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Najmeh Neysani Samany
Faculty of Geography, Department of Remote Sensing and GIS, University of Tehran, Iran

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Journal article
Published: 09 July 2021 in Applied Soft Computing
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Emergency evacuation throughout and after the flood is a crucial task to mitigating more instantaneous impacts, whilst refining social resilience for longer-term recovery. To enhance the evacuation process, the determination and prediction of safe areas before a flood is necessary. Indeed, the safe area or shelter in place could play two roles during the flood; as temporary shelters and as meeting points (station) for gathering before evacuation. This paper aims to determine the safe area according to the spatial and environmental characteristics of the urban extent (accessibility, topography, congestion, and land use). The main contribution is finding safe areas using modified particle swarm optimization (MPSO) with local search (LMPSO). The proposed method recognizes the optimal location of temporary shelters as evacuation stations. It has been implemented in Districts 3, 6, and 7 of Tehran, the capital of Iran. The comparison between the achieved results of MPSO and LMPSO demonstrated that the LMPSO is more efficient than the modified version. Since LMPSO is less sensitive to local minima and converged to minimum cost faster than MPSO, and the distribution of optimum locations of safe areas has been balanced, so all the population could benefit from these stations. The comparison among the results of MPSO, LMPSO, GA, ACO and genetic simulated annealing algorithms justified the efficiency of LMPSO too.

ACS Style

Najmeh Neysani Samany; Mahdi Sheybani; Sisi Zlatanova. Detection of safe areas in flood as emergency evacuation stations using modified particle swarm optimization with local search. Applied Soft Computing 2021, 111, 107681 .

AMA Style

Najmeh Neysani Samany, Mahdi Sheybani, Sisi Zlatanova. Detection of safe areas in flood as emergency evacuation stations using modified particle swarm optimization with local search. Applied Soft Computing. 2021; 111 ():107681.

Chicago/Turabian Style

Najmeh Neysani Samany; Mahdi Sheybani; Sisi Zlatanova. 2021. "Detection of safe areas in flood as emergency evacuation stations using modified particle swarm optimization with local search." Applied Soft Computing 111, no. : 107681.

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.

Review article
Published: 01 March 2021 in Aeolian Research
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The Tigris and Euphrates basin (TEB) has long been one of the active dust sources in the Middle East. In the last four decades, inefficient water resources management has intensified dust activities in the TEB. Dried water bodies have a high potential for dust emission. Therefore, several studies have been conducted in TEB to identifying dust sources. Nevertheless, the role of water body changes in dust emission is not yet clear. The present study aimed to evaluate the effect of natural and anthropogenic drivers on changes in water bodies and dust emissions. The long-term spatial-temporal monitoring of water bodies changes was performed using 36-year Landsat 5, 7, and 8 multi-spectral images. Using visual interpretation of MODIS-RGB143 images, 904 dust storm events were identified, about 61% of them originated from dried beds of lakes, marshlands, and river margins. The lowest area of water bodies was observed in the period from 2000 to 2004 and 2008 to 2012. The area of water bodies in the two mentioned periods has decreased by 31% and 33%, respectively. Severe droughts have occurred in the region during these two periods. Overall, this has led to an increase of almost 23% in dust activities. However, the relationship between change in the area of water bodies and dust emission in the TEB is not necessarily linear and straightforward. In general, it can be concluded that the dried beds of water bodies is the largest source of dust emission in the TEB.

ACS Style

Ali Darvishi Boloorani; Ramin Papi; Masoud Soleimani; Leyla Karami; Fatemeh Amiri; Najmeh Neysani Samany. Water bodies changes in Tigris and Euphrates basin has impacted dust storms phenomena. Aeolian Research 2021, 50, 100698 .

AMA Style

Ali Darvishi Boloorani, Ramin Papi, Masoud Soleimani, Leyla Karami, Fatemeh Amiri, Najmeh Neysani Samany. Water bodies changes in Tigris and Euphrates basin has impacted dust storms phenomena. Aeolian Research. 2021; 50 ():100698.

