Document Type : Research Paper

Authors

1 Associate Professor, Geography, Payame Noor University(PNU), P.OBox, 19395-4697, Tehran, Iran

2 Associate Professor of Geography, Payame Noor University, Tehran, Iran

3 M.Sc. in Climatology, Payame Noor University(PNU)

Abstract

Extended Abstract
Introduction:
Due to the kind of its usage in a relatively long period, the analysis of temperature levels of modern cities is among the most important subjects that can be considered in the field of geography and environment, and its results can be used in promoting the science and solving the problems of today’s societies. The effect of temperature on climate, is one of the crucial indexes of this procedure, especially in metropolises. The rise in the land surface temperature, which is an indicator of the heat intensity, is among the important elements for identifying theweather changes. The emergence of heat in cities is one of the most known forms of such changes. Urban heat islands are indicated by a temperature inversion and annoying temperatures throughout winters and summers. The temperature of some cities or urban areas has remarkably grown compared to the suburbs or rural areas around them. This phenomenon, called urban heat island, has caused numerous problems.
The term “heat island” was proposed by Havard for the first time almost a century ago in 1833 (Sook, 2004: 10). Afterward, numerous studies were carried out in the large and industrialized cities of the world, whoseresults demonstrated that civilization has exerted significant changes in the meteorological parameters and properties of the ground surface, and consequently, remarkable variations in local climate (Mousavi Baygi et al., 2012: 36).
 
Research objectives:
The present research is aimed at identifying the places with high heat, which have created the known thermal patterns in theArakcity in Iran. Assessment of the spatial-temporal variations of the urban heat islands can be used as a critical component in the management strategies of natural resources and environmental changes, whose results can be useful for environmental, regional, and urban planners.
 
Methodology:
The studied area, Arak, is the capital of the Markazi Province in Iran, with an area of 304.8 km2 at 1755 m above mean sea level. The city has temperate weather tending to cold and semi-arid. According to enactment in 2011, Arak has five municipal districts.
 
The research method was analytical-statistical, and an effort was made to evaluate the relationship between land surface temperature and land cover of the city.
In order to evaluate the development of hot places in Arak and determine its urban thermal patterns and heat islands in the long term, the data of the satellite images of the Landsat scanners 4, 5, 7, and 8, including the data of the TM scanners of Landsat’s 4 and 5, Landsat 7 (+ETM), and Landsat 8 (OLI/TIRS), during the period 1985-2017 were used. These images include two sets of reflective spectral and thermal bands. The thermal bands were used to identify the surface temperature and thermal islands, and the reflective bands were employed to apply the indexes of image processing. The data of the TM, +ETM, and OLI/TIRS scanners were provided in the bands 6, 8, and 11, respectively. The data of the thermal band 6 of Landsats 5 and 7 with wavelengths of 10.40-12.5 micrometers and the band 10 of Landsat 8 with wavelengths of 10.60-11.19 micrometers were used to calculate the surface temperature distribution patterns of Arak. The bands 3 and 4 of Landsats 5 and 7, along with bands 4 and 5 of Landsat 8, were also utilized to calculate the NDVI index (NASA, 2014). In the global imaging system, the images of the Arak areaexist in the 165th And 36th row.
Generally, the following steps were taken to analyze the urban heat islands of Arak:

Calculation of LST and spectral radiance
Conversion of the calculated radiation to Kelvin temperature
Calculation of the temperature levels of five districts of Arak
Calculation of the density percentage of the fourth level of temperature (hot points of the city)
The minimum, maximum, and average temperatures of Arak
Calculation of normalized difference vegetation index (NDVI)
Calculation of the urban thermal field variance index (UTFVI)

