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        1 - Spatio-temporal Assessment of Climatic Comfort in Hamedan Province Using Physiologically Equivalent Temperature (PET) and Nervous Stress Indices
        Mohammad Ghasem Torkashvand
        Abstract Climate conditions is one of the most important and affecting factors on different aspects of life, especially the health and human comfort. In this study, using bioclimatic and Tourism indices including; Physiological Equivalent Temperature (PET) and Nervous S More
        Abstract Climate conditions is one of the most important and affecting factors on different aspects of life, especially the health and human comfort. In this study, using bioclimatic and Tourism indices including; Physiological Equivalent Temperature (PET) and Nervous Stress, climatic comfort of Hamedan province is evaluated. For each of the indicators, were used climatic parameters of the 9 meteorological stations in the province in 14-year period (2014- 2001). Then, different areas of the province have been evaluated in terms of above bioclimatic indices. The results show that different areas of the province have a large variety of climatic comfort during the year. Based on PET, in May (Malayer, Nahavand, Tuyserkan, Razan, Ghahavand and Famenin Stations), in September (Hamadan station) and in October (Asadabad, Famenin and Ghahavand) are under optimum climate conditions, and "non stress". Also, based on the Nervous Stress index; in June, Hamedan and Famenin stations and in July, all stations are in "warm and comfortable" condition. In August; Hamedan, Malayer, Nahavand and Razan stations are in "Comfortable" and the rest of the stations are in "warm and comfortable". In September; all stations are in the "cool" condition. In general, according to the above indicators examined in terms of climatic comfort, the best time in the province are May, September and October respectively. However, based on Nervous Stress index, comfort conditions provides only in August. During this period, in addition to the optimal climatic comfort, natural beauty across the province is also very favorable. Manuscript profile
      • Open Access Article

        2 - Detection of Heat Islands over Arak City Based on Spatial Autocorrelation Analysis
        Mohammad Ghasem Torkashvand
        The assessment of urban heat islands is considered as a key variable in the studies of environmental sciences because modeling the interactions of the land surface flux can best respond to many urban problems of modern societies. This study aimed to detect heat islands More
        The assessment of urban heat islands is considered as a key variable in the studies of environmental sciences because modeling the interactions of the land surface flux can best respond to many urban problems of modern societies. This study aimed to detect heat islands over Arak city and their clustering was done. For this purpose, the satellite images of Landsat 8 (OLI and TIRS) related to August for three consecutive years 2013, 2014 and 2015 were taken from the United States Geological Survey (USGS) Site. For the extraction of Urban Heat Islands (UHI) values of Land Surface Temperatures (LST), Moran's autocorrelation functions and hot spot analyses by MATLAB and Arc GIS capabilities were used. After land surface temperature (LST) calculation, hot and cold clusters of heat islands over Arak were extracted using the hot spot analysis index. To evaluate the factors affecting on the formation and clustering of heat islands in Arak NDVI and NDBI indices were used. The results showed that there is a high correlation between the two parameters, vegetation and urban built areas with land surface temperature so that the vegetation index has moderated and urban built areas has exacerbated the heat islands over Arak city. Comparative assessment of urban heat islands led to the detection of two types of heat islands over Arak: Focal heat islands and the linear heat islands. Moran's spatial autocorrelation analysis revealed that the land surface temperature has spatial structure in Arak; in other words, land surface temperature is distributed in clusters in Arak. Finally, analysis of hot spots is a clear confirmation on focus and clustering of heat islands over Arak by increasing the time period. Manuscript profile