Spatial- Temporal Analysis of Urban Heat- Island of Mashhad City due to Land Use/ Cover Change and Expansion

Document Type : Research article

Authors

1 Professor, Remote Sensing and GIS, Faculty of Geography, University of Tehran, Iran

2 M.A. in Remote Sensing and GIS, Faculty of Geography, University of Tehran, Iran

Abstract

1. Introduction
Increase in the land surface temperature and the formation of heat islands in the metropolis areas has become one of the environmental problems emerged by unplanned expansion of cities. Many factors are involved in the creation of urban heat islands. These factors can generally be divided into two groups of controlled and uncontrolled. In addition, the controllable and uncontrollable factors can be classified as another. The factors with temporary impact such as wind speed and cloud cover, the variables with constant and stable impact such as green space, building materials and sky view and, finally, the factors with periodic or cyclical impact such as solar radiation and heat sources are caused by human activities. Generally, the heat generated in the surface is resulted from the sun in the form of solar radiation, large industries and factories, cars, air ventilation systems and other sources related to the human activities (Rizwan et al., 2008: 122). Nowadays, use of satellite imagery in urban environment studies has been growing rapidly due to integrated vision and reduction in the cost and time of the studies. Land surface temperature is one of the most important variables measured using these images. Thermal images are widely used to evaluate the urban heat island. More research is focused on the earth surface temperature patterns and their relation to biophysical characteristics of urban areas, especially with vegetation index (Sobrino & Raissouni, 2000: 353; Weng et al., 2004: 467) and changes in land use/cover (Xiao & Moddy, 2005: 237; Amiri et al., 2009: 2006; Weng et al., 2009: 467).
Expansion of the city of Mashhad in the past two decades had augmented numerous environmental problems such as air pollution and urban heat island. These problems led to a decline in air quality and the health of urban life and the risk of diseases such as asthma, insomnia and other respiratory diseases. Hence, the need for environmental research and urban planning in the city has been doubled. Therefore, this research using multi-temporal Landsat images (TM, ETM+ and OLI) investigate spatial-temporal distribution of the urban heat-island variations due to changes in the urban development of Mashhad, vegetation, land use/ cover, simultaneously.
Methodology
In this study, Landsat images of TM (1/5/1987), ETM + (28/5/2000) and sensor OLI (11/5/2014) was used. The Mashhad topographic map at scale 1:25,000 was used for Geometric correction with RMSE error less than 0.5 pixels. We also used FLASH algorithm for the atmospheric correction on the images. To extract Land Surface Temperature from Landsat images, the raw values (DN) were converted into Spectral Radiance image. Spectral Radiance of thermal bands then was converted into brightness temperature. This is by assuming the fact that the brightness temperature of the black body (emissivity= 1) is calculated and contains the effects of the atmosphere (absorption and emission). Brightness temperature using sensor’s calibration coefficients is obtained from the following equation:
 
where T is effective at-sensor brightness temperature [K], K2 Calibration constant 2 [K], K1 Calibration constant 1 [W/(m2 sr μm)], L𝜆 Spectral radiance at the sensor's aperture [W/(m2 sr μm)]. Obtaining land surface temperature is required to know about land surface emissivity (LSE). To obtain the emissivity, hybrid threshold NDVI and image classification method was used. With obtaining the values of the emissivity, the temperature of the surface for TM and ETM+ images can be calculated from the following equation (Artis & Carnahan, 1982):
 
where Ts land surface temperature, T brightness temperature, ε emissivity power, λ wavelength of radiance, α=hc/k (h=Planck's constant; c=Velocity of light) (k=Boltzmann constant). To obtain the land surface temperature from Landsat 8 thermal data (TIRS), we also used split windows algorithms. Finally, thermal image didn’t take simultaneous and heterogeneous classes of images due to changes in urban land use.
Results and Discussion
The results showed that urban sprawl into agricultural areas can reduce green space and that this was the main factor in the surface temperature rise and expansion of urban heat islands in the city of Mashhad. However, global warming, industrial development of the city, and urban traffic (due to the expansion of the city) are increasing the temperature of the thermal expansion of the islands. Thus, the results indicated that about 2,500 hectares of agricultural land and green spaces are changed into built-up land use. This shows that the decrease in vegetation cover is the most important factor in development of the heat islands in Mashhad. With the loss of vegetation cover in and around the city, very cool temperature class (25-29°C) has been replaced by normal temperature class (33-37°C). Furthermore, by manipulating the surrounding areas of the city, their temperature is increased and transformed into the hot and very hot temperature classes.
Conclusion
The results of surface temperature distribution changes indicated that several temperature clusters in the North West, South and South West of Mashhad have been developed. In the north west this development is because of manipulation of the land connected to the city and in the south the development is mainly because of airport's development. The sunny slopes in the West and South West are because of manipulation of these domains. In addition, the conversion of agricultural lands into urban land uses in the east and north east can alter the very cool and cool temperature classes into normal and hot temperatures classes. The results also showed that the use of multi-temporal satellite data and conventional methods can represent the combined heat islands (assessment of spatial – temporal changes of the distribution of urban heat islands into changes in the development of urban, heat islands relationship with vegetation and land use/cover). These changes in the urban surface areas can reveal  all aspects of the formation and expansion of urban heat islands.

Keywords


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