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Saman Nadizadeh Shorabeh
Department of GIS and Remote Sensing, Faculty of Geography, University of Tehran, Tehran 14178-53933, Iran

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Journal article
Published: 03 March 2021 in Remote Sensing
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Due to irregular and uncontrolled expansion of cities in developing countries, currently operational landfill sites cannot be used in the long-term, as people will be living in proximity to these sites and be exposed to unhygienic circumstances. Hence, this study aims at proposing an integrated approach for determining suitable locations for landfills while considering their physical expansion. The proposed approach utilizes the fuzzy analytical hierarchy process (FAHP) to weigh the sets of identified landfill location criteria. Furthermore, the weighted linear combination (WLC) approach was applied for the elicitation of the proper primary locations. Finally, the support vector machine (SVM) and cellular automation-based Markov chain method were used to predict urban growth. To demonstrate the applicability of the developed approach, it was applied to a case study, namely the city of Mashhad in Iran, where suitable sites for landfills were identified considering the urban growth in different geographical directions for this city by 2048. The proposed approach could be of use for policymakers, urban planners, and other decision-makers to minimize uncertainty arising from long-term resource allocation.

ACS Style

Salman Qureshi; Saman Shorabeh; Najmeh Samany; Foad Minaei; Mehdi Homaee; Fatemeh Nickravesh; Mohammad Firozjaei; Jamal Arsanjani. A New Integrated Approach for Municipal Landfill Siting Based on Urban Physical Growth Prediction: A Case Study Mashhad Metropolis in Iran. Remote Sensing 2021, 13, 949 .

AMA Style

Salman Qureshi, Saman Shorabeh, Najmeh Samany, Foad Minaei, Mehdi Homaee, Fatemeh Nickravesh, Mohammad Firozjaei, Jamal Arsanjani. A New Integrated Approach for Municipal Landfill Siting Based on Urban Physical Growth Prediction: A Case Study Mashhad Metropolis in Iran. Remote Sensing. 2021; 13 (5):949.

Chicago/Turabian Style

Salman Qureshi; Saman Shorabeh; Najmeh Samany; Foad Minaei; Mehdi Homaee; Fatemeh Nickravesh; Mohammad Firozjaei; Jamal Arsanjani. 2021. "A New Integrated Approach for Municipal Landfill Siting Based on Urban Physical Growth Prediction: A Case Study Mashhad Metropolis in Iran." Remote Sensing 13, no. 5: 949.

Journal article
Published: 18 February 2021 in Journal of Cleaner Production
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Many parts of the world may have suitable conditions and potential to establish two or more renewable energy farms. Given the pervasive use of renewable energy globally, assessing the potential of regions to establish a multi-renewable energy farm is of great importance. This study aimed to assess the potential for the establishment of renewable energy farms (solar, wind, biomass, and geothermal) in the eastern regions of Iran. For the first time, the potential for establishing multi-renewable energy farms in an area has been assessed. For this purpose, a series of environmental and economic criteria were addressed and investigated. Respectively, Analytical Network Process (ANP) and Fuzzy logic were employed for obtaining the required weights as well as accounting for the element of uncertainty among the different criteria. The final suitability maps for identification of the most optimal locations for the institution of renewable energy farms were obtained using Weighted Linear Combination (WLC) method. The study area was classified as highly suitable for the establishment of renewable energy farms, as maintained by the final results, wherein 5, 13, 23, and 19% of the entire study area were selected as eligible placements for the institution of biomass, geothermal, solar, and wind power plants, respectively. In consonance with the final map obtained using a combination of individual suitability maps, a total of 5465 km2 worth of area was categorized as highly suitable for the establishment of renewable energy farms. Results also were indicative of the prominence of the different weights assigned to each criterion on identifying the optimal choices of the region concerning the establishment of renewable energy farms. The results can be further used for and are highly advantageous to various managerial, planning, and decision-making procedures in connection with the development of prospective renewable energy sources.

ACS Style

Saman Nadizadeh Shorabeh; Meysam Argany; Javad Rabiei; Hamzeh Karimi Firozjaei; Omid Nematollahi. Potential assessment of multi-renewable energy farms establishment using spatial multi-criteria decision analysis: A case study and mapping in Iran. Journal of Cleaner Production 2021, 295, 126318 .

AMA Style

Saman Nadizadeh Shorabeh, Meysam Argany, Javad Rabiei, Hamzeh Karimi Firozjaei, Omid Nematollahi. Potential assessment of multi-renewable energy farms establishment using spatial multi-criteria decision analysis: A case study and mapping in Iran. Journal of Cleaner Production. 2021; 295 ():126318.

Chicago/Turabian Style

Saman Nadizadeh Shorabeh; Meysam Argany; Javad Rabiei; Hamzeh Karimi Firozjaei; Omid Nematollahi. 2021. "Potential assessment of multi-renewable energy farms establishment using spatial multi-criteria decision analysis: A case study and mapping in Iran." Journal of Cleaner Production 295, no. : 126318.

Journal article
Published: 25 January 2020 in Atmospheric Environment
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Dust storms are considered as one of the most important environmental challenges in the West Asia region. In addition to the harmful impacts of dust storms on human health, they also have particular effects on socioeconomic and agroecological domains of human communities. Identify the sources of dust storms is the first step to combat against these devastating phenomena. Accordingly, the present study was conducted to determine dust sources of the Tigris and Euphrates basin using satellite and climatic data. Monthly LST and NDVI of MODIS, monthly wind speed, soil moisture, and absolute air humidity data from GLDAS, monthly TRMM precipitation, and soil texture data of FAO were used. The Analytic Hierarchy Process (AHP) model was applied to determine the weights of the collected data (i.e. criteria or drivers for dust storms formation). Susceptible Areas to Dust Storm Formation (SADSF) were determined using the Weighted Linear Combination (WLC) model for months of June, July, and August from 2000 to 2017. After performing SADSF analysis, five main dust sources were identified in the whole basin. To evaluate the accuracy of the results, the number of real Observed Dust Storms (ODS) in each source was compared to the repetition of allocation in SADSF for each pixel over the 18-year period of this study from 2000 to 2017. Results indicated that the area of SADSF has significantly grown for all three months since 2008. The areas of SADSF in June and July were almost the same, while they were significantly bigger than August. Among identified dust sources, the highest SADSF repetition was in the northwest of Iraq followed by eastern Syria, southern Iraq, southeast border of Iraq, and east border of Iraq, respectively. The correlation coefficient between the SADSF repetition with the number of ODS events in those recognized dust sources was equal to 0.88, 0.76, and 0.74 for June, July, and August, respectively, that shows the accuracy of our results in comparison to actual data.

ACS Style

Ali Darvishi Boloorani; Yasin Kazemi; Amin Sadeghi; Saman Nadizadeh Shorabeh; Meysam Argany. Identification of dust sources using long term satellite and climatic data: A case study of Tigris and Euphrates basin. Atmospheric Environment 2020, 224, 117299 .

AMA Style

Ali Darvishi Boloorani, Yasin Kazemi, Amin Sadeghi, Saman Nadizadeh Shorabeh, Meysam Argany. Identification of dust sources using long term satellite and climatic data: A case study of Tigris and Euphrates basin. Atmospheric Environment. 2020; 224 ():117299.

Chicago/Turabian Style

Ali Darvishi Boloorani; Yasin Kazemi; Amin Sadeghi; Saman Nadizadeh Shorabeh; Meysam Argany. 2020. "Identification of dust sources using long term satellite and climatic data: A case study of Tigris and Euphrates basin." Atmospheric Environment 224, no. : 117299.