Chicago/Turabian Style

Ali Darvishi Boloorani; Ramin Papi; Masoud Soleimani; Leyla Karami; Fatemeh Amiri; Najmeh Neysani Samany. 2021. "Water bodies changes in Tigris and Euphrates basin has impacted dust storms phenomena." Aeolian Research 50, no. : 100698.

Journal article
Published: 31 December 2020 in ISPRS International Journal of Geo-Information
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The size, volume, variety, and velocity of geospatial data collected by geo-sensors, people, and organizations are increasing rapidly. Spatial Data Infrastructures (SDIs) are ongoing to facilitate the sharing of stored data in a distributed and homogeneous environment. Extracting high-level information and knowledge from such datasets to support decision making undoubtedly requires a relatively sophisticated methodology to achieve the desired results. A variety of spatial data mining techniques have been developed to extract knowledge from spatial data, which work well on centralized systems. However, applying them to distributed data in SDI to extract knowledge has remained a challenge. This paper proposes a creative solution, based on distributed computing and geospatial web service technologies for knowledge extraction in an SDI environment. The proposed approach is called Knowledge Discovery Web Service (KDWS), which can be used as a layer on top of SDIs to provide spatial data users and decision makers with the possibility of extracting knowledge from massive heterogeneous spatial data in SDIs. By proposing and testing a system architecture for KDWS, this study contributes to perform spatial data mining techniques as a service-oriented framework on top of SDIs for knowledge discovery. We implemented and tested spatial clustering, classification, and association rule mining in an interoperable environment. In addition to interface implementation, a prototype web-based system was designed for extracting knowledge from real geodemographic data in the city of Tehran. The proposed solution allows a dynamic, easier, and much faster procedure to extract knowledge from spatial data.

ACS Style

Morteza Omidipoor; Ara Toomanian; Najmeh Neysani Samany; Ali Mansourian. Knowledge Discovery Web Service for Spatial Data Infrastructures. ISPRS International Journal of Geo-Information 2020, 10, 12 .

AMA Style

Morteza Omidipoor, Ara Toomanian, Najmeh Neysani Samany, Ali Mansourian. Knowledge Discovery Web Service for Spatial Data Infrastructures. ISPRS International Journal of Geo-Information. 2020; 10 (1):12.

Chicago/Turabian Style

Morteza Omidipoor; Ara Toomanian; Najmeh Neysani Samany; Ali Mansourian. 2020. "Knowledge Discovery Web Service for Spatial Data Infrastructures." ISPRS International Journal of Geo-Information 10, no. 1: 12.

Original research
Published: 28 July 2020 in Journal of Ambient Intelligence and Humanized Computing
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The increasing use of private cars in large cities is accompanied by adverse ramifications such as severe shortage of parking spaces, traffic congestion, air pollution, a high level of fuel consumption, and travel cost. Ridesharing is one of the emerging solutions that facilitate the simultaneous match of drivers and passengers with similar travel schedules. In this paper, ridesharing equals carsharing which involves a cooperative trip of at least two passengers who share an automobile and must match their itineraries. The main objective of this paper is to develop a ridesharing system based on the geosocial network to be employed in Tehran, capital of Iran. In this regard, a new hybrid approach based on GIS and ant colony is developed to provide optimal shared-routes through integrating three main procedures sequentially. First, the spatio-temporal clustering of passengers is carried out using the K-means algorithm, second spatio-temporal matching of passengers ‘clusters, and drivers’ has been carried out by combining Voronoi continuous range query (VCRQ), a region connected calculus (RCC5) and Allen’s temporal interval algebra. Third, the optimum shared-route is found by the ant colony optimization (ACO) algorithm. The proposed hybrid model integrates metric and topological GIS-based methods with a metaheuristic algorithm. It is implemented via a bot “@Hamsafar” within the platform of a robot Telegram messenger. The proposed ridesharing application is applied with 220 passengers and 70 drivers with 61 shared trips in District # 6 of Tehran, Iran. The system are evaluated based on the statistical results, usability questionnaire, time performance, and comparison to some other metaheuristic approaches which in turn demonstrate the efficiency of the proposed algorithm.

