Application of fuzzy-AHP method for desertification assessment in Sabzevar area of Iran

Mostafa Dastorani ()
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Mostafa Dastorani: Hakim Sabzevari University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 112, issue 1, No 8, 187-205

Abstract: Abstract Desertification is a serious problem in most arid and semi-arid areas of the world, and especially in Iran. Combating desertification planning and any preparatory measures require detailed mapping of the current status of desertification as well as its evolvement during the time. This study, basically relying on remote sensing datasets, strives to map desertification in the Sabzevar area of Iran and identify its changes between the years 2001 and 2020. The indicators used in this study included Enhanced Vegetation Index, Vegetation Condition Index, Salinity Index, Synthetized Drought Index, Temperature Condition Index, Precipitation, Normalized Vegetation Index, and Land Surface Temperature. Analytical Hierarchical Process was used to determine the weight of the factors and the fuzzy overlay approach was used for synthesizing the thematic layer maps. According to the expert judgments, precipitation and salinity are the most important desertification factors in the area (~ 50% of the total weight). In terms of land-use changes over the past 20 years, urban, desert, croplands and bare lands grew in size at the expense of rangelands and open canopy forests which shrank greater than 3.5% (435 km2). Based on our findings, the total area of desertification classes has not changed considerably during the period but there has been a growth in very high and high desertification intensity classes by 12%. According to our findings, very high and high classes have increased between the years 2001 and 2020 mostly in the central and southern parts of the study area. The results obtained in this research are very important to the land managers of the Khorasan Razavi Province, for formulating sustainable development programs and avoiding the unwanted consequences of desertification.

Keywords: GIS; Remote sensing; MODIS; Landsat; Vegetation (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-021-05177-8

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