Research activities per year filter by:
Articles
Publication Date: 2025
Land Use Policy (0264-8377)
This paper presents a method for quantitatively evaluating property landscape views by integrating Building Information Model (BIM) and 3D Geographical Information Systems (3D GIS). Previous studies have used limited methods such as dummy variables and the hedonic method, which are subjective and implicit. Additionally, GIS-based methods have not fully accounted for important variables such as building layout, observer position, and landscape diversity, all of which impact view assessment quality. To address these limitations, the proposed method integrates 3D GIS and BIM to accurately determine the field of view, while considering the observer's position in relation to windows, window size, observer field of view, landscape diversity and quality, and the simultaneous presence of visible landscapes. The weight of simultaneous presence and intensifying effects of different landscapes were modeled using Sugeno fuzzy measures and Choquet integral. An Ordered Weighted Average operator (OWA) was designed to estimate the building's view score in optimistic, normal, and pessimistic states. The proposed method was evaluated on a case study building, demonstrating its effectiveness in measuring and ranking property based on visible landscape views. Additionally, the proposed method can be applied in pre-construction and architectural design phases to identify optimal positions for windows and terraces, to enhance the aesthetic value of a building's view. © 2025 Elsevier Ltd
Publication Date: 2022
Transactions in GIS (13611682)(2)
Due to the many objectives and constraints involved in urban land use planning (ULUP), this is considered as a many-objective and complex optimization problem that needs a variety of geographical analyses. In this article, the main target is improving NSGA-III as an advanced many-objective optimization algorithm for solving the ULUP problem. In this study, five objective functions (i.e., consistency, dependency, compactness, suitability, and per capita violation of land uses) are considered for their simultaneous optimization for allocation. The proposed algorithm is tested using the spatial data of region 7, district 1 of Tehran using a vector format. To evaluate the results, two more real datasets were implemented. The performance of the improved algorithm is compared concerning NSGA-II and NSGA-III in the main case study area and two other instances. The comparison results show that the improved algorithm increases the convergence and diversity of the generated solutions in ULUP concerning the results obtained by these two other algorithms. The results of the optimization with these methods can help decision-makers toward sustainable development in the construction of new cities, new towns, and smart cities. © 2021 John Wiley & Sons Ltd.
Publication Date: 2020
Land Use Policy (0264-8377)
Spatial urban land-use planning is a complex process, through which we aim to allocate suitable land-uses while taking into consideration multiple and conflicting objectives and constraints under certain spatial contexts. Landowners should be modeled as players that are able to interact with each other so as to seek their best land-uses while considering multiple objectives and constraints simultaneously. Game theory provides a tool for land-use planners to model and analyze such interactions. In this paper, spatial urban land-use planning is considered as a game to model local competitions between landowners, whose players (i.e. landowners) of which play to pick the most suitable land-use for themselves. The game is defined based on the objectives of consistency, dependency, suitability, compactness of land-uses, and land-use per capita demand. In this paper, three different scenarios are designed for the players. In the first scenario, the players are greedy and only accept the most compatible land-use. In the second scenario, conversely, the players are fully collaborative and care about other players’ payoff. In the third scenario, the players are first greedy, but when they cannot achieve an agreement with other players, they change their attitude to become gradually collaborative for reaching the Nash equilibrium (NE). Furthermore, the dissatisfaction index (DI), which represents the number of unsatisfied landowners with their current land-use, is defined to compare the different scenarios. The proposed model is tested in a district located in District 7 in Tehran (the capital city of Iran) with 2710 parcels. Results of the first scenario showed that, at the beginning of the game, 50 % of the landowners were not satisfied with their current land-uses, but after 50 iterations, about 100 landowners were dissatisfied with their land-use and this scenario was not able to reach the NE. Results of the second scenario indicated that, in order to reach an optimized layout, 325 parcels needed to be changed. Also, after reaching the NE in this scenario, values of the objective functions did not significantly improve. So, lowering the expectations of the players would not lead to appropriate results. The outcomes of the third scenario provided appropriate results, which could be achieved when the expectation levels of the players could be changed during the game. Furthermore, the NE was obtained among the players and the objective functions improved by 20 % on average in comparison with the other scenarios. Moreover, results of the scenarios were compared with the optimized layout obtained by a genetic algorithm (GA) using different parameter values. Results of the comparison also revealed that the urban layouts produced by game theory improved the objective function values obtained by the GA in about 10 % and improved the GA's running time in more than 85 %, on average in this research. © 2020 Elsevier Ltd
Publication Date: 2020
Process Safety and Environmental Protection (09575820)