ACS Style

Mohammadreza Jelokhani-Niaraki; Najmeh Neysani Samany; Moslem Mohammadi; Ara Toomanian. A hybrid ridesharing algorithm based on GIS and ant colony optimization through geosocial networks. Journal of Ambient Intelligence and Humanized Computing 2020, 12, 2387 -2407.

AMA Style

Mohammadreza Jelokhani-Niaraki, Najmeh Neysani Samany, Moslem Mohammadi, Ara Toomanian. A hybrid ridesharing algorithm based on GIS and ant colony optimization through geosocial networks. Journal of Ambient Intelligence and Humanized Computing. 2020; 12 (2):2387-2407.

Chicago/Turabian Style

Mohammadreza Jelokhani-Niaraki; Najmeh Neysani Samany; Moslem Mohammadi; Ara Toomanian. 2020. "A hybrid ridesharing algorithm based on GIS and ant colony optimization through geosocial networks." Journal of Ambient Intelligence and Humanized Computing 12, no. 2: 2387-2407.

Journal article
Published: 03 May 2020 in Remote Sensing
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Timely and accurate information on crop mapping and monitoring is necessary for agricultural resources management. Accordingly, the applicability of the proposed classification-feature selection ensemble procedure with different feature sets for crop mapping is investigated. Here, we produced various feature sets including spectral bands, spectral indices, variation of spectral index, texture, and combinations of features to map different types of crops. By using various feature sets and the random forest (RF) classifier, the crop maps were created. In aiming to determine the most relevant and distinctive features, the particle swarm optimization (PSO) and RF-variable importance measure feature selection methods were examined. The classification-feature selection ensemble procedure was adapted to combine the outputs of different feature sets from the better feature selection method using majority votes. Multi-temporal Sentinel-2 data has been used in Ghale-Nou county of Tehran, Iran. The performance of RF was efficient in crop mapping especially by spectral bands and texture in combination with other feature sets. Our results showed that the PSO-based feature selection leads to a more accurate classification than the RF-variable importance measure, in almost all feature sets for all crop types. The RF classifier-PSO ensemble procedure for crop mapping outperformed the RF classifier in each feature set with regard to the class-wise and overall accuracies (OA) (of about 2.7–7.4% increases in OA and 0.48–3.68% (silage maize), 0–1.61% (rice), 2.82–15.43% (alfalfa), and 10.96–41.13% (vegetables) improvement in F-scores for all feature sets). The proposed method could mainly be useful to differentiate between heterogeneous crop fields (e.g., vegetables in this study) due to their more obtained omission/commission errors reduction.

ACS Style

Elahe Akbari; Ali Darvishi Boloorani; Najmeh Neysani Samany; Saeid Hamzeh; Saeid Soufizadeh; Stefano Pignatti. Crop Mapping Using Random Forest and Particle Swarm Optimization based on Multi-Temporal Sentinel-2. Remote Sensing 2020, 12, 1449 .

AMA Style

Elahe Akbari, Ali Darvishi Boloorani, Najmeh Neysani Samany, Saeid Hamzeh, Saeid Soufizadeh, Stefano Pignatti. Crop Mapping Using Random Forest and Particle Swarm Optimization based on Multi-Temporal Sentinel-2. Remote Sensing. 2020; 12 (9):1449.

Chicago/Turabian Style

Elahe Akbari; Ali Darvishi Boloorani; Najmeh Neysani Samany; Saeid Hamzeh; Saeid Soufizadeh; Stefano Pignatti. 2020. "Crop Mapping Using Random Forest and Particle Swarm Optimization based on Multi-Temporal Sentinel-2." Remote Sensing 12, no. 9: 1449.

