Journal
AEOLIAN RESEARCH
Volume 35, Issue -, Pages 19-28Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.aeolia.2018.09.001
Keywords
Desertification; Aeolian sediments and GSS; MLP neural networks; Regression logistic
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Wind erosion in arid and semi-arid regions is a serious concern because it can cause land degradation and consequently affect the land use pattern. The aim of this study was to assess the variations of aeolian sediments and gypsum sediment surfaces (ASGSS) during 1992-2017 in Sejzy Plain and to analyze the impact of plans against desertification, as well as human and environmental activities on the variations of these surfaces. In the current study, Landsat satellite images were classified using the multiple layer perceptron (MLP) neural network. Finally, the logistic regression model has been used to study the impact and role of plans against desertification, human and environmental activities on the ASGSS variations in the studied area. The ASGSS decreased from 37.9% in 1992 to 24.3% in 2017 in the study area. Investigation of the effect of aeolian desertification in the region showed that planting stabilizing species and preventive measures taken in controlling gypsum-mining activities and grill areas, especially in the northern parts of the region has prevented further variation in the gypsum sediment cover. The results indicate that the planting of stabilizing species in lands outside the ASGSS has a greater effect on reducing ASGSS, in comparison with the planting of stabilizing species in the interior lands of the and ASGSS. Also, the results show that policies related to plans against desertification have been useful in reducing lands with ASGSS.
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