 
Results and discussion
Evaluation of the land surface temperature changes and patterns
The analysis of the vegetation variations demonstrated that depending on different uses of urban lands, vegetation is in accordance with the temperature level. Generally, the low temperature in the southwest of the city, which was observed in the land surface temperature maps, is caused by the gardens of Senejan and Karahroud cities. The eastern and southeastern parts of district 1, which has industrial uses, streets with heavy traffic, and accumulation of uses, and the north of the city, i.e., the north of district 3 with the accumulation of residential uses and heavy traffics, have higher temperatures. Generally, during the study period on vegetation, all areas having this usehad considerable changes, except for the northwestern part. Most of the vegetation in the study period was concentrated in districts 4 and 5, which included the gardens of Senejan and Karahroud. However, other parts of the city, including the northwest and, to some extent, the city center and district 1, whose vegetation includes several parks and green spaces, show decreasing changes in temperature.
Based on the results obtained from evaluating the urban thermal field variance index (UTFV) of Arak, using 20 land surface temperature (LST) maps and normalized difference vegetation index (NDVI), obtained from Landsat satellite, (TM), (ETM+), (OLI/TRS), the very hot temperature level of Arak was widely observed in the north, northeast, east, and southeast of district 1, north and northwest of district 3, west and southwest of district 2, and west ofdistrict 5.
 
Conclusions
The evaluation of the LST maps to identify the hot points and urban thermal patterns revealed that most of the hot points are located in the areas with idle lands in the suburbs. These lands are mostly observed in the recently developed areas of the suburbs, including districts 1 and 3. Inside the city, most of the hot places conform to the formation of thermal patterns close to industrial towns, streets with heavy traffic and high pollution, and residential areas with dense and urban decay.
The largest area of the third temperature level is observed in district 1 due to the presence of industrial towns, dense residential towns, cultural and governmental organizations, heavy traffics in the streets, the northern and southern belts in the district, and idle lands in the north and east of the district. The presence of the industrial towns and factories in the city of Arak, especially in district 1, is one of the effective factors in increasing the heat and creating thermal patterns. The thermal patterns in district 1 had the highest intensity in 1988/09/08 and 2017/01/08 during the study period.

