GIS based multi criteria decision making application for electric bicycle sharing and charging stations

Nowadays, many problems are observed in the cities that are developing and the population densities are increasing accordingly. Environmental problems and transportation problems are among the first to come up. While many problems can be prevented by the planned development of cities, other plans are required to reduce carbon emissions. There are many sources of carbon emissions; energy production, industry, transportation and use in housing are the main sources. In order to reduce carbon emissions in energy production, it is known that the tendency towards renewable energy sources is increasing worldwide. In addition, it is observed that electric vehicles are becoming widespread in transportation, which is one of the other dominant carbon emission sources. Bicycles, which are widely used in certain regions around the world, are an important alternative to reduce the use of motor vehicles. Bicycle sharing systems, which were seen in the Netherlands in the 1960s, are still widely used today and are becoming more common with electric bicycles. It is predicted that electric bike sharing systems will play an important role in urban transportation. In this thesis study, the most suitable sites of sharing and charging stations for electric bicycles were tried to be determined in Ilkadım district of Samsun province. First of all, depending on the literature research and expert opinions, the criteria that will affect the locations of the sharing and charging stations in Ilkadım district have been determined. Data belonging to the determined criteria were obtained and criteria maps were created with Geographical Information Systems (GIS) software. The criteria are weighted with the Best Worst Method (BWM), a relatively new Multi-Criteria Decision Making (MCDM) method. With the help of GIS, weighted criteria layers were evaluated together and the most suitable places for electric bike sharing and charging stations were tried to be determined and 24 station locations were suggested for the study area. Keywords : Electric bicycle sharing and charging, Multi-criteria decision making, Geographical Information Systems, Best Worst Method