جستجوی مقالات مرتبط با کلیدواژه « heat island » در نشریات گروه « جغرافیا »

Land surface temperature (LST) is one of the important parameters in the study of climate change and physical processes of the earth's surface. Rising land temperature causes the phenomenon of heat islands, which is caused by changes in land-use and land cover in urban areas and today has become a major environmental concern. Ahvaz metropolis, as the capital of Khuzestan province in southwestern Iran, has undergone many changes in land-use and land cover in recent years and has enjoyed significant population growth. In recent years, the pattern of unbalanced urban development in Ahvaz has led to the destruction of agricultural lands, vegetation and gardens around the city as one of the most important factors balancing the land surface temperature. This has led to an increase in land surface temperature and the formation of heat islands. The purpose of this study is to investigate land-use changes in Ahvaz and its effects on spatio-temporal patterns of land surface temperature and heat islands in the years 2002-2021.

First, the land-use changes were studied and then, in order to evaluate the relationship between the changes in each Land-use and the land surface temperature, the maximum temperature in each land-use was determined and then the amount of changes was investigated. Landsat 7 ETM+ (2002) and Landsat 8 OLI/TIRS (2013/2020) images downloaded from the USGS. Object-oriented method was used for classification. Educational samples were implemented on the image surface and their corresponding objects were selected as educational samples for each class. The classification was done by SVM algorithm and the user maps were classified into four classes including vegetation, barren areas, constructed areas and water areas. In this study, estimating the LST was performed base on separate window Algorithm and with Landsat 7 ETM+ band 6 and Landsat 8 OLI/TIRS band 11 data. In this Study, LST was estimated using Split-Window (SW) algorithm on Landsat-7 ETM+ and Landsat-8 OLI/TIRS Thermal Infrared (TIR) bands. Then the NDVI values, Vegetation Proportion and Radiated Power were obtained. Finally, The LST value was extracted based on degrees Celsius. In this study, Pearson correlation coefficient was used to investigate the relationship between LST and air temperature. RMSE values was used to compare the estimated temperature by SW algorithm and the measured temperature by Field research. Also, two indices UHII and UHIII were used to calculate the intensity of heat islands. These indices evaluate the LST using the values of vegetation in one area.

According to the results of this study, Kappa coefficients and overall accuracy were 74% and 76% for year 2002 map, 78% and 85% for year 2013 map and 88% and 93% for year 2020 map, respectively. The area of built-up and barren areas has increased and the area of vegetation and water areas has decreased. The rate of increase in land-use of the constructed areas from 2002 to 2020 was about 579.69 hectares and the decrease in vegetation cover was 3200.15 hectares. The barren areas have increased by 2521.66 hectares from 2002 to 2020. Pearson correlation coefficient between air temperature and LST values of 0.65% is obtained, which shows a positive correlation. The RMSe values in comparison with LST and measured temperature by Field research for the images of 2002, 2013 and 2020 was 1.79, 1.66 and 0.98 degrees, respectively. According to the results, the LST values in year 2002 fluctuated about 24.48-42.55, in year 2013 about 26.32-44.47 and in year 2020 about 28.13-46.65 degrees Celsius. The results of LST show an increasing trend of temperature during the period 2020-2020. After estimating the LST, the maximum temperature of each user was determined, which showed the increasing trend of temperature in all applications. The decreasing trend of vegetation has a direct effect on increasing LST in this land-use. The temperature of this land-use has increased by 6.32 degrees in 2002-2020. Over a period of 18 years, the LST in built-up areas and barren areas has increased by 4.10 and 5.26 degrees, respectively. In order to study the spatio-temporal patterns of LST and heat islands, first with NDVI index, vegetation status in each year was divided into three classes of low, medium and high vegetation and then LST values in each category were determined. According to the results, the highest temperature occurred in the floor with low vegetation. The correlation between the two variables LST and NDVI was significant and regression between them showed an inverse correlation that indicated a negative relationship between LST and vegetation. Therefore, vegetation plays an important role in reducing the intensity of the heat island. UHIII index values in the low vegetation class from 0.63 to 0.67, in the medium vegetation class from 0.57 to 0.61 and in the high vegetation class from 0.51 to 0.54 it is arrived. The highest intensity of heat islands in 2002, 2013 and 2020 were in the southern, eastern and northwestern parts of the city, respectively.

According to the research results, land-use changes in the study period have caused an increase in land surface temperature. The highest temperatures have occurred in built-up areas and barren areas; this is due to the increase in the area of built-up and barren areas. Decreased vegetation has a direct effect on increasing LST in this land-use. The NDVI, UHII, UHIII indices and LST values were used to study the spatio-temporal patterns of land surface temperature and heat islands. The results indicate high temperatures in the vegetation with low vegetation. Due to the correlation of NDVI values with land surface temperature and the intensity of heat islands, the necessity and importance of vegetation protection as a very important variable to regulate the air temperature in the city is essential.

Replacing natural vegetation cover with impermeable urban surfaces) stone, cement, metal, etc.) has resulted in increased land surface temperature which is considered to be the most important problem of urban areas. Distinct temperature difference between the city and the surrounding areas is called heat island (Melkpour et al., 2018). Increased land surface temperature and resulting heat islands in urban areas built without proper preplanning (Khakpour et al., 2016) especially in developing countries such as Iran experiencing a rapid growth rate have resulted in widespread environmental problems. Heat islands mainly occur due to the presence of man-made surfaces which prevent the reflection of sunlight and result in temperature increase. In general, urban heat islands result in increased air and land surface temperature and thermal inversion (Gartland, 2012).