Journal article
Published: 30 April 2020 in Library & Information Science Research
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Spatial features of libraries are crucial to increasing trends in library usage, particularly in the case of attracting students. Selecting a suitable location for the establishment of public libraries can be determined using spatial criteria and by employing Geographic Information System (GIS) in conjunction with Multi-Attribute Decision Making (MADM). The Weighted Linear Composition (WLC) method was used to determine the suitable areas for library construction located in District 5 of Tehran in Iran. This model has a high capability in combining the effect of different values of effective criteria and the weight of each of them in determining the suitable areas for the establishment of the library. Based on the findings, 42% of the total study area was labeled as suitable for public library construction as indicated by the centrality criteria. The remainder of the study area was classified as so: 27% of the districts were in the suitable class, 34% in the moderate class, and 39% in the unsuitable class. The results of this study could be employed as potential tools in urban management and planning to locate suitable areas for the construction of libraries and thereby increase the overall rates and trends of library usage.

ACS Style

Saman Nadizadeh Shorabeh; Ahmadreza Varnaseri; Mohammad Karimi Firozjaei; Fatemeh Nickravesh; Najmeh Neysani Samany. Spatial modeling of areas suitable for public libraries construction by integration of GIS and multi-attribute decision making: Case study Tehran, Iran. Library & Information Science Research 2020, 42, 101017 .

AMA Style

Saman Nadizadeh Shorabeh, Ahmadreza Varnaseri, Mohammad Karimi Firozjaei, Fatemeh Nickravesh, Najmeh Neysani Samany. Spatial modeling of areas suitable for public libraries construction by integration of GIS and multi-attribute decision making: Case study Tehran, Iran. Library & Information Science Research. 2020; 42 (2):101017.

Chicago/Turabian Style

Saman Nadizadeh Shorabeh; Ahmadreza Varnaseri; Mohammad Karimi Firozjaei; Fatemeh Nickravesh; Najmeh Neysani Samany. 2020. "Spatial modeling of areas suitable for public libraries construction by integration of GIS and multi-attribute decision making: Case study Tehran, Iran." Library & Information Science Research 42, no. 2: 101017.

Journal article
Published: 25 October 2019 in Cities
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Senior citizens are commonly regarded as the vulnerable class of society; requiring elderly-friendly urban environments as well as particular municipal services to respond to their specific needs. This study proceeds to design a PPGIS (Public Participation GIS) by means of integrating VGI (Volunteered Geographic Information), GIS and MCDA (Multicriteria Decision Analysis) techniques aiming to evaluate the age-friendliness of cities. The proposed PPGIS assesses the age-friendliness of cities through integrating certain criteria weights determined by the elderly with VGI collected by regular citizens. The system was used to create the age-friendliness map of district # 6 of Tehran, Iran. The resulting map shows that the center of the district is more age-friendly than the other areas. Based on the evaluation results, the majority of citizens found the system to be a suitable tool for evaluating the age-friendliness of the city, collecting VGI related to the elderly’s urban environment and helping urban planners improve the age-friendliness of the city. Nonetheless, a rather small percentage of citizens concur that: (i) the PPGIS is a suitable tool for persuading citizens to participate in the city age-friendliness assessment and that (ii) the PPGIS provides a reliable way for assessing the age-friendliness of cities.

ACS Style

Mohammadreza Jelokhani-Niaraki; Fakhreddin Hajiloo; Najmeh Neysani Samany. A Web-based Public Participation GIS for assessing the age-friendliness of cities: A case study in Tehran, Iran. Cities 2019, 95, 102471 .

AMA Style

Mohammadreza Jelokhani-Niaraki, Fakhreddin Hajiloo, Najmeh Neysani Samany. A Web-based Public Participation GIS for assessing the age-friendliness of cities: A case study in Tehran, Iran. Cities. 2019; 95 ():102471.

Chicago/Turabian Style

Mohammadreza Jelokhani-Niaraki; Fakhreddin Hajiloo; Najmeh Neysani Samany. 2019. "A Web-based Public Participation GIS for assessing the age-friendliness of cities: A case study in Tehran, Iran." Cities 95, no. : 102471.