The urban sewer pipeline network is a vital urban infrastructure that is highly at risk of failure and its deterioration can be harmful to the environment and public health and safety. Therefore, for performing an effective rehabilitation program, it is needed to prioritize the sewer pipelines. In this paper, a novel risk assessment approach is proposed for prioritizing sewer pipelines based on a combination of Geospatial Information System (GIS) and Analytic Hierarchy Process (AHP)- Data Envelopment Analysis (DEA). To do so, it calculates the Probability of Failure (PoF), along with the Consequence of Failure (CoF) for the sewer pipelines. Bayesian Network (BN) as the probabilistic method is used to calculate PoF. The main contribution of the study lies in using a combination of GIS, AHP, and DEA for quantitatively assessing the CoF, firstly, the criteria weights are determined by the AHP method through experts’ judgments. Then, GIS functionalities along with DEA, are used to calculate scores for the alternatives. Finally, the outputs of the AHP method are integrated with the outputs of the DEA method in order to calculate CoF. The proposed method is applied to a local sewer pipeline network as a real-world case study to assess its risk of failure. The results indicated that the sewer pipelines are in good condition in the study area and among 1605 sewer pipelines, only 48 of them (about 3 %) are in a critical situation that it is needed to perform rehabilitation program. © 2019 Institution of Chemical Engineers
Publication Date: 2019
International Journal of Disaster Risk Reduction (22124209)
The paper proposes an alternative new approach in contrast with the traditional methods to deal with multi-criteria group decision-making problems. It takes into account the multi-criteria group decision-making process as a multi-stakeholder multi-issue negotiation problem, in which stakeholders attempt to lead a consensus on the relative importance of the criteria by using software agents. To do so, it suggests three main steps: pre-negotiation, automated negotiation, and evaluation phases. The pre-negotiation phase is a human-computer interaction by which software agents attempt to exhibit and model the preferences space of the stakeholders. In the automated negotiation phase, the agents come together to negotiate on the criteria weights to reach an agreement on behalf of the stakeholders. Finally, in the evaluation phase, the evaluator agent applies a sensitivity analysis method to determine output variations due to the inputs and parameters. The proposed method is applied to a disaster management practice as a real-world case study, in which some stakeholders jointly attempt to identify the strategic roads in disaster situations specifically, flood events. Three spatial criteria are used for evaluating the road transportation network: load capacity, access to emergency suppliers, and importance of the roads in geometric structure of the network. The results of the study confirm that the proposed method is an efficient alternative approach to deal with multi-criteria group decision-making problems. © 2019 Elsevier Ltd
Publication Date: 2019
ISPRS International Journal of Geo-Information (22209964)(12)
A comprehensive fire risk assessment is very important in dense urban areas as it provides an estimation of people at risk and property. Fire policy and mitigation strategies in developing countries are constrained by inadequate information, which is mainly due to a lack of capacity and resources for data collection, analysis, and modeling. In this research, we calculated the fire risk considering two aspects, urban infrastructure and the characteristics of a high-rise building for a dense urban area in Zanjan city. Since the resources for this purpose were rather limited, a variety of information was gathered and information fusion techniques were conducted by employing spatial analyses to produce fire risk maps. For this purpose, the spatial information produced using unmanned aerial vehicles (UAVs) and then attribute data (about 150 characteristics of each high-rise building) were gathered for each building. Finally, considering high-risk urban infrastructures, like the position of oil and gas pipes and electricity lines and the fire safety analysis of high-rise buildings, the vulnerability map for the area was prepared. The fire risk of each building was assessed and its risk level was identified. Results can help decision-makers, urban planners, emergency managers, and community organizations to plan for providing facilities and minimizing fire hazards and solve some related problems to reduce the fire risk. Moreover, the results of sensitivity analysis (SA) indicate that the social training factor is the most effective causative factor in the fire risk. © 2019 by the authors.
Publication Date: 2019
Environmental Monitoring and Assessment (01676369)(6)
The water table is an important piece of data for hydrogeological studies, particularly as input data to groundwater simulation models. Since the accuracy of groundwater simulation models significantly depends on input data, this study highlights the application of fuzzy kriging to improve the accuracy of water table interpolation. The results of the fuzzy kriging approach are compared with common methods in water table interpolation like ordinary kriging, inverse distance weighting (IDW), and Thiessen polygon methods to justify the suitability of the fuzzy kriging. The Gilan and Zanjan plains, located in the northwest of Iran, are used as case study areas. The Gilan Plain is characterized by a dense and regular piezometric network and gentle hydraulic gradient. The longitudinal plain of Zanjan has a sparse and irregular piezometric network and steep hydraulic gradient. Since these plains have different piezometric network configurations, the sensitivity of the interpolation methods to the monitoring point configuration is analyzed. The cross-validation method is employed to validate the accuracy of interpolation methods in water table interpolation. In control points, the average of root-mean-square errors associated with groundwater water table values estimated using fuzzy kriging, ordinary kriging, IDW, and Thiessen polygon methods are obtained to be respectively 1.36, 1.93, 3.49, and 9.10 in the Gilan Plain and 13.60, 22.86, 32.30, and 59.81 in the Zanjan Plain. The results indicate that the fuzzy kriging technique has greater precision in comparison with other methods, especially under the conditions of the sparse piezometric network and steep hydraulic gradient. The results also demonstrate that the used methods generally have higher accuracy in the Gilan Plain with a regular piezometric network than in the Zanjan Plain. Furthermore, Thiessen polygon, IDW, and ordinary kriging methods overestimated water table in comparison with the fuzzy kriging method in our cases. This overestimation may cause large error values in subsequent calculations such as water budget and aquifer storage which play a major role in the appropriate management of water resources. © 2019, Springer Nature Switzerland AG.