The present study applies a statistical-analytical research method based upon statistical data received from meteorological stations and extracted from satellite images. Climatic data recorded from 1976 to 2020 in Yazd Meteorological Station were retrieved from the General Meteorological Department of Yazd Province and used to measure temperature changes. Urban climate studies mainly take advantage of long-term patterns and thus, the present study has applied the common Man-Kendall method to measure the trend of temperature changes in warm season (July, August, and September). Also, satellite images collected by Landsat 4-8 in a 33-year period, including four statistical periods with a time interval of 11 years (the average recorded in July, August and September of 1987, 1998, 2009 and 2020), have been used to extract heat islands of Yazd city in warm seasons. These images collected under clear weather conditions were retrieved from the United States Geological Survey website (http://glovis.usgs.gov/) in the WGS-1984 UTM image system. NDVI index was used to investigate the vegetation cover. Main land uses discussed in the present study included barren lands, urban areas, vegetation cover and roads. Sample land uses were collected from Google Earth and visually interpreted in ArcMap. Maximum likelihood algorithm was used for the classification process. Finally, Land Surface Temperature was extracted from satellite images and compared with air temperature trend using the Mann-Kendall test.

Results indicate that due to thicker vegetation cover in summer, there has been a negative relationship between the vegetation cover and land surface temperature. In other words, land surface temperature has increased with decreased vegetation cover and vice versa. Types of land use identified in satellite images collected from Yazd city have showed that the city has experienced a widespread physical expansion during the 33-year statistical period regardless of the season under investigation and thus, built-up urban land use class has expanded significantly. As a result, vegetation cover has experienced a negative trend and decreased. Land surface temperature extracted from thermal images of Yazd city has proved parts of northwest and south of the city to be the core of its heat islands. This is due to the presence of barren lands, lack of evapotranspiration mechanisms, high heat absorption capacity and low conduction capacity. Man-Kendall test has found a significant increasing trend for temperature especially in recent years in which the temperature has increased about 2.3 °C. This is most possibly due to the increasing trend of urban population in recent decades, followed by increased residential structures and resulting heat island phenomenon.

In general, classification of urban land use types in Yazd has shown a significant physical expansion of the city during the statistical period. This physical development has occurred in all directions; beginning from the central and northeast-southeast parts, and moving towards northwest-southwest parts. Maximum NDVI was observed in a strip along the central part of Yazd in which vegetation cover is thicker. Green spaces are also observed in some areas of the city. Color spectrum of the LST map has shown relative changes of the ambient temperature in various parts of the city. High and very high temperature (between 41.5 and 50 °C) show the location of the heat islands on LST maps. Also, areas with a deep red color and a temperature above 50 °C have formed hot clusters formed or strengthened between 2009 and 2020 in the west and southwest parts of the city. Satellite images and related graphs have showed that in 2020, Yazd have witnessed a sharp increase in temperature and a heat island.  Temperature data of Yazd Meteorological Station and Man-Kendall test have shown a significant increasing trend (about 2.3°C), especially in recent years. These are related to the urban population growth in recent decades, followed by increased urban structures (residential-commercial) and heat island phenomenon.

Rising temperatures in cities are one of the effects of direct human intervention. The thermal island of the city is due to the characteristics of urban planning, air pollution, human heat, and the existence of impermeable surfaces in the city. In the meantime, recognizing the effects of heat islands on the psyche of people is very important. The purpose of this study is to study and identify the heat islands of Ahvaz according to the pattern of air pollution.

This research is applied in terms of purpose and in terms of descriptive-analytical methodology based on spatial studies approach and analysis of satellite images. To identify and analyze the heat islands of Ahvaz, satellite images were used during 5 periods from 2001 to 2017 and processed using software (ENVI). Also, data related to the air pollution index (AQI) in the city of Ahvaz was used in a period of 7 years from 2010 to 2017. In order to identify the areas with the most pollution, the network analysis process (Network Analyst) has been used in the ArcGIS environment.

The results of this study show that southwest of Ahvaz Due to the multiplicity of polluting centers such as oil and gas refining centers and industrial towns, the pollution center of this city is considered. The results of the questionnaire analysis also show that the Heat tolerance threshold in the city of Ahvaz in the first place reduces the increase in stress and daily pressure in people and then reduces happiness and freedom and reduces the feeling of life satisfaction will follow.

The expansion of urbanization and the development of urban lands towards orchards and agricultural farms is one of the biggest problems of the country's major cities, and in recent years, this development, along with reduced water resources and a sharp increase in population, has led to the development of urban heat and metropolitan heating. In this study, by examining the situation of the heat island of Isfahan and its surroundings, as well as changes in green spaces and gardens adjacent to the city of Isfahan, the relationship between these two variables was evaluated. The research method is descriptive and correlational and the purpose of this study is to investigate the role of tourism development of garden houses around the city of Isfahan and its role in reducing the effects of the heat island of Isfahan. The results of this study showed that in recent years the temperature of Isfahan and its surroundings has increased between 2.5 to 4 degrees Celsius and this increase has coincided with the development of Isfahan and the destruction of gardens around the city.