Journal article
Published: 29 April 2019 in Cities
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Wayfinding is one of the most daily activities of peoples in urban spaces which could be facilitated by a set of landmarks to provide a mental map of the environment. Landmark detection in urban spaces is yet one of the great challenges in landmark-based wayfinding. This paper aims to apply new sources of geo-tagged photos derived from social media like Telegram for landmark extraction. This paper proposed a method to extract landmarks automatically through clustering of geo-tagged photos by Density Based Spatial Clustering of Applications with Noise (DBSCAN) method and object detection by deep artificial neural network (deep belief network) algorithm. The proposed method is implemented in 48 different routes of 3 districts of Tehran, Iran. The accuracy assessment demonstrated the efficiency of the algorithms for landmark extraction from huge geo-tagged photographs. Furthermore, the extracted landmarks are evaluated by 120 wayfinders. The experimental results demonstrated the usability of the proposed landmarks in wayfinding process with 87% of user satisfaction.

ACS Style

Najmeh Neysani Samany. Automatic landmark extraction from geo-tagged social media photos using deep neural network. Cities 2019, 93, 1 -12.

AMA Style

Najmeh Neysani Samany. Automatic landmark extraction from geo-tagged social media photos using deep neural network. Cities. 2019; 93 ():1-12.

Chicago/Turabian Style

Najmeh Neysani Samany. 2019. "Automatic landmark extraction from geo-tagged social media photos using deep neural network." Cities 93, no. : 1-12.

Original research
Published: 03 April 2019 in Journal of Ambient Intelligence and Humanized Computing
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Wayfinding or leading a moving user from an origin to a target is one of the main research focuses in urban context-aware systems. Space and time are two dominant properties of the context-aware wayfinding process and spatio-temporal relevancy between the fixed urban entities and the moving users determine whether an entity is related to the moving user or not. This paper specifically concentrates on the development of customized fuzzy interval algebra (FIA5) for detecting spatio-temporally relevant contexts to the user. This paper integrates fuzzy spatial and temporal intervals and customizes the spatio-temporal relations between the new data models—called fuzzy spatio temporal prism relevancy (FSTPR25) model-based on Allen’s fuzzy multi interval algebra. In this implementation, the FSTPR25 helps the tourist to find his/her preferred areas that are spatio-temporally relevant with two optimistic and pessimistic strategies. The experimental results in a scenario of tourist navigation are evaluated with respect to the accuracy of the model in 450 iterations of the algorithm in 15 different routes based on the statistical quantifiers in Tehran, Iran. The evaluation process demonstrated the high accuracy and user satisfaction of the optimistic strategy in real-world applications.

ACS Style

Najmeh Neysani Samany; Mahmoud Reza Delavar; Nicholas Chrisman. Developing FIA5 to FSTPR25 for modeling spatio-temporal relevancy in context-aware wayfinding systems. Journal of Ambient Intelligence and Humanized Computing 2019, 11, 2453 -2466.

AMA Style

Najmeh Neysani Samany, Mahmoud Reza Delavar, Nicholas Chrisman. Developing FIA5 to FSTPR25 for modeling spatio-temporal relevancy in context-aware wayfinding systems. Journal of Ambient Intelligence and Humanized Computing. 2019; 11 (6):2453-2466.

Chicago/Turabian Style

Najmeh Neysani Samany; Mahmoud Reza Delavar; Nicholas Chrisman. 2019. "Developing FIA5 to FSTPR25 for modeling spatio-temporal relevancy in context-aware wayfinding systems." Journal of Ambient Intelligence and Humanized Computing 11, no. 6: 2453-2466.

Article
Published: 08 March 2019 in Journal of Mountain Science
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Urban buildings and urban traffic network are considered as the vital arteries of cities which have particular effects especially after the crisis in the search and rescue operations. The aim of this study is to determine the vulnerability of urban areas especially, buildings and traffic networks using multicriteria geographic information systems and decisionmaking methods. As there are many effective criteria on the seismic vulnerability that they have uncertain and vague properties, the method of this paper is applying fuzzy ordered weighted average (OWA) to model the seismic vulnerability of urban buildings and traffic networks in the most optimistic and pessimistic states. The study area is district 6 of Tehran that is affected by the four major faults, and thus will be threatened by the earthquakes. The achieved results illustrated the vulnerability with different degrees of risk levels including very high, high, medium, low and very low. The results show that in the most optimistic case 14% and in the pessimistic case 1% of buildings tolerate in very low vulnerability. The vulnerability of urban street network also indicates that in the optimistic case 12% and in the pessimistic case at most 9% of the area are in appropriate condition and the North and North-East of the study area are more vulnerable than South of it.

