Modeling the relationships between urban green space, air and noise pollution and temperature using landscape metrics

Green space has an important role in the quality of urban environments. The purpose of this study was to investigate the relationships between urban green space, air and noise pollution and temperature in Tehran using landscape metrics approach. For this purpose, the green space map was prepared and updated and then landscape metrics were calculated. Then, through interpolated of annual mean data, the air and noise pollution maps were extracted, while the temperature map was prepared by the regression method. Finally, the required information from the prepared maps was extracted for 52 study units and was analyzed using structural equations modelling. The results indicated green space has a decreasing effect on air and noise pollution and temperature. As per unit increase in standard deviation of green space, 0.509 units in the standard deviation of temperature, 0.462 units in the standard deviation of noise pollution and also 0.831 units in the standard deviation of air pollution decrease were observed. For green space construct, the indices of cohesion and patch density had the highest role and the area index had the lowest role in decreasing air and noise pollution and temperature. The highest and lowest amounts of green space construct effect on the air pollution were related to particles less than 2.5 microns and sulfur dioxide, respectively. The Cronbach's Alpha value was 0.807 and the Composite Reliability coefficient of 0.808 indicates high reliability and Average Variance Extracted of 0.523 represents a high convergence validity in the air pollution constructs. In the green space construct, the variance inflation factor value indicates a noncollinearity error.