The expansion of urbanization and the increase of population in metropolises and the growth ofindustrial activities of cities, It has caused changes in urban area climate. One result of these changesis the city's heat islands. The city of Mashhad has also grown rapidly in recent years. This studyinvestigates the heat/cold island of Mashhad metropolis based on the background climate in order toidentify its spatiotemporal behavior. For this purpose The MODIS Terra and Aqua land surfacetemperature (LST) data were obtained and the heat island was examined accordingly. A new wasused to measure the heat island. In this method, Modis land use data was used to determine the urbanand suburban boundaries as well as to determine the land use type of the study area. The backgroundclimate was determined based on Far-side temperature and the representative non urban area wasselected based on the most frequent temperature and the heat island was calculated. Survey ofheat/cold island in the daily period showed that during the day the average temperature of city islower than non urbun temperature and at night is higher. Also the seasonal survey of heat island/couldisland of Mashhad metropolitan shows that daily cold island is the highest during the warm seasonsand lowest in the cold seasons and the seasonal variability of nightly heat island is less than the dailycold island. The core of the daily cold island is located between the Haram and the Shahid FehmidahSquare towards the western area of Mashhad. The day time cold island matches the areas of the citywith high vegetation coverage. The core of the nightly heat island is consistent with the old textureand dense area around the Haram towards the northwest of the city. The heat/cold island intensity isalso directly related to the wind speed. The role of land use in intensifying or reducing the intensity ofthe heat island of Mashhad is well seen. In the development of the city, more attention can be paid tothe use of urban land use in order to moderate the temperature of the city.

One of the consequences of the rapid growth of the cities is the heat islands, where the air temperature of the cities rises sharply in relation to the surrounding areas. Anzali station synoptic statistics were used to detect and detect changes in the Rasht elemental elements over the period 1956 to 2017. The time intervals included mean temperature, mean and maximum temperature, precipitation, humidity, evaporation, sunshine and mean wind speed. the effect The heat island intensity of Rasht city was selected from the atmospheric synoptic models and its effect on climate elements, 6 days of 2010, and ground conditions were investigated with the Jumvord scale. Sunshine and evaporation have had the highest increasing trend at different months of the year as well as the annual trend. During the high-altitude system due to the stability and stability of the island, the intensity of the heat island increases, and this occurs during the low-altitude system and the instability of the air. After comparing climate elements Rasht During the reign of high altitude and low altitude systems in this city, it was found that the climate elements were strongly influenced by these patterns. So that the difference of more than 11.5 ° C in the maximum air temperature between August 5, 2010 and August 22, 2010 Also, the difference of about 29% of humidity on the same day indicates the intensity of Rasht heat island on August 5, 2010 This system is dominated by low altitude.

Urban development and industrial activities have led to dramatic changes in the physical characteristics of the land surface, energy balance and, as a result, local climate change in big cities. To investigate heat/cold island intensity, Modis Terra and Aqua data were used to obtain land surface temperature from 2002 to 2016 and all cities with a population of more than 500,000 were selected. Modis land cover data were used to extract urban and non-urban areas. And so the difference between the maximum and minimum latitude and longitude of the urban area was obtained and on every side, the city was expanded to its size To specify the non-urban area. In the next step, a representative temperature of the non-urban had to be selected from non-urban cells. For this purpose, for each day the temperature that had the highest frequency among all cells of the non-urban was selected as the representative temperature of the non-urban. And the urban heat/cold island intensity was obtained from the difference between the Representative temperature of non-urban and all urban cells. The result shows that at the day in all metropolises except Rasht from a cold island. At night, except Zahedan, which has a weak cold island, in the other city form a heat island.

This study aims to investigate the role of heat island in the process of temperature changes in an urban area of Tehran during 2010 and 2018, equivalent to 1389 and 1397. To evaluate the changes, five points were identified on the map of region 1 and its eight regions. Then the middle month of each season from 2010 and 2018 was selected for review. Landsat 8 satellite data were used to analyze the heat island and the effects of urban construction on the intensification of this phenomenon. The maximum temperature data, normalized vegetation difference index, and ground surface temperature were extracted. This study shows that the level of vegetation in 2018 compared to 2010 has decreased sharply, so that it has caused temperature changes and also the creation of a heat island in recent years in the region. The increase in temperature in the morning and noon is observed in all selected months of the four seasons of the year. At the same time, the amount of increase in minimum temperatures was greater than the maximum temperatures.

Problem statement:

Urbanization and human activities affect the urban climate and clearly affect the air temperature close to the surface. In Tehran and its satellite, factors such as climatic region, season, time of day and wind regimes, topography, urban environments, population density, residentschr('39') activity, vegetation structure and urban physical form play an important role in the formation of urban heat islands. The purpose of this research is to determine the type of spatial distribution of heat islands of Tehran metropolis and satellite cities using land use and land cover. Replacing natural land cover with impervious surfaces due to urban development has negative environmental, social and economic impacts, in addition to beneficial aspects. Most of the albedo belong to the built areas and the bare land and the smallest of the Albedo belong to the aquatic areas and vegetation. In this research, the hypothesis is whether the suburbs may have higher temperatures than urban areas depending on the type of land use? In fact, it is examined the spatial distribution of the heat island of Tehran and its satellites, in which the use of land and land cover are analyzed as a factor contributing to the creation, intensification or reduction of the thermal island.

