بررسی تغییرات پوشش گیاهی با استفاده از شاخص NDVI و ارتباط آن با دمای سطح زمین (مطالعه موردی: شهرستان کوثر)

Introduction
Vegetation, as an important part of the earth, plays an essential role in providing organic matter to terrestrial organisms, regulating the carbon cycle and promoting energy exchange (Das Gardi et al., 1401). In fact, vegetation is one of the main ecosystems of the earth and plays an irreplaceable role in regulating and protecting the atmosphere, water and soil, reducing the concentration of greenhouse gases and increasing and maintaining climate stability (Darvishi et al., 1401). Vegetation plays a central role in the negative urban effects and reducing the surface urban heat island effect (Jio et al., 2019), in general, vegetation is the most important factor that connects soil, atmosphere and humidity. Natural vegetation changes due to seasonal and annual climate changes, however, vegetation can be a measure of global climate change (Bagherzadeh et al., 2020). During the last two decades, plant indices have been widely used in natural resource studies and vegetation monitoring from small scale to regional and global scales (Natighi et al., 2016). Normalized Difference Vegetation Index (NDVI) is an important index for large-scale vegetation cover. The magnitude of NDVI indicates the intensity of vegetation activity, and this intensity reflects more of the structure and functional characteristics of the ecosystem (Jeo et al., 2019). The pattern of land use is constantly changing due to the increase of human activities (Mansour Moghadam et al., 2019). Investigating the sustainability of vegetation changes is one of the most important issues of vegetation management and control in the direction of sustainable development. Changes in the area of vegetation have different factors, such as the use of forest trees for fuel, livestock pressure on pastures, forest fires, and droughts cause a decrease in the area and loss of vegetation (Mahmoud et al., 1400). Over time, land cover patterns and land use undergo major changes (Ding et al., 2013). Factors affecting vegetation changes mainly include two types: climate changes and human activities (Zhang et al., 2019). Evaluation of vegetation changes at the regional and provincial levels using field methods due to the large extent, complexity, rate and The nature of what can be different in time and place is difficult (Abbas Nejad et al., 1401). Due to the limitations resulting from spatial and temporal variability and the cost of field studies, the use of satellite images provides acceptable results in the investigation of vegetation cover changes due to its wide coverage and multi-temporal nature (Jehan Tigh et al., 2018). The advancement of remote sensing technology in recent years has made experts to study the planet Earth comprehensively and more precisely. Vegetation studies are one of the important studies that are carried out using remote sensing and in this way the growth, disease, moisture, dryness and freshness of the plant are studied (Kefait Mutlaq et al., 2016).
According to the stated contents and the studies conducted in connection with this issue, the purpose of this research is to investigate the changes in vegetation cover using the NDVI index in the last 30 years and to evaluate the change in the density of vegetation cover. It is also a study of the relationship between vegetation cover and the Land Surface Temperature.

materials and ways
Kausar city (Givi) with an area of 14.3211 square kilometers is located at 48 degrees 29 minutes of longitude and 37 degrees 41 minutes of latitude and is located at a distance of 85 kilometers from Ardabil. It is neighboring with Nair and Miene cities. The average rainfall in this region is about 444 mm and 86 to 94% of the total rainfall occurs in the months of April and May. The vegetation of this city is steppe and in the highlands in the form of pastures and meadows. In this research, images from Landsat 8 and 5 were used to investigate vegetation density and evaluate its changes in the last 31 years. These satellite images have also been used to estimate the Land Surface Temperature. The images obtained in ENVI5.6 software are cut based on the study area and then atmospheric corrections are applied on it. After making corrections, vegetation density has been measured using the NDVI index; This was presented by Rose et al (1974). NDVI is based on the difference between near infrared (NIR) and pigment absorption in the red (VIS or visible red) (Bagherzadeh et al. 2020). As the most well-known vegetation index, this index is used to evaluate the health and density of vegetation by measuring changes in plant chlorophyll absorption. And then the temperature of the earth's surface is estimated by the single channel method. Various algorithms are used to determine the real Land Surface Temperature, such as the single-channel algorithm. This algorithm was presented by James-Mons et al. (2014), which was developed with the aim of extracting Land Surface Temperature using a thermal infrared band. In the single-band method, the temperature is estimated assuming that the emission coefficient and atmospheric profiles are known. Finally, in this research, the relationship between vegetation cover and temperature was measured using geographic weighted regression.
Conclusion
In this research, vegetation density was estimated using NDVI index in both years 1991 and 2022. Then, the extent of vegetation was measured by thresholding; that in 1991, the area of dense vegetation cover is about 11 km and in 2022, it is 8 square km, in general, 3 km of the area and forest trees in Kausar city have decreased, also the area of medium and low density vegetation cover in 1991 is about 97 km and In 2022, it will be about 85 kilometers; that in the last 31 years, the vegetation in the study area has decreased significantly. Many human and natural factors are effective in the change, density and extent of vegetation cover. One of the most important factors of climate change is that among the climate factors, temperature is the most important component of the climate that affects it. In this study, the temperature value was also evaluated in both years of the study; And then, using geographic weighted regression, the relationship between temperature and vegetation was investigated. The results showed that the highest temperature in 1991 in Kausar city was 53 degrees Celsius. But in 2022, the maximum temperature has reached more than 60 degrees. Therefore, in the studied area, the temperature has increased by about 8 degrees. By applying geographic weighted regression, it was found that there is a significant correlation between temperature and vegetation. Its correlation value (R) is 0.7 in 1991 and 0.8 in 2022 and its Sig value is zero. In general, the more Sig is less than 0.05 and the R value is closer to 1, the higher the correlation between two data.