Climate is one of the most important factors affecting human life from past to present. Climate has a huge impact on people's daily lifestyles (Thompson and Perry 1997). There is a strong relationship between the distribution of the earth surface, people's food and clothing preferences, shelter needs, and urban climate, which has an important role in the development of human character, and bioclimatic comfort (Insaf et al. 2013; Kim et al. 2017). Characteristic climatic events such as urban climate and urban heat island that occur in cities create different physical and psychological environments for those living in cities. Urban climate can increase thermal stress of urban residents, especially during summer (during heat waves), while it reduce thermal stress in winter (Gulyás et al., 2006).
Fossil fuel use, population growth, urbanization, wrong land use, unconscious disposal of wastes in nature and deforestation have brought many environmental problems, especially global warming. Global warming caused by climate change has negative effects on many factors such as ecosystems, living beings and water resources (Mansuroglu et. al. 2021). Heat stress, excessive precipitation, inland and coastal floods, landslides, air pollution, drought and water scarcity are the biggest threats to urban areas (IPCC, 2014). High temperature, poor air quality and strong wind caused by climate change can cause heatstroke, shortness of breath and injuries, respectively (Karakounos et al., 2018).
In recent years, urban climate studies have been given great importance in order to reveal the effects of climate factor on cities and people living in cities and the dimensions of global warming. Urban climate studies cover a wide range of research categories, including the evaluation of thermal comfort with the aim of improving urban sustainability. Actually, there is an increasing interest in this issue due to the fact that more than half of the world's population lives in cities and the percentage of urban population is increasing (Ichim and Sfîcă, 2020).
The most commonly used concept within the scope of urban climate studies is the concept of bioclimatic comfort. The concept of bioclimatic comfort is defined as the conditions in which people adapt to their environment by spending the least energy (Cetin et al. 2010; Cetin et al. 2018). Although there are great differences between climate parameters, air temperature, air humidity, air wind and short-long wave radiations constitute the most important components of bioclimatic comfort. These components are an important factor in people's physiological state and health.
According to Olgyay (2015); while ideal bioclimatic comfort values vary between 21-27.5°C in terms of temperature parameter and 30-65% in terms of relative humidity parameter, this value is known as 5 m/sec for wind speed parameter. In a study on Turkey; It has been found that ideal temperature values should be between 16.7°C and 24.7°C in order to provide a comfortable environment for people in terms of climate. It has been emphasized that in determining the comfort zone, the wind speed below 6 m/s and the relative humidity value between 30% and 70% should be taken into account, as well as the temperature values (Güçlü, 2008). According to recent studies; The temperature range for bioclimatic comfort in Turkey has been determined between 17.0 and 24.9°C, and this perceived temperature range is located in the middle latitudes (Sen and Genc, 2017; Yucedag et al. 2019).
Meteorological parameters have an important role in guiding urban studies in the fields of landscape architecture, landscape management, landscape planning, landscape design and city planning. People can choose new residential areas by using bioclimatic maps and provide a comfortable environment suitable for them at comfortable temperature values (Cetin et. al., 2018). These maps provide invaluable reference information in urban and rural planning, ecological and economic decision making, land use planning, recreation and tourism planning studies. Considering the dimensions of urbanization, such maps can provide important clues in determining the most suitable places for recreation and residential areas (Olgyay 2015; Topay and Parladir 2015).
Svensson et al. (2003) used the PET index based on meteorological methods to determine the relationship between bioclimatic comfort zones and land use areas in Gothenburg, Sweden. According to the findings obtained from this study; It has been determined that the problem affecting bioclimatic comfort in Scandinavia is the wind speed and wind chill. The highest PET values in the study area were found in central residential areas, while the lowest PET values were determined in coastal and green areas. Emmanuel (2005) examined the relationship between residential areas and thermal comfort conditions determined based on THI and RSI (Relative Strain Index) in Sri Lanka. The findings of the researcher showed that climatic sensitivity is taken into account in urban design for tropical areas. Toy et. al (2007) used THI to determine the relationship between rural, urban and urban forest areas and bioclimatic conditions in Erzurum, Turkey. According to the researcher; It has been determined that the most suitable areas for human comfort in Erzurum conditions are the urban forest and the urban area followed by the rural areas throughout the entire period.
Kantor and Unger (2010), in their study on the suitability of resting places in urban areas in terms of thermal comfort, revealed the relationship between the thermal conditions determined based on PET and the land use model. The study emphasized that it would be easy to calibrate the area model, to calculate the comfort indices from the measured meteorological parameters, or to simulate the thermal conditions of the investigated area with the use of ENVI-Ray or RayMan software. Danisvar et al. (2013) evaluated bioclimatic comfort conditions in Iran based on PET method. The study concluded that bioclimatic comfort conditions in the country occur mostly in spring, the researcher emphasized that areas with an altitude between 1000 and 2000 m have better conditions. Ahmadi and Ahmadi (2017) obtained thermal comfort maps by using meteorological parameters of 43 meteorological stations of Iran between 1970-2013. Researchers have demonstrated bioclimatic comfort mapping (BCM) of the study area based on bioclimatic indices such as Temperature Humidity Index (THI), Effective Temperature (ET) and Relative Strain Index (RSI). According to the results of the researchers; Thermal comfort in the northern and western half of Iran is higher than in the southern and eastern parts of the country. The ET and THI results divided the whole country into six regions, ranging from regions with thermal comfort deficiency to regions with thermal comfort conditions. The study concluded that there are no thermal comfort conditions for most of the year in the middle and southeastern regions of the country as well as the southern part of it. In the study by Vinogradova (2020), UTCI was applied to evaluate the bioclimatic situation in Russia. According to the results obtained by the researcher; It has been determined that all cold stress and all heat stress categories are observed in Russia, but cold stress conditions are more dominant. In summer, heat stress and uncomfortable conditions were observed in most of Russia. In most of the country, the maximum UTCI values for the study period corresponded to mild and strong heat stress. Cetin and Sevik (2020) investigated the relationship between land use and bioclimatic comfort zones determined based on PET index in Trabzon province using GIS and prolonging sensing technologies. Bioclimatic comfort maps produced for the years 1985, 1994, 2005 and 2018 and CORINE land use maps belonging to the same years were evaluated together. In the study conducted by Gungor et al. (2021), The bioclimatic comfort areas of Mersin city center between 1972 and 2018 were revealed depending on the PET index. Meteorological parameters such as surface and air temperature, wind speed and relative humidity were taken into account in PET calculations. According to the results of the study; As a city station, PET values increased in areas close to water in Mersin, while a decreasing trend was observed in rural areas.
This study aims to reveal the relationship between bioclimatic comfort zones determined based on environmental climate parameters (ECP) and bioclimatic indices (PET, THI, UTCI,) and land use changes in Sivas province. In the study, meteorological data of Sivas province for the years 1990 and 2018 and the CORINE land cover data of the relevant years were used.