Extraction and preparation of imagery data through the Landsat 7 Satellite ETM + sensor over the years 2001-2015 and selection of June as the hottest month of the study area. These images were extracted from Route 164 and Row 35 of the USGS. An assessment was carried out through the accuracy of ground surface temperature data by Landsat satellite images and obtained temperatures from the weather stations in the area based on the Taylor diagram. In order to investigate the spatial structure of the cells obtained in each map, each containing surface temperature and heat island extraction, it used the methods of world spatial autocorrelation (high and low clustering, spatial correlation) and local (Cluster and Outlier analysis, hot spot analysis). The high and low clustering statistics show how the concentration of high or low values ​​in the region. In the next step, the results of analysis of Anselin Local Moran and hot spots were compared in map format. Hot spots were analyzed in all studied regions and in all 7 cities. The area of ​​hot spots was investigated over the course of 15 years and the results were presented in table and diagram form.Land use was surveyed for every 7 county. In the last section were studied, the relationship between hot spots in each city and type and land use changes over 15 years.Surface spatial analysis of the surface temperature of the area showed that the cells follow a cluster pattern and their trend towards clustering. Any kind of land cover and land use will create special features in a place that can be increased or decreased with a specific microclimate.

After selecting the years 2001, 2005, 2010, and 2015 as the sample and survey of the temperature of each land use in that year, it was determined that artifact, pasture, bare lands, forest, aquatic areas, agriculture and green spaces were respectively have the highest to the lowest temperature in the area. On the other hand, in the area of heat island in a region are Rabat Karim, Ray, Islamshahr, Tehran, Shahriar, Karaj and Shemiranat, respectively.In spite of the reduction of aquatic areas and even bare lands, because of the large impact of green space or agricultural land was reduced the extent of heat islands during the statistical period, and on the contrary, the reduction of green space and agricultural land in places where even their forest areas have grown, has increased the levels of heat islands. This suggests that the dispersion and extent of green spaces has a more effective role in reducing the heat island compared with the creation of limited forest and planted surfaces in one place. Hence, in Tehran despite the significant growth of artifacts, due to the increasing growth of green space, the heat islands has been reduced compare with the Ray, Robatkarim and Islamshahr cities, which are exactly on its suburbs.

The high spatial and temporal limitations of TIR images for use in urban climatology have been identified as a current scientific challenge. Therefore, the use of Data Fusion Algorithms in Remote Sensing has been considered. In the old methods, two bands of one sensor were used for Data Fusion. In these methods, a panchromatic band was used to increase spatial accuracy, so only spatial resolution was increased. To solve this problem, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was used to integrate the images of two Landsat and Modis gauges to increase the spatial and temporal resolution of the reflection. but, this algorithm is designed for pixels and unmixing areas that are the same in Modis and Landsat pixels. The use of this model was not suitable for urban areas with a different of landuse. Therefore, the Enhanced STARFM model (ESTARFM) was developed. The ESTARFM model was improved in 2014 to predict thermal radiation and LST, taking into account the annual temperature cycle and the unevenness of the earthchr('39')s surface, and the SADFAT model was introduced.
In this study, the performance of SADFAT model in the use of OLI spatial resolution and MODIS temporal resolution in LST forecast in urban areas was examined. The metropolis of Tehran has different surface covers and multiple microclimates. So if the algorithm works successfully, This model can be used in other cities to improve urban heat island studies. The inputs for the algorithm are thermal radiance of Modis and Landsat   images, the red and near infrared band of Landsat for daily production of LST in 2017 in the city of Tehran. The algorithm uses two pairs of Modis and Landsat images at the same time and sets of Modis images at the time of prediction and then calculate the conversion coefficient for relating the thermal radiance change of a mixed pixel at the coarse resolution to that of a fine resolution. In this way, LST is generated in areas with a variety of landuse.
All the estimated pixels were compared to the base image pixels in that range to evaluate the results of the model. The comparison results for the autumn days with the average correlation coefficient of 0.86 and RMSE equal to 0.122, showed that the model has the highest accuracy in this season and in other seasons with the average correlation coefficient of 0.76 and RMSE about 0.4, has provided good accuracy.
Visual interpretation of the results of SADFAT showed that this model is able to accurately predict the LST of the land cover in different surface coatings and even in areas where one or more urban land uses are mixed in one MODIS pixel.
However, the borders are well separated and the features are not combined. Although the boundaries are clearly defined, in some land uses, the predicted LST is somewhat higher than the observational image.
Landsat and Modis satellites pass through an area with a small time difference, so they are suitable for combining with each other. But in predicting reflectance with the SADFAT algorithm, there are systematic and variable errors that we need to be aware of in order to increase the output accuracy. One of the systematic and unavoidable errors is the instability of the Terra and Aqua satellites passing through at any point, ie at each satellite pass, the location of the study area in Swath and the size of the pixel changes. Due to the distance of the study area from the vertical center of measurement on the ground (Nadir), the amount of this error varies on different days and should be checked for each day. The preventable error is the sudden change in one or more images used (16 days of the same pass time interval for Landsat) is high for estimating surface reflectance with spatial and temporal resolution. These changes may be due to human factors such as air pollution or natural factors. Natural factors such as clouds and dust storms are the main sources of error in using the SADFAT model because they are sudden and temporary and cover a wide area. The occurrence of these two factors has a great impact on reflectance. Therefore, a sudden change in these factors, in one or more images, causes a large error in the calculations.
The study also found minor spatial errors in the prediction, so that even on days when the results were better, points were observed where the values ​​in the predicted LST images did not match exactly with the OLI sensor. The reason for this may be due to changes in vegetation. Although there are some systematic and variable errors in the images and the implementation of the algorithm The results of this study showed that the performance of this model is reliable for predicting the daily LST with a spatial resolution of 30 meters in Tehran.
This method is able to support urban planning activities related to climate change in cities, so it is recommended that its performance be examined separately for different land cover in the city and the efficiency of this algorithm be evaluated with other sensors such as Copernicus Sentinels.

