Application of fuzzy analytical hierarchy process for assessment of combating-desertification alternatives in central Iran

Sadeghravesh, Mohammad Hassan; Khosravi, Hassan; Ghasemian, Soudeh

doi:10.1007/s11069-014-1345-7

Cited by 21 publications

(11 citation statements)

References 10 publications

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“…Due to the use of complex methods in each model, the results were largely the same. Sadeghiravesh et al prioritize the strategies in the Khezrabad region by using the following models: AHP (Sadeghiravesh et al, 2010), ELECTRE (Sadeghiravesh et al, 2014), weighted sum model (WSM) , BORDA (Sadeghiravesh, 2014), PERMUTATION (Sadeghiravesh, 2013), and PROMETHEE (Sadeghiravesh et al, 2016). The results of these studies are the same and largely similar to the results of previous research.…”

Section: Introductionsupporting

confidence: 55%

Assessment of combating desertification strategies using the linear assignment method

Sadeghravesh¹,

Khosravi²,

Ghasemian³

2016

Preprint

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Abstract. Select appropriate strategies according to all effective criteria in combating desertification process can be so useful in controlling and rehabilitation of degraded lands, and avoid degradation in vulnerable fields. This study provides systematic and optimal strategies of combating desertification by group decision-making model. To this end, in the framework of Multi Attribute Decision Making (MADM) and by using Delphi model (Delphi), the preferences of indexes were obtained. Then priorities of strategies were evaluated by using linear assignment (LA) method. According to the results, the strategies to prevent improper change of land use (A18), development and reclamation of plant cover (A23) and adjustment for harvesting from groundwater sources (A31), respectively were identified as the most important strategies for combating desertification in this study area. Therefore, it was suggested to consider ranking results in projects which controls and reduces the effects of desertification and rehabilitates degraded lands.

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Section: Introductionsupporting

confidence: 55%

Assessment of combating desertification strategies using the linear assignment method

Sadeghravesh¹,

Khosravi²,

Ghasemian³

2016

Preprint

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“…Sadeghiravesh also used AHP (Sadeghiravesh et al, 2010) technique for order preference by similarity to ideal solution (TOPSIS) (Sadeghiravesh et al, 2012) ، Electera (Sadeghiravesh et al, 2014) and fuzzy analytical hierarchy process (Sadeghi ravesh et al, 2015) and prioritized de-desertification alternatives in Khezer Abad region. The results of these studies were identical and also similar to the results of the present study.…”

Section: Researches Grau Used Elimination Et Choicementioning

confidence: 99%

Evaluation of Combating Desertification Alternatives Using Promethee Model

Sadeghravesh¹,

Khosravi²,

Abolhasani³

et al. 2016

JGG

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According to the extent of damage, various effects and complexity of desertification process, selecting appropriate alternatives considering all effective desertification criterions is one of the main concerns of Iran in the field of natural resources. This can be effective in controlling, reclamation of disturbed lands and avoiding destruction areas at desertification risk. This paper tries to provide a systematic and optimal alternatives in a group decision-making model. For this aim, PROMETHEE II method was used for ranking desertification alternatives. At the first in the framework of Multiple Attribute Decision-making (MADM), normalized decision matrix was provided by Delphi model. Then, to ease and accuracy in estimating the criteria preference and alternatives priority, the normalized decision matrix data were entered in Visual PROMETHEE software. Based on the results, the alternatives of prevention of unsuitable land use changes (A18), vegetation cover development and reclamation (A23) and modification of ground water harvesting (A31) with pure out ranking progress of =0.3660, 0.1909 and -0.0887 were selected as the main combating desertification altarnative in the study area, respectively. Therefore, it is suggested that the obtained results and ranking should be considered in projects of controlling and reducing the effects of desertification and rehabilitatyion of degraded lands plans.

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“…The analytic hierarchy process (AHP) has been widely used in the study of aeolian desertification [37,38] and can reveal the relative importance of different desertification indicators based on the study area. The weight of each variable in the AHP is determined from the matrix of pairwise comparisons, where the importance of indices is ranked from 1 to 7, otherwise they are assigned 1/2 to 1/7 (Table 2).…”

Section: Dynamic Change Evaluation Of Adl 271 Construction Of Desertification Indexmentioning

confidence: 99%

Monitoring the Spatiotemporal Dynamics of Aeolian Desertification Using Google Earth Engine

Chen

Xiao

et al. 2021

Remote Sensing

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Northern China has been long threatened by aeolian desertification. In recent years, all levels of the Chinese government have performed a series of ecological protection and sand control projects. To grasp the implementation effects of these projects and adjust policies in time, it is necessary to understand the process of aeolian desertification quickly and accurately. Remote sensing technologies play an irreplaceable role in aeolian desertification monitoring. In this study, the Zhenglan Banner, which is in the hinterland of the Hunshandake Sandy Land, was considered as the research area. Based on unmanned aerial vehicle (UAV) images, ground survey data, and Landsat images called in Google Earth Engine (GEE), the aeolian desertified land (ADL) in 2000, 2004, 2010, 2015, and 2019 was extracted using spectral mixture analysis. A desertification index (DI) was constructed to evaluate the spatial and temporal dynamics of the ADL in the Zhenglan Banner. Finally, a residual analysis explored the driving forces of aeolian desertification. The results showed that (1) the ADL area in the Zhenglan Banner has been trending downwards over the past 20 years but rebounded from 2004 to 2010; (2) over the past 20 years, the area of slightly, moderately, and severely desertified land has decreased at annual rates of 0.4%, 2.7%, and 3.4%, respectively; (3) human activities had significantly positive and negative impacts on the aeolian desertification trend for 20.0% and 21.0% of the study area, respectively, but not for the rest. This paper explored new techniques for rapid aeolian desertification monitoring and is of great significance for controlling and managing aeolian desertification in this region.

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Application of fuzzy analytical hierarchy process for assessment of combating-desertification alternatives in central Iran

Cited by 21 publications

References 10 publications

Assessment of combating desertification strategies using the linear assignment method

Assessment of combating desertification strategies using the linear assignment method

Evaluation of Combating Desertification Alternatives Using Promethee Model

Monitoring the Spatiotemporal Dynamics of Aeolian Desertification Using Google Earth Engine

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