ACS Style

Yasaman Asadi; Najmeh Neysani Samany; Keyvan Ezimand. Seismic vulnerability assessment of urban buildings and traffic networks using fuzzy ordered weighted average. Journal of Mountain Science 2019, 16, 677 -688.

AMA Style

Yasaman Asadi, Najmeh Neysani Samany, Keyvan Ezimand. Seismic vulnerability assessment of urban buildings and traffic networks using fuzzy ordered weighted average. Journal of Mountain Science. 2019; 16 (3):677-688.

Chicago/Turabian Style

Yasaman Asadi; Najmeh Neysani Samany; Keyvan Ezimand. 2019. "Seismic vulnerability assessment of urban buildings and traffic networks using fuzzy ordered weighted average." Journal of Mountain Science 16, no. 3: 677-688.

Journal article
Published: 24 October 2018 in Asian Journal of Water, Environment and Pollution
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ACS Style

Kayvan Bagheri Sayed Shekari; Najmeh Neysani Samany; Morteza Omidipoor; Sirous Hashemi Darehbadami. Uncertainty Modelling of Waste Disposal Site Selection (Case Study: Marivan City). Asian Journal of Water, Environment and Pollution 2018, 15, 89 -98.

AMA Style

Kayvan Bagheri Sayed Shekari, Najmeh Neysani Samany, Morteza Omidipoor, Sirous Hashemi Darehbadami. Uncertainty Modelling of Waste Disposal Site Selection (Case Study: Marivan City). Asian Journal of Water, Environment and Pollution. 2018; 15 (4):89-98.

Chicago/Turabian Style

Kayvan Bagheri Sayed Shekari; Najmeh Neysani Samany; Morteza Omidipoor; Sirous Hashemi Darehbadami. 2018. "Uncertainty Modelling of Waste Disposal Site Selection (Case Study: Marivan City)." Asian Journal of Water, Environment and Pollution 15, no. 4: 89-98.

Journal article
Published: 01 September 2018 in Ocean & Coastal Management
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Recent incremental trends in environmental pollutants alongside garbage disposals and wastes have undoubtedly affected the global visage of coastal areas. High population density, in conjunction with numerous tourists who visit coastal regions along with wastewater from factories, industrial centers, cities, agricultural activities, especially oil contaminants, are amongst major contributors to pollution in coastal areas. Fortunately, developing countries have recently instigated developmental procedures with the participation of the general public in an effort to protect the environment. Thus, one can perceive the importance of creating an appropriate system, which facilitates public participation in monitoring coastal environments. Such a system would notably provide solutions for many issues of pollution management in coastal regions. The purpose of this study is to design and implement a Volunteered Geographic Information (VGI)-based system through integration of concepts and methods from three areas of Geographic Information System (GIS), coastal pollution management, and public participation in order to monitor coastal pollution. After the implementation phase, Nowshahr port city, Mazandaran Province, Iran, was selected as the study area, wherein tourists, residents, and other present individuals were asked to report observable pollutants at their location. After a 3 day monitoring of coastal regions, 98 reports were registered in the system, indicating high amounts of contamination within the respective coastal area. 86% of the total recorded reports were accounts of accumulation of garbage and other dispersed solid material such as foliage and tree trunks, which were somehow the main source of pollution. 10% and 4% of the remaining reports were related to the wastewater pollution and oil contaminants, respectively. According to survey results, 74% of users were satisfied with ease of use and performance of system (26% voted very good and 48% voted good) amongst whom 67% noted the system as an advantageous and effective tool for monitoring the coastal pollution (31% cases of very good and 36% cases of good).