The increase in population and the development of urbanization and, consequently, diforested areas have caused an increase in the surface temperature in urban areas, which results in an urban heat island. The heat islands of the city is one of the factors that has become important at the same time with the development of the city and today it can be calculated and evaluated using satellite images. The objectives of this study are to evaluate the points of temperature changes, land use, vegetation, traffic and soil types relationship with surface temperature in Sari and the trend of its spatial changes during the two time periods of 1988 and 2018. For this purpose, TIRS and Landsat 5 and 8 TM images in a period of 30 years (1988-2018) were used to study the heat island changes and calculate the surface temperature with a single-channel algorithm. The results showed that during a period of 30 years with a decrease of 235.3 hectares of green space and a 34% increase in land occupation in Sari, the area of heat islands increased by 21.83%. Also, considering the value of P-value less than 0.05, it showed that there is a significant relationship between vegetation index and city occupation level with land surface temperature and it can be argued that land use change, vegetation and traffic due to population growth and land use change is one of the main factors in increasing spatial changes in the heat islands of Sari.

UHI (Urban Heat Island) describes the phenomenon of temperature change in urban areas than their surroundings such as bare lands, gardens. Its effects are: increasing energy and water consuming, escalation of air pollution and intrusion on thermal welfare (Hashemi et al., 2019). Different researches about UHI, have assessed the effect of one or several factors, mainly land use, on the escalation of surface and sensible temperature. There are many researches about this issue. In one case in Macedonia, Skopje, heat island was assessed by using of NDVI index. The results indicated NDVI index was effective in weakening heat island and NDBI index had positive correlation with surface temperature which shows manmade areas have effects on heat island intensification (Kaplan et al., 2018). RS (remote sensing) makes it possible to assess all aspects of UHI as a hazard through preparing high quality satellite images. GIS (geographical information system) does too by preparing database, uniform methods, analysis and producing maps. The objective of this paper is temporal-spatial analysis of heat island of this hazard to recognize the UHI places in relation to land uses. This analysis helps urban managers to know more about spatial requirements in city and the importance of proper places (green lands and parks) to moderate urban temperature.2. Study Area Urmia city is the central district of Urmia county in the center of west Azerbaijan province in Iran. The city has been located in the distance of 18km from Urmia Lake. The city is located in 37 ºN latitude and 45 ºE longitude. Its climatehas beenaffected by latitude, winds, Urmia Lake, Mediterranean wet climate, Siberian cold air masses, topography, altitude, and the direction of altitudes (Javan, 2013).

In this study Landsat images for August period of 1989, 1998, 2011 and 2018 were used. Preprocessing, atmospheric and radiometric correction were performed for the images. To prepare heat island maps, land surface temperature (LST) was calculated by the threshold limit of NDVI and Plank principle method for TM images and Split Window algorithm for TIRS image. The algorithms were run in ENVI 5/3. LST formula factors for TM images included Brightness Temperature and Land Surface Emissivity (LSE). To calculate LST for TIRS bands, Split Window algorithm was run by using some important factors including brightness temperature, split window coefficient values, mean LSE, difference in LSE and atmospheric water vapor content. Using of NDVI and land-use images, the relationship of LST, vegetation cover and different land uses was analyzed. For assessment of heat island intensity changes in Urmia, the index of heat island proportion was used for the images. See the following: temperature of place       Average surface temperature

According to land use maps, during 29 years from 1989 to 2018, Urmia city has had significant growth and expansion. Change detection results indicated  that about 82%, equal to 2475 hectare of bare lands and 72%, equal to 1833 hectare of surrounding farmlands and gardens of the city have been changed to urban land use and related constructions. Using Zonal statistics in Arc GIS the temperature of land uses was assessed .According to the results in 1989 the green cover had the lowest temperature, and the bare lands had the highest average temperature. In August 2018, the maximum temperature is related to urban areas. On August 2018 some new UHIs have been made which are related to producing and industrial workshops, buildings and bare lands in the north east, east and south east of city. The assessment of UHIs changes process showed the escalation of UHI index in Urmia.