Publication Date: 2017
ISPRS International Journal of Geo-Information (22209964)(9)
Urban land-use allocation is a complicated problem due to the variety of land-uses, a large number of parcels, and different stakeholderswith diverse and conflicting interests. Various approaches and techniques have been proposed for the optimization of urban land-use allocation. The outputs of these approaches are almost optimum plans that suggest a unique, appropriate land-use for every land unit. However, because of some restrictions, such stakeholder opposition to a specific land-use or the high cost of land-use change, it is not possible for planners to propose a desirable land-use for each parcel. As a result, planners have to identify other priorities of the land-uses. Thus, ranking land-uses for parcels along with optimal land-use allocation could be advantageous in urban land-use planning. In this paper, a parcel-levelmodel is presented for ranking and allocating urban land-uses. The proposed model benefits from the capabilities of geographic information systems (GIS), fuzzy calculations, and Multi-Criteria Decision-Making (MCDM) methods (fuzzy TOPSIS), intends to improve the capabilities of existing urban land-use planning support systems. In this model, as a first step, using fuzzy calculations and spatial analysis capabilities of GIS, quantitative and qualitative evaluation criteria are estimated based on physical characteristics of the parcels and their neighborhoods. In the second step, through the fuzzy TOPSIS method, urban land-uses are ranked for each of the urban land units. In the third step, using the proposed land-use allocation process and genetic algorithm, the efficiency of the model is evaluated in urban land-use optimal allocation. The proposed model is tested on spatial data of region 7, district 1 of Tehran. The implementation results demonstrate that, in the study area, the land-use of 77.2% of the parcels have first priority. As such, the land-use of 22.8% of the parcels do not have first priority, and are prone to change. © 2017 by the Author.
Publication Date: 2017
Geographical Analysis (00167363)(1)
Usually, allocation of resources is an optimization problem which involves a variety of conflicting economic, social, and ecological objectives. In such a process, advanced geographic analyst tool for manipulation of spatial data and satisfaction of multiple objectives is essential to the success of decision-making. The present research intends to demonstrate the application of a multiobjective optimization method based on NSGA-II (we call it HNSGA-II), along with Geographical Information System (GIS) to select suitable sites for the establishment of large industrial units. Having defined the elements of HNSGA-II for the site selection of industrial units, the method is tested on the data of Zanjan province, Iran, as the case study. The results showed that the proposed approach can easily find a variety of optimized solutions, giving the decision-makers the possibility to opt for the most propitious solution. Using this method, the achievement level regarding each objective function can be studied for any of the nondominated solutions. © 2016 The Ohio State University
Regarding the complexity of natural disasters in cities and the urgent need to employ methods in order to reduce the risk in residential areas, the risk management as a new and effective method in preventing and preparation for critical situations, has been employed in different ways throughout the world. Risk management includes a set of processes needed for identification, analysis and reaction against the crisis that aims at maximization of desired goals and minimization of risks and adverse consequences. This paper intends to present a GIS-based fuzzy approach for risk assessment in residential areas. Places such as medical centers and parks are effective factors in reducing the risk and the gas stations and high voltage power stations are factors that increase the risk. Now regarding the distance between each urban feature and the above features, fuzzy linguistic variables are defined and according to the rules extracted by expert, the risk of each feature is separately estimated and designed as a risk map for each area. Now with the help of this map, we can reduce the risk to which every building is subjected by constructing the needed centers and also fortification plans. © Gi4DM 2011 - GeoInformation for Disaster Management.All right reserved.
Road accidents are one of the major causes of mortality around the world and over 1,300,000 people are killed annually in the road accidents. Most of fatal accidents occur on the roads outside the city. Some of the casualties are killed in the crash moment and the others after the accident, mostly due to late arrival of rescue groups. The late arrival of rescue groups is mostly because of the lack of rapid and timely notice from accident. For this reason, this paper proposes the employment of location-based service to develop a system that can be used easily to locate an accident more quickly and inform emergency service to accelerate the transfer of victims to medical centers. This system is composed of two parts. The first part of the system is activated when something hits the impact sensors embedded in the vehicle and then it captures the location of vehicle via GPS. Employing GSM, the first part of the system sends an SMS which contains the location and other necessary information of vehicle to the second part of system which is situated in the emergency center. After the SMS is delivered, the system is able to locate the accident on the map and dispatch the rescue groups to the place of accident. © Gi4DM 2011 - GeoInformation for Disaster Management.All right reserved.
