Geographic Information System (GIS)
Ahmad Mazidi; Foroogh Mohammadi Ravari
Abstract
Extended Abstract
Introduction:
Time series analysis is a suitable tool that is used in mathematical modeling, predicting future events, revealing trends, investigating diffraction in climate data, as well as reconstructing incomplete data, and expanding information. Climatic changes are mainly caused ...
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Extended Abstract
Introduction:
Time series analysis is a suitable tool that is used in mathematical modeling, predicting future events, revealing trends, investigating diffraction in climate data, as well as reconstructing incomplete data, and expanding information. Climatic changes are mainly caused by fluctuations, fluctuations, or changes in climatic elements, especially temperature and precipitation. These developments leave undeniable effects on local phenomena, hence the evidence of the past climate can be traced in all wet and dry, hot and cold environments, and biological areas (Ghayour, 2006:85). The temperature of the earth's surface is an important parameter for evaluating the energy budget of the earth's surface (Trigo et al, 2008:1). With the change in climate (temperature and rainfall), many changes are made on the surface of the earth, including vegetation. In fact, with the increase in temperature and decrease in rainfall, vegetation in the region decreases. Considering the importance of the issue and the relationship between climatic indicators and vegetation, by determining the relationship between them, one can predict the changes based on the other, which leads to an increase in the speed and accuracy of the work. Therefore, it seems important to use satellite images and extract and investigate the relationship between temperature and rainfall factors as well as vegetation in different areas, especially watersheds (Zhu et al, 2016:792). With the expansion of satellite technology, satellite images have widely provided access to information on land resources, and remote sensing tools have taken an important role in obtaining information about climate phenomena, because multi-spectral satellite images have important advantages, including They have the availability and ability of digital interpretation (Lillesand and Kiefer, 1994:750).
Materials & Methods:
In this research, using monthly rainfall data from a CHIRPS sensor with a spatial resolution of five kilometers, NDVI vegetation index from a MODIS sensor for 16 days, with a resolution of 250 meters, and day and night surface temperature of 8 days from a MODIS sensor with a resolution of one kilometer, to analyze the changes in surface temperature and its relationship with climatic factors in Kerman province during a statistical period of 22 years (2001-2022) were studied. In the investigation of the annual precipitation fluctuations of Kerman province, standardized values of Z have been used, and these values have varied between -1.5 and +1.5. After receiving the data, first the CHIRPS images, then the NDVI and LST images were processed in the ArcGIS software environment and the values were extracted for Kerman province and then analyzed in the Excel software environment.
Results & Discussion:
According to SPI results, drought is observed in 2010, 2016, 2018, and 2021, and drought in 2004, 2009, 2017, 2019 and 2020. In the rest of the years, the SPI index has been normal. Also, the seasonal rainfall showed that the highest rainfall was in the winters of 2005, 2017, and 2019 with an amount of 90 mm and more and the lowest rainfall was in the summer of 2019 with an amount of less than 1.04 mm. The value of the vegetation cover index (NDVI) is also in the spring season with a value of 1.05, which has an increasing trend, and the lowest value of the vegetation cover index (NDVI) in the autumn and winter seasons, whose lowest value is 0.35 and 0.42 on December 19 and November 17 with a trend A decrease is shown. The seasonal vegetation also shows that as we move from the west of the region to the east, the amount of vegetation decreases. The seasonal changes in the temperature of the surface of the earth during the day in Kerman province show that the hottest seasons are summer and spring and the coldest season is winter. The seasonal changes in the earth's surface temperature at night also show that the highest surface temperature is related to summer and spring, and the lowest is in autumn and winter.
Conclusion:
In general, the results show that according to temperature fluctuations, there is a positive and significant relationship between the temperature of the earth's surface and vegetation (P-value at the 0.01 level). And there is a negative and significant relationship between the temperature of the earth's surface and precipitation. So precipitation has the greatest effect on the variability of the earth's surface temperature and vegetation has the least effect on the surface temperature changes. The increase in day and night temperatures in the spring and summer seasons causes an increase in evaporation and a subsequent decrease in water resources throughout the province and pressure on underground water. On the other hand, with the increase in temperature, the amount of evaporation and transpiration (plants' water needs) will also increase and will lead to a potential decrease in water resources, especially in the eastern regions of the province, but the presence of vegetation can almost reduce the temperature of the earth's surface. In the autumn and winter seasons, during the last decades, with the increase in temperature, the amount of precipitation and vegetation has decreased. Also, an increase in temperature can increase the water demand, which in turn leads to more extraction of surface and underground water resources. This means that the surface temperature has increased significantly in the mentioned statistical period. Also, the different conditions of each region are important factors in determining the type of relationship between temperature, vegetation, and precipitation. The results of this research on the relationship between the earth's surface temperature and climatic factors with the research of Mianabadi et al (2023), and Mazidi et al (2023) based on the method of the experimental relationship between surface temperature and other factors are consistent. According to the findings, the temperature trend in Kerman province is significant and the possibility of heat stress will increase in the future.
Geographic Data
Foroogh Mohammadi Ravari; Ahmad Mazidi; Zahra Behzadi shahrbabak
Abstract
Extended Abstract
Introduction
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 ...
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Extended Abstract
Introduction
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).
Methodology
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 & Discussion
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.
Conclusion
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.