Urban Heat Islands have destructive effects for metropolises and the residents. Urmia as a metropolis has had rapid industrial and population growth in the recent decade. In this research assessments have been done by Landsat images from 1989 to 2018 with four years with temporal distances. The results indicated that in 2018 the area of cold and very cold temperature classes have been decreased. It is because of destroying of large areas of farmlands and gardens and changing to urban land use during studied years. In 1989 and 1998 very high temperature class included bare lands. Passing years and constructing new buildings, industrial and production workshops, new UHIs have been created in east, north east and south east in 2018. The results indicated that during the studied period, according to UHI index results, UHI has been intensified. The UHI index with the amount of 0/2 in 1989, has been reached to 0/37 in 2018. According to these results, in addition to extending of UHI in Urmia, UHI has been intensified. Another research which has been done on UHI in Urmia in July 2015 (Asadi et al., 2019) had the same results of this paper. It proved the effect of industrial and administrative land uses on high temperatures. This research represented the negative relation between LST and green lands and vegetables. Maleki et al. (2018) using synoptic stations information and statistics to assess the UHIs in Urmia and recognized the UHIs in same places like this article. This shows that satellite images have high accuracy and efficiency in analyzing natural or manmade phenomena.

During the life of the planet Earth, there has been a lot of climate change and, currently, indicators show that the climate change has been accelerated due to the human intervention. Expansion of urbanization, reduction of green areas and consumption of more fossil fuels contribute to the generation of heat islands over cities which increases the temperature, as much as several degrees centigrade, therefore making the cities warmer than the surrounding areas. This phenomenon occurs when a large percentage of natural vegetation is destroyed and replaced by buildings, roads and other urban facilities. These are less reflective. They absorb and keep the solar energy and cause the occurrence of heat island phenomenon therefore making a great temperature difference between inside the cities and the surrounding areas. Generally, factors such as natural shape of cities, urban structure, geography, meteorology, size, geometry, population and urban density, thermal properties, vegetation and the used building materials are among the factors influencing occurrence of the heat island phenomenon in cities among which the building materials used in walls of the buildings, requires special attention. Low reflection materials accelerate the occurrence of the heat island phenomenon in cities. Therefore, this article aims to, through understanding the accelerative factors such as reflection, absorption, emission and release of carbon, provide a list of suitable building materials for cities and future buildings in order to reduce the destructive effects of heat islands in cities.

This study was conducted to investigate the microclimate role of extruded builders in the last decade on surface temperature rise and heat island resonance and air pollution in the Tehran area. Shemiranat station data and Aqdasia air pollution measurement data over a 12 year statistical period were used. Landsat 8 satellite images were used to reveal the role of vegetation reduction on surface temperature. The results showed that in area 1 due to non-regular and unconditional construction in recent decades, the vegetation and trees of the area were not cut or standard green space development was not followed. Two hot areas, or islands of high surface temperature heat, are forming and developing over other adjacent parts. The eastern half of Region 1, especially its southeastern part, boasts a very hot part in all seasons. In hot seasons, surface temperatures in the area can reach as high as 50 degrees Celsius. The middle section is still better off if it still manages to maintain its green space. However, due to the steady growth of builders in the last decade, the minimum (morning) temperatures, especially in cold seasons, are rising rapidly and steeply. The amounts of fine-grained particles, especially PM10 and PM2, are increasing in region 1.The intensification of the heat island has caused south-west to south-southeast winds to intensify all months of the year. And it has made the area particularly polluted in the colder months of the year. The purpose of this study was to investigate the role of changes in land use and deforestation and loss of vegetation in changes in surface temperature and heat island of Tehran metropolitan area.

Urban heat island (UHI) is one of the environmental phenomenon which has made difficult environmental conditions for citizen. This study aims to evaluate the spatial and locational variability of Esfahan urban heat island according to the role of land use. Thus an area about 190.2 square kilometers (km2) in Esfahan, as the microclimate, was studied. In order to analyze the relationship between land use and land cover changes on Esfahan urban heat island, the images of Landsat 7 (TM and ETM +) and Landsat 8 (OLI / TIRS) on 20 July 1989, 17 August 2005, 18 August 2014 have been used. The results show that the urban areas has experienced 31% changes in positive direction; while the agricultural sector and green space havehad a reduction of 25% in their area. The analysis of the intensity of heat island show that heated cores are related topoor and barren lands with about 37/33 and 36/5. Although the most area of thermal classwere related to warm thermal class in 1989 and 2005, the average thermal classes were about 63/8%in 2014. Moreover, the locational variation distribution of Esfahan heat island shows that the locationof the heat island has gradually changed. For example in 2014 it included small parts in the south of the city, military zones and barren lands in the south, some parts in the north west and north east areas and small areas in the east of Esfahan. This means that urban development isn’t the main factor of the surface temperature increase and urban heat development, but rather the type of land use has influenced the decreasing or increasing of air temperature.

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One of the main challenges in urban development processes in developing countries is the change that increasingly occurs in heat islands. Their rapid growth has created many problems for urban management and planning processes. The present study aims to reveal heat island changes using Landsat satellite data during the 1991-2016 statistical period. The satellite images have been pre-processed in four stages, including basic processing, extraction of impenetrable educational levels, assessment of the accuracy, assessment of the accuracy of classification, and retrieval of ground temperature. The results of Kappa coefficient accuracy extraction show that the images of 2016 are more accurate with a coefficient of 0.8341. In terms of location, warm cores match arid lands and poor areas that are clustered in the north and south of the city and in vegetation-free areas. Heat islands are also observed in the city center as small thermal wells. Investigation of how heat island intensity is related to the type of land cover reveals a negative correlation between construction density and vegetation on one hand and surface temperature on the other. Therefore, it can be said that humidity and coveredness of the ground the factors that moderate the heat island in the city of Esfahan.

