Investigation of urban heat islands of Tabriz metropolis using multi-time data of LANDSAT8 satellite based on hot spot analysis method

Authors

1 Ph.D Student of Urban Climatology, Shahid Beheshti University, Tehran, Iran

2 Associate Professor Climatology, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran

Abstract

Abstract
Rapid urbanization in Tabriz has a significant impact on the urban thermal environment and these changes have affected the climate, environment and quality of life of residents. The aim of this study was to evaluate the urban heat islands (UHI) of Tabriz using spatial autocorrelation methods and its relationship with physical parameters of the surface. NDVI and Split Window algorithms based on TIRS and OLI Sensor of Landsat 8 satellites were used to calculate the vegetation index and land surface temperature; then the relationship between LULC, NDVI and Land Surface Temperature (LST) changes evaluated. Spatial autocorrelation methods Moran's I and Hot Spot were used to identify UHI. The results showed that in the metropolis of Tabriz, there is a significant inverse relationship between α = 0.05 between LST and NDVI. LST minimum and maximum 11.99 to 58.49 Celsius respectively in central and north-west of the city is obtained. Also, the assessment of land surface temperature with LULC has shown that the impervious surface along with the worn-out urban textures are the most important reasons for the intensification of Tabriz urban heat islands. The Moran's I space spatial autocorrelation method showed that the LST of Tabriz has a spatial structure or in other words has a cluster pattern and its value varies between 0.92 and 0.95. The urban heatislands of Tabriz are of the peripheral and triangular type, which increase the intensity and extent of urban heatislands from the center. The largest identified heatisland is located in District 6 of the city. Due to the existence of Tabriz Airport, as well as the existence of barren lands and worn-out urban textures, this area has the maximum land surface temperature (LST).
 
Keywords: urban heat island, LULC Index Index, Getis-ord Gi* Index, TIRS sensors, Tabriz.

 

ExpandedAbstract
 
Introduction:
Rapid urbanization in Tabriz has a significant impact on the urban thermal environment and these changes have affected the climate, environment and quality of life of residents. The aim of this study was to evaluate the urban heat islands (UHI) of Tabriz using spatial autocorrelation methods and its relationship with physical parameters of the surface. LULC is the interface between human activities and the environment, and it plays an important role in the urban climate because LULC changes are often required to support and implement urban planning policies and promote urban comfort. The increased temperatures in urban areas have created significant economic and health-related issues that affect more than half of the global population. Remote sensing is a powerful tool for environmental monitoring that can be used to help understand LULC and rapid urbanization and to estimate UHI properties at the Earth’s surface because the UHI phenomenon affects many millions of people worldwide. Urban areas cover only 2 to 3 percent of the total land area, however, due to the rapid growth of urbanization around the world, have attracted much attention. The city's thermal city (UHI), which in some way can be called the identity of a metropolitan area in modern times, is a phenomenon that has a higher temperature than surrounding areas. The thermal island phenomenon changes the level of surface energy by changing the natural cover of the earth with pavements, buildings, concrete, asphalt and other buildings. City-level frolics (SUHI) exist at any time of the day, and are more intense in the summer and mid-day. The present study was conducted with the aim of evaluating the thermal heat islands of Tabriz and its correlation with physical parameters of the surface using OLI and TIRS sensor data of LANDSAT8 satellite. The results of this research can be effective for urban management models, sustainable development and urban viability in the future.
Methodology:
NDVI and Split Window algorithms based on TIRS and OLI Sensor of Landsat 8 satellites were used to calculate the vegetation index and land surface temperature; then the relationship between LULC, NDVI and Land Surface Temperature (LST) changes evaluated. Spatial autocorrelation methods Moran's I and Hot Spot were used to identify UHI. The digital values of thermal images converted to spectral radiance to calculate the surface temperature. The NDVI index was used to assess the coverage of the earth's surface and its relationship with the surface temperature of the earth. Finally, the Hot Spot Analysis Index, Getis-ord Gi* statistic was used to calculate the urban thermal islands.
Results and discussion:
Land surface temperature (LST) and normalized vegetation index (NDVI) in Tabriz, based on LANDSAT8 satellite data, OLI and TIRS sensors were. Accordingly, the average surface temperature In Tabriz during the study period in summer, it fluctuates between 32.12 and 46.41 ºC, respectively, for September and August 2015, the average amount of earth surface temperature was not expected to be unpredictable in winter. The average surface temperature in Tabriz is 49/37 ° C. Maximum deviation rate occurred in August 2015. The relationship between the two parameters studied, Land Temperature (LST) and (NDVI) showed a negative significant correlation at 0.05% level. The maximum correlation with Earth surface temperature in Tabriz is September 2015. The correlation between September and August in the three months of the summer months is stronger than in August. This may be due to rising rainfall in September, which has increased vegetation. There is a great difference in temperature between the northern and northwestern regions and the central regions of Tabriz (regions 9, 21, 22 and 19). Impermeable surfaces such as concrete and asphalt in urban space trap heat at the surface.
Conclusion:
The results showed that LST is sensitive to vegetation. Therefore, it can be concluded that LST can be used to detect LULC changes over time. The population of the metropolis of Tabriz has grown dramatically over the past two decades; the coincidence of this increase in population has certainly led to changes in the LULC, which has led to an increase in impermeable urban areas and the trapping of the temperature and the rise of urban hot springs. Increasing population numbers, especially in developing countries such as Iran, will increase the pressure on natural resources, which will result in widespread change in urban and urban conditions. One of the most important changes in pressure on natural ecosystems the city will change the city's bio-availability. The largest metropolitan thermal island is located in the 6th district. . The correlation coefficient of Pearson and the coefficient of determination (R2) calculated by the linear regression method showed that the relationship between LST and NDVI vegetation index is a significant inverse relationship at the level of α = 0.05. However, it should be noted that this relationship is necessarily is not linear. LST minimum and maximum 11.99 to 58.49 Celsius respectively in central and north-west of the city is obtained. Also, the assessment of land surface temperature with LULC has shown that the impervious surface along with the worn-out urban textures are the most important reasons for the intensification of Tabriz urban heat islands. The Moran's I space spatial autocorrelation method showed that the LST of Tabriz has a spatial structure or in other words has a cluster pattern and its value varies between 0.92 and 0.95. The urban heat islands of Tabriz are of the peripheral and triangular type, which increase the intensity and extent of urban heat islands from the center. The largest identified heat island is located in District 6 of the city. Due to the existence of Tabriz Airport, as well as the existence of barren lands and worn-out urban textures, this area has the maximum land surface temperature (LST).

Keywords


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