Keywords

1- حجازی­ زاده، پروین؛ زهرا، نادر (1388). بررسی تغییرات دما و بارش تهران طی نیم قرن اخیر. پژوهش ­های بوم ­شناسی شهری، سال اول، شماره 1، صص56-43.
2- حلبیان، کیخسروی کیانی؛ امیرحسین، محمدصادق  (1395). واکاوی وردش ­های مکانی دما در حوضه زاینده­ رود به کمک سنجنده مودیس. پژوهش ­های جغرافیای طبیعی، دوره 48. شماره 3: (پیاپی 97). صص 411-399.
3- سلطانی، زهرا (1395). شناسایی و تحلیل جزیره حرارتی در شهر شیراز با استفاده از فناوری سنجش ­ازدور. دانشگاه پیام نور مرکز اصفهان، پایان­ نامه ارشد.
4- صادقی­ نیا، علیجانی، ضیائیان؛ علی، بهلول، پرویز(1391). تحلیل فضایی - زمانی جزیره حرارتی کلان ­شهر تهران با استفاده از سنجش­ازدور و سیستم اطلاعات جغرافیایی. جغرافیا و مخاطرات محیطی، شماره 4:  صص 17-1.
5- علوی­ پناه، سیدکاظم (1382). کاربرد سنجش ­ازدور در علوم زمین (علوم خاک). انتشارات دانشگاه تهران، تهران، ص170.
6- علیجانی، بهلول (1396). محاسبه شدت جزیره حرارتی براساس هندسه شهری موردمطالعه: محله کوچه ­باغ شهر تبریز، نشریه تحلیل فضایی مخاطرات محیطی، سال چهارم، شماره 3:  صص112-99.
7- مرادی، مهربان ­ساعی، سرکارگر­اردکانی؛ فرزاد،  رضا، علی (1393). پایش دمای سطح زمین (LST) با استفاده از تصویربرداری MODIS (مطالعه موردی استان تهران). همایش ژئوماتیک ژئوماتیک 1393، تهران.
8- موسوی بایگی، اشرف، فرید حسینی، میان ­آبادی؛ محمد، بتول، علیرضا، آمنه.، (1391). بررسی جزیره حرارتی شهر مشهد با استفاده از تصاویر ماهواره ­ای و نظریه فرکتال. مجله جغرافیا و مخاطرات محیطی، شماره 1: صص 49-35.
9- نقیب­ زاده، رویا.، (1398). تحلیل تغییرات مکانی- زمانی الگوهای حرارتی شهر اراک با پردازش تصاویر ماهواره ­ای، پایان­ نامه کارشناسی ارشد رشته اقلیم­ شناسی، به راهنمایی دکتر امیرحسین حلبیان و مشاوره دکتر نادر پروین، دانشگاه پیام­ نور مرکز سقز، ص 175.
10-  Chakraborty, T.; Lee, X., (2019). A simplified urban-extent algorithm to characterize surface urban heat islands on a global scale and examine vegetation control on their spatiotemporal variability. International Journal of Applied Earth Observation and Geoinformation. Vol. 74: 269–280.
11- Chakraborty, T.; Sarangi, C.; Tripathi, S.N., (2017). Understanding Diurnality and Inter-Seasonality of a Sub-tropical Urban Heat Island. Boundary-Layer Meteorology, NO 2. Vol. 163: 287–309. 
12- Cracknell, A.P., (1997). The Advanced Very High Resolution Radiometer (AVHRR). Geological Magazine, Vol. 134: pp. 877 - 883
13- Huang, Q.; Lu, Y., (2015). The Effect of Urban Heat Island on Climate Warming in the Yangtze River Delta Urban Agglomeration in China. International Journal of Environmental Research and Public Health, NO 8. Vol. 12: PP. 8773–8789. 
14- Laosuwan, T.; Sangpradit, S., (2012). Urban heat island monitoring and analysis by using integration of satellite data and knowledge based method. International. Journal of Development and sustainability online. NO 1. Vol. 2: PP. 99-110.
15- Liu, L.; Zhang, Y., (2011). Urban Heat Island Analysis Using the Landsat TM Data and ASTER Data: A Case Study in Hong Kong. Remote sensing. NO.3. Vol.7. PP. 1535-1552.
16- Moran. M.S.; Clarke, T.R.; Inoue. Y.; Vidal, A., (1994). Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sensing of Environment. . NO 3. Vol. 49: PP. 246-263.
17- Prasoon Singh.; Barath Mahadevan.; Arindam Datta.; Vinay Shankar Prasad Sinha.; Neha Pahuja., (2017). Heat Island Effect in an Industrial Cluster – Identification, Mitigation and Adaptation. The Energy and Resources Institute (TERI). New Delhi. India.
18- Sin. H.T.; Chan N.W., (2004). The urban heat island phenomenon in Penang Island: Some observations during the wet and dry season. Bangui world Conference on Environmental Management; Facing Changing Conditions. September. 2004; Bangui, Malaysia; NO 1. Vol. 2: PP. 504-516.
19- Solecki, W.D.; Rosenzweig, C.; Parshall, L.; Pope, G.; Clark, M.; Cox, J.; Wiencke, M., (2005). Mitigation of the heat island effect in urban New Jersey. Global Environmental Change Part B: Environmental Hazards, NO 6. Vol. 1: PP. 39–49.
20- Song, Y.; Wu, C., (2016). Examining the impact of urban biophysical composition and neighboring environment on surface urban heat island effect. Advances in Space Research, NO 1. Vol. 57: PP. 96-109.
21- Theeuwes, N. E.; Steeneveld, G.J.; Ronda, R.J.; Holtslag, A.A.M., (2017). A diagnostic equation for the daily maximum urban heat island effect for cities in northwestern Europe. International Journal of Climatology, NO 1. Vol. 37: 443–454.
22- United States Environmental Protection Agency (2008). Reducing urban heat islands: Compendium of strategies (Report). PP. 7–12.
23- Walawender, J.P.; Szymanowaki, M.; Hajto, M.J.; Bokwa, A., (2014). Land Sur-face Temperature Patterns in the Urban Agglomeration of Krakow (Poland) De-rived from Landsat-7/ETM+ Data. Pure Appl. Geophys. NO 6. Vol. 171: PP. 913-940.
24- Yang, H.; Xi, C.; Zhao, X.; Mao, P.; Wang, Z.; Shi, Y.; He, T.; Li Z., (2020). Measuring the Urban Land Surface Temperature Variations Under Zhengzhou City Expansion Using Landsat-Like Data. Remote Sensing. Vol. 12 : 801-828.
25- Yuan, F.; Bauer, M.E., (2007). Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery; Remote Sensing of Environment; RSE. NO 3. Vol. 106: PP. 375-386.
26- http://archive.mrud.ir