Human activities control the microclimate of the city and one of the most important effects of it is the urban heat island phenomenon. The heat island affects the quality of urban life, including energy consumption, air and water quality, as well as human health. Ahwaz, on the other hand, is one of the hottest cities in Iran. Therefore, the study of the heat island of Ahwaz and the knowledge of urban microclimate is worthy of consideration.e. For this purpose, in this study, the heat island of Ahwaz metropolitan area was investigated in terms of temporal and spatial variations by using the data of temporal temperature data of the MODIS-Terra and MODIS-Aqua observations from 2002 to 2017. The intensity of the heat island was measured based on the background climate. To this end, after the city boundary was determined by the latest Google Earth imagery. Then, a range, of the size of the city, was determined around the city and was called the non-urban. The temperature that was most common among all the non-urban cells was considered as the temperature of the non-urban. The temperature difference of all the non-urban cells of the city was obtained from the non-urban temperature. The average temperature difference of all cells from the temperature of non-urban was obtained and called the average intensity of the heat/cold island. The results showed that Ahwaz, during the day has a cold island (-2 degrees Centigrade), and at night was a heat island (2.2 degrees Centigrade). Due to the fact that the Karun river passes through the city, heat island is divided into two parts. The eastern and western parts of the city have more procedural temperatures than the city average. Also, the core of the nightly heat island and the weak parts of the daily cold island are in line with the industrial zone of Ahwaz.

Introduction and Background: The growth of cities and the increase in the population and the diverse use of urban lands have caused problems for urban communities. One of these is the phenomenon of heat islands, which is the result of an unusual temperature increase of the city relative to the surrounding countryside. This research tries to achieve a general view on the heat island mechanism, air temperature changes and urban temperature changes in parts of Hamadan city by using TIRS (Landsat 8 satellite images) and comparing it with actual ground level data by statistical methods. The temperature difference of different points from satellite images based on the spectral radiance method and the degree of gray value of pixels in the thermal bond was made using the photo of the Planck equation. Based on the relationship between real data on ground surface temperature at the meteorological station and data extracted from satellite images, according to different regression models, the highest determination coefficient was obtained for three linear, quadratic and cubic correlation methods. Among them, the cubic regression method with the least error was meaningful at 95% confidence level. The high explanatory factor (70% and above) indicates that there is an acceptable coordination between satellite image information and weather station information. The maximum difference between the data taken with the actual ground station data is related to the blanket and minimum temperature of 5.5 and the minimum difference of the green area is 0.5°C. The difference in temperature in different parts of the city is more closely related to the minimum temperature. While the temperature difference in areas covered by green space in Hamadan city with real data is higher at maximum temperature. The results showed that the Hamadan heat islands have a direct relationship with the construction and land use. The temperature changes in different parts of the city of Hamedan are indicative of the creation of heat islands in the non-used building and ground areas. The results of this research can be applied in the management and urban planning and land use of Hamedan.

Urban heating is one of the most well-known forms of local manipulation of the climate by mankind, so that changes in the use of land cover in urban areas can lead to an increase in urban temperatures relative to the air temperature in rural areas. This phenomenon has been quantified in the form of the Urban Heat Islands (UHI) and has been studied and recorded for over 150 years in various cities of the world. The effect of the Urban Heat Island refers to an increase in the temperature of each man-made area, with respect to the surrounding surfaces. This phenomenon in urban areas refers to an increase in the temperature of cities with respect to the rural and suburban areas. On the other hand, the heat island directly affects the health of urban wildlife. Each year, in the United States, about 1,000 animals die due to the temperature rise, and more than that are destroyed because of the urban air harmful compounds. These changes in the pattern of winds have very important and dangerous consequences, such as the transmission of air pollution and dispersed toxic particles from cities to the suburbs, to disruption the people’s comfort within the city, which is why the heat islands are now considered as the causes of worrying about people’s health. Moreover, the heat islands change the wind patterns in the cities and surrounding areas. The suburban breeze is a dominant phenomenon in cities that are located on a flat land. The presence of heat islands, in addition to temperature changes, causes changes in land processes such as early flourishing of urban plants and longer growing season.
The present research has been an applied research in terms of targeting and a field-analytical one in terms of data collection. In order to reach the final goal of the research, the meteorological statistics of the synoptic meteorological station of Urmia city was studied first. Then, the study of different regions of the city was done in terms of temperature given the 9 stations set up inside the city and the suburbs. The data of 9 stations set up in the city was adjusted by installing a dry temperature sensor at an altitude of 180 cm, in cooperation with the municipality of Urmia, at a minimum and maximum daily rate of two hours (7:30 am and 5:30 pm) in hourly, daily and monthly forms. It should be noted that, the desired statistical period is from April 21, 2015 to July 22, 2015, and the readout pattern is on a daily basis, and its output is in the form of 1st to 4th of each month (days 7, 15, 22 and 29 of each month).
Result and The rapid growth of urbanization and the increase in the population of Urmia city has caused significant changes in the physical and natural conditions of the city. This increase and expansion of the urbanization trend has affected some of the meteorological quantities in a way that, the performed studies indicate that the minimum temperature of Urmia city during the twenty year period is increasing in all months of the year compared with the neighboring stations. Nevertheless, specifying the limits of the Urmia heat island requires more precise studies. The study of the isothermal map of the average maximum temperature in the months of May, June and July, 2015 indicates that the Velayat-e-Faqih square station with a temperature of 29.41 degrees Celsius accounts for the highest temperature compared with eight other stations and in fact, has formed the center of the heat island. At the same time, the station for the license plate exchange center in the city of Urmia with a maximum temperature of 22.27 Celsius, is the coolest station compared to other stations, indicating a heat difference of 6.64 Celsius in the city. According to the above map, the intensity of the heat island decreases by distancing from center of the city. But the most important result that can be obtained from the above maps is the extension of maximum temperature curve toward parts of the East and South-east. The reasons for the high average temperature at the station of the municipality town and the station of Golman Khane can be summarized as follows: The existence of 90% of industrial uses, workshops and factories at the edge of these stations Wind flow Given that wind is the most effective barrier against the formation of heat islands, the combination of the wind field with the pattern of heat island’s spatial variations shows significant results, which is a sign of the great impact of wind on the quality of formation of the heat island. The wind contributes to the extension of the heat island’s curve through the transfer of suspended particles and gases existing in the urban atmosphere.

