Mehrdad AhangarCani; Mohammad Reza Malek
Abstract
Extended Abstract
Introduction and Objective
Road traffic accidents impose numerous social, economic, and cultural costs upon various societies, especially developing countries. Identification of accident blackspots is a method proposed to deal with car accident risks. Among various events associated ...
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Extended Abstract
Introduction and Objective
Road traffic accidents impose numerous social, economic, and cultural costs upon various societies, especially developing countries. Identification of accident blackspots is a method proposed to deal with car accident risks. Among various events associated with transportation network, road traffic accidents play a significant role, because of their specific features, including high frequency, high intensity and the chance of direct involvement of all members of the community.This problem is more conspicuous in developing countries such as Iran. The present study aims to identifyaccidentblackspotsand to prepare risk map for road trafficaccidents in Babol city using volunteered geographic information.
Materials and methods
According to the characteristics of the study area, the present study takes advantage of criteria such as distance from population centers, proximity to city squares, distance from footbridges, and proximity to road intersections to identifyaccidentblackspotsand a prepare risk map for roadtraffic accidents in Babol city. Accident blackspots detected by volunteered geographic information, along with the criteria determined by applying analytic hierarchy process (AHP) and analytic network process (ANP) were compared in a pairwise manner, and their respective weight was calculated to showtheir specific level of impact. Ultimately, a risk map was produced for the risk of road traffic accidents obtained from each method. In order to evaluate the accuracy of the identified accident blackspots obtained from volunteered geographic information, as well as the accuracy of susceptibility maps, ROC curve and Kappa Coefficient were applied to police official records.
Results and Discussion
According to the findings, Jame Mosque shopping center, Shahabnia shopping center, intersection of Farhangstreet and Velayat square were identified as the most accident-prone areas in Babol city. Also, among the prespecified criteria, distance from population centers and distance from intersections are considered to be the most important criteria, respectively. Results obtained from the evaluation criteria indicatedhigh accuracy of volunteered geographic information, and thus it is concluded that this kind of information can be effective in determining the accident blackspotsinBabol city. Also, the ANP method works better than AHP method in preparing the risk map of accidents.
Conclusion and Future works
Due to the large number of road accidents, especially in developing countries,the issue of accident blackspotsand providing a risk map for road trafficaccidents are an essential part of roads safety. In the present study, volunteered geographic information was used, along with multivariate decision-making methods of analytic hierarchy process (AHP) and analytic network process (ANP) to identifyaccident blackspots based on number, causes and severity of accidents and to develop a risk map for driving accidents in Babol city. Moreover, the criteria of distance from population centers, proximity to the city squares, distance from the footbridges, and adjacency to intersections were used to determine accident blackspotsand to prepare a risk map for driving accidents in Babol city. According to the results, Jame Mosque shopping center, Shahabnia shopping center, Farhang intersection and Velayat square were identified as the most accident-prone points in Babol city. Also, distance from population centers and distance from intersectionswere identified as the most important criteria, respectively. Evaluation criteria demonstrated that volunteered geographic information can be effective and accurate in determining accident blackspotsinBabol city. Also, the ANP method worked better than AHP method in preparing the risk map of driving accidents. The method proposed in this study to identify accident blackspots and preparedriving accidents risk maps can be generalized to other areas. Basedon the characteristics of specific routes, other criteria such as arc radius, longitudinal slope can alsobe used. It is also suggested that the results of other methods used for investigation ofaccidentblackspotsand production of risk maps based onvolunteered geographic information (VGI) are compared with the results of the present study.
Saeid Hamzeh; Afshin Amiri
Abstract
Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide ...
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Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide susceptibility maps provide important and valuable information,including time scale of possible future landslides, which are usedfor predicting landslide hazards. Since predicting the time of landslide occurrence is beyond the capability of science and knowledge, identifying areas susceptible to landslide and ranking them can extensively restrict the damages caused by landslide. Therefore, it is essential to zone landslide risk and identify factors affecting it. Analytic Network Process(ANP) is aGIS-based Multi-Criteria Decision Analysis(GIS MCDA) method successfully applied to many decision-making systems. The present study seeks to evaluate landslide risk and achieve a zoning map for the sub-basin under study using ANP and Weighted Overlaymethods. Materials and Methods Based on the literature and using different experts’ viewpoint, criteria affecting landslide risk were identified and five major criteria including topography, land use and land cover, geology, hydrometry and infrastructure were selected. The selected criteria include the following sub-criteria: slope, slope direction, curvature, elevation, lithology, soil type, land use, vegetation density, distance from roads, distance from habitat, river and drainage density and precipitation. The effective factor layers were standardized and a specific scale was defined for their units.Then, each layer was assigned a weight based on its role and importanceusing Analytic Network Process.Proposed to modify Analytic Hierarchical Process(AHP), this method (ANP) relies on the analyses of the human brain for complex and fuzzy problems.Network Analysis Process generally includes the following steps: determining indicators, criteria and options;classifying identified criteria into clusters and elements; determining the relationship between clusters, elements and options; performing pairwise comparisons between clusters, elements and options, and finally calculating the final weight of elements and options. UsingWeightedOverlaymethod, these elements were then integrated with their related coefficients and the final landslide risk map was obtained. Results and discussion Each criteria and sub-criteria were weighted using Analytic Network Processmethod.Topographic and land cover criteria had the most and hydrographic criteria had the least impact on the landslide occurrence. According to the final map, most landslides have occurred in eastern and southern slopes at an altitude of 500 to 2,200 meters. Moreover, 17/31% of the study area was located in the very high-risk class and 33% in the high risk class (about half of the area has high potential of landslide). Previous landslide data were used to assess the landslide zoning map results. Results indicate that most landslides have occurred in the high risk class (about 35% of landslides) and only about 4% of landslides have occurred in the very low risk class. Conclusion Landslide is one of the natural hazards causing serious harms and problems for human life. Identifying the factors affecting landslide and zoning its hazard is especially important for the identification of risky and susceptible areas.So, landslides were selected as one of the main topics of the study with the aim of controlling and managing its hazards.The ANP network analysis method was used to model and predict landslide risk in this research.Each criteria and sub-criteria were weighted and overlapped to producethe map of relative landsliderisk.The lowest risk was observed in the northern parts of the region, and the highest landslide risk was observed in the northern hillsides with higher humidity.WeightedOverlaymethod and network analysis model were effective in predicting landslide susceptibility and producing landslide zoning map.
