| چکیده انگلیسی مقاله |
Statement of the Problem: One of the most important challenges in studying vegetation cover and its vulnerability is the lack of precise spatial information. Satellite data with temporal and spectral diversity can be a suitable tool for investigating vegetation cover. Remote sensing is one of the most important technologies in spatial studies and spectral characteristics of phenomena and can play a significant role in terrestrial studies. In southern Kerman, due to the climatic conditions, plants that are resistant to dryness, heat, and unfavorable soil conditions can grow. The region, influenced by arid and semi-arid climates, has poor vegetation cover. Therefore, the management of natural vegetation cover and agriculture requires an assessment of the factors affecting them.
Purpose: Plant cover plays a crucial role in maintaining natural balance in ecosystems and changes in it can indicate environmental transformations. In dry and semi-arid regions, a reduction in plant cover can lead to soil erosion, land degradation, and desertification. This issue is particularly important in southern Kerman, which is a dry and semi-arid region. The aim of this study is to evaluate changes in plant cover influenced by climate.
Methodology: As mentioned, the aim of this research is to assess the trend of vegetation cover changes. For investigating the trend of vegetation cover changes, Kendall non-parametric test in TerrSet software was used to calculate the trend of EVI changes from 2001 to 2022 for the target month. Then, the correlation of EVI changes over time was determined using Pearson correlation coefficient by the Earth Trends Model (ETM) in TerrSet software. The slope of EVI changes in the target month over time was calculated for 22 years using TerrSet software. Linear regression analysis can be used to simulate the trend of changes. This method determines whether there is a linear relationship between all data of a dependent variable and corresponding data of an independent index. Generally in the present study, a time series of the Enhanced Vegetation Index (EVI) for the years 2001-2022 in South Kerman was prepared using MODIS sensor data, and the trend of changes in the mentioned index was calculated by applying the Kendall trend test in the TerrSet software. Then, using the ETM modeling in the TerrSet software, the correlation of EVI changes in a unit time, based on Pearson correlation coefficient.
Results and discussion: Based on the results, the month of April, which had the highest EVI index, was chosen to investigate the trend of EVI changes. According to the results obtained, a large part of the study area shows a decreasing trend. In 44.16% of the study area, there is a probability of over 99% that the trend of EVI changes is decreasing. These areas are scattered in most parts of the study area, but are mostly observed in the western, northwestern, southwestern, southern, and eastern parts of the area. In 23.38% of the study area, the trend of EVI changes is decreasing with a probability of 95 to 99%. These areas are also located on the margins of the previous classes. The decreasing trend of EVI with a probability of 90 to 95% only occurred in 7.86% of the study area. Overall, 75.4% of the study area has a probability of over 90% that the trend of EVI changes is decreasing. Based on the results, very slight and slight change classes include 15.28% and 21.95% of the study area, respectively. covering major parts of Bam, Fahraj, the northern and eastern areas of Narmashir county, and northern parts of Qaleh Ganj county. The central, western, and southwestern parts of the study area are allocated to the classes of very high and high change intensity, covering 17.06% and 22.75% of the study area, including major parts of Manujan, Kuhnuj, Faryab, Roudbar Jonub, Arzouyeh, and Jiroft South. Moderate change intensity classes were observed in the eastern, southeastern, southern, and northwestern parts of the study area, covering 22.95% of the study area. According to the results obtained, the highest average monthly long-term EVI value belonged to the month of April, leading to the selection of this month as the study month for evaluating the trend of EVI changes over 22 years and calculating the slope and correlation of EVI changes in a unit time. According to the research findings, 44.16% of the study area had a decreasing trend in EVI with a probability of over 99%, covering the largest extent of the study area. Furthermore, very strong correlation class and moderate slope class of changes accounted for 20.89% and 22.95% of the study area, respectively, allocating the largest extent to themselves. Additionally, the highest percentage of the areas of Kuhnooj and Manoojan counties, with 36.58% and 35.48% respectively.
Conclusion: Given the prevailing climate conditions in the southern regions of Kerman province, studying the status of vegetation cover and its changes over