Urban climate is strongly influenced by the processes of urban work and life. Expansion of cities and consequently increased human constructions causes to changes in urban climate. The rising temperature of cities rather than the surroundings is one of the effects linked to direct human intervention.
Building heating, air pollution and the use of inappropriate materials in the flooring streets (like asphalt streets due to dark colors in energy-absorption) are effective in phenomenon of urban heat islands that makes unfavorable environment for citizens. Paying attention to the urban surfaces like sidewalk, streets and rooftops has a great role in decreasing effect of this phenomenon. Due to growing urbanization and subsequently cities development, urban heat islands have taken a growing trend in big cities.
In general, the urban heat-island is a result of urbanity features, air pollution, human warmth, presence of impervious surfaces in the city, thermal properties of materials and geometry of urban areas. Heat island phenomenon is a result of many factors that are summarized below: (1) urban Geometry (morphometry) (2) thermal properties of materials which increase the sensible heat storage in the urban texture (3) released human heat as a result of fuel combustion and animal metabolism (4) urban greenhouse gases, leading to an increase in long wave radiation, atmospheric contamination and therefore warmer atmosphere (5) reduction of evaporation levels in cities, which means that energy will be released more as tangible rather than latent heat (6) reduction of turbulence and heat transfer through the streets.
This study aimed to simulate and calculate the maximum amount of heat island (UHI max) according to the conditions of urban geometry in the region of Kucheh bagh in Tabriz that is a pioneer study in Iran.
The study area is located in Kuche bagh region at the intersection of the streets of Ghods and Farvardin in the city of Tabriz.
The Oke’s numerical-theoretical equation was used for this study. First, the geometry of the target area using the radius of 15 meters from the axis of the road was divided into separate blocks. The ratio of street width (W) and height of buildings (H) was calculated in GIS software and at the end, the intensity of UHImax was calculated and simulated using Oke equation.
The urban geometry including building height and street width is calculated using Equation 1.
The theoretical- numerical basis of this equation shows that simulation of H/W ratio is an appropriate ways to describe urban geometry. Increasing the value of this ratio could lead to an increase in urban heat-island through modeling. This model has many advantages compared to other methods used to estimate the urban heat island. So, the selected parameter to calculate urban geometry and the model used to estimate the maximum intensity of heat island is the ratio of H / W and OKE model, respectively. In addition, the average height of buildings located within a radius of 15 meters and an average width of passages were calculated from the equation 2 and 3, respectively.
After calculating the geometry of the study area, the results showed that the blocks E, G and D in terms of height of the buildings have a heterogeneous distribution, but the distribution of blocks C, I and J is illustrative of their standard configuration. Although the blocks E, F and J in terms of street width are less diverse compared to other blocks, but in terms of height of buildings (8.6, 7 and 5 meters) have a different pattern that maximum values of their UHI are 8.3, 7.5 and 6.3 degrees, respectively. Three blocks B, H and I, in addition to their similarity according to street width and height of the buildings, in terms of the ratio of H / W and heat island intensity with the values of 9.6, 9.8 and 10.2 degrees are homogeneous.
It was also found that the greatest difference between the H / W ratio is related to block A (0.54) and block H (1.98); this difference has caused that greatest difference between the maximum intensity of UHI would calculated between the two blocks equal to 5.2 degree.
Misconfiguration causes that energy leaving from city surface deal with the problem due to narrow passages and high buildings. Therefore, consideration appropriate width of passages and streets and height of buildings are necessary to ease heat leaving and reduce intensity of UHI.
These simulations showed that high buildings and narrow streets intensify the heat islands. While in the presence of short buildings and wide streets, the UHI max is lowered. When the ratio H / W in the studied urban area is between 0.54 to 0.81, UHI max remains between 5 to 6.6 C˚, when this ratio increases to 1.01 to 1.98, UHI max will be between 7.5 and 10.2 C˚. The result also revealed that block A and H with 5 and 10.2 C˚ have the minimum and maximum value of UHI intensity, respectively. So can be concluded that block A and H have the most standard and non-standard urban configuration in the region. The estimates from regression model showed that the street width (91.6%) is more effective than the height of the buildings (6.6%) in changing UHI max.