Estimation Soil Adjusted Vegetation Index surface energy balance By analyzing their relationship through linear regression (Case Study: Nazarabad City)

Temperature is one of the main factors influencing urban planning because it guides the type of facilities available in cities and even determines the urban structure, shape and texture. On the other hand, increasing vegetation cover is one of the most effective strategies to reduce urban climate impacts. In the present study, the land energy balance algorithm was used to achieve land surface temperature and the soil vegetation index of Nazarabad city was used to estimate plant poisoning. For this purpose, Landsat satellite images (TM-OLI), years (2000-2019) were used. First, the relevant images were obtained and the necessary preparations were made. Then, the object-oriented classification was performed. Linear regression analysis was used to estimate the correlation between surface temperature and vegetation. Surface temperature results showed that vegetation areas such as agriculture and rangelands averaged 32 and 34 ° C for 2000 and 2019, respectively. However, during these years, vegetation-free areas such as urban and wilderness areas that were devoid of vegetation have averaged 36 and 39 degrees Celsius, indicating the effect of vegetation on surface temperatures. Also in estimating the correlation between vegetation and land surface temperature, it can be said that there is a strong correlation between the data. Independent variables have been explained which show high value and the model is significant with 0.95% confidence and is able to express changes based on available data so it can be concluded that this model has high accuracy for this study.