , January 2018, , Pages 921-939


  landslides situation recognized using interpreting the aerial photos and extensive field measurements. Among total number of 200 identified landslides, %70 (140 landslides) of them have been utilized for model executing and %30 (60 landslides) of them for verification randomly. This research criteria ...  Read More