Determining effect of meteorological parameters on tourism of metropolises based on presenting integrated spatial-temporal predicting model for air pollutants (case study: Tehran)

Environmental problems in tourist places is one of the major problems of tourism industry, also air pollution in tourist areas is one of the most important environmental problems. Tehran is capital of Iran and it has plenty of tourist sites. The air pollution has hit the tourism in this city. Therefore, this research was carried out for modeling, control and manage of air pollution in Tehran. Based on the previous models presented for air pollution management, the possibility of simultaneous prediction of pollution based on time and place variables has been less considered. Therefore, in this research, for the first time, a spatial-temporal model for pollution management in Tehran was presented. In this research, the spatial model in the GIS environment for each pollutant was defined. Then, based on a Python program, modeling by neural networks in GIS environment for each pollutant at each arbitrary location of the city was implemented. According to validation of model, error values were acceptable. This research model can predict air pollutants, and therefore tourism desirability of each cities point can be estimated based on air pollutants concentration.