ACS Style

Sima Fatehian; Mohammadreza Jelokhani-Niaraki; Ata Abdollahi Kakroodi; Qiuomars Yazanpanah Dero; Najmeh Neysani Samany. A volunteered geographic information system for managing environmental pollution of coastal zones: A case study in Nowshahr, Iran. Ocean & Coastal Management 2018, 163, 54 -65.

AMA Style

Sima Fatehian, Mohammadreza Jelokhani-Niaraki, Ata Abdollahi Kakroodi, Qiuomars Yazanpanah Dero, Najmeh Neysani Samany. A volunteered geographic information system for managing environmental pollution of coastal zones: A case study in Nowshahr, Iran. Ocean & Coastal Management. 2018; 163 ():54-65.

Chicago/Turabian Style

Sima Fatehian; Mohammadreza Jelokhani-Niaraki; Ata Abdollahi Kakroodi; Qiuomars Yazanpanah Dero; Najmeh Neysani Samany. 2018. "A volunteered geographic information system for managing environmental pollution of coastal zones: A case study in Nowshahr, Iran." Ocean & Coastal Management 163, no. : 54-65.

Journal article
Published: 27 September 2017 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Landslide is one of the main geomorphic processes which effects on the development of prospect in mountainous areas and causes disastrous accidents. Landslide is an event which has different uncertain criteria such as altitude, slope, aspect, land use, vegetation density, precipitation, distance from the river and distance from the road network. This research aims to compare and evaluate different fuzzy-based models including Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), Fuzzy Gamma and Fuzzy-OR. The main contribution of this paper reveals to the comprehensive criteria causing landslide hazard considering their uncertainties and comparison of different fuzzy-based models. The quantify of evaluation process are calculated by Density Ratio (DR) and Quality Sum (QS). The proposed methodology implemented in Sari, one of the city of Iran which has faced multiple landslide accidents in recent years due to the particular environmental conditions. The achieved results of accuracy assessment based on the quantifier strated that Fuzzy-AHP model has higher accuracy compared to other two models in landslide hazard zonation. Accuracy of zoning obtained from Fuzzy-AHP model is respectively 0.92 and 0.45 based on method Precision (P) and QS indicators. Based on obtained landslide hazard maps, Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR respectively cover 13, 26 and 35 percent of the study area with a very high risk level. Based on these findings, fuzzy-AHP model has been selected as the most appropriate method of zoning landslide in the city of Sari and the Fuzzy-gamma method with a minor difference is in the second order.

ACS Style

N. Mijani; N. Neysani Samani. COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2017, XLII-4/W4, 407 -416.

AMA Style

N. Mijani, N. Neysani Samani. COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2017; XLII-4/W4 ():407-416.

Chicago/Turabian Style

N. Mijani; N. Neysani Samani. 2017. "COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W4, no. : 407-416.

Journal article
Published: 01 January 2013 in Journal of Ambient Intelligence and Smart Environments
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ACS Style

Najmeh Neysani Samany; Mahmoud Reza Delavar; Nicholas Chrisman; Mohammad Reza Malek. Spatial relevancy algorithm for context-aware systems (SRACS) in urban traffic networks using dynamic range neighbor query and directed interval algebra. Journal of Ambient Intelligence and Smart Environments 2013, 5, 605 -619.

AMA Style

Najmeh Neysani Samany, Mahmoud Reza Delavar, Nicholas Chrisman, Mohammad Reza Malek. Spatial relevancy algorithm for context-aware systems (SRACS) in urban traffic networks using dynamic range neighbor query and directed interval algebra. Journal of Ambient Intelligence and Smart Environments. 2013; 5 (6):605-619.

Chicago/Turabian Style

Najmeh Neysani Samany; Mahmoud Reza Delavar; Nicholas Chrisman; Mohammad Reza Malek. 2013. "Spatial relevancy algorithm for context-aware systems (SRACS) in urban traffic networks using dynamic range neighbor query and directed interval algebra." Journal of Ambient Intelligence and Smart Environments 5, no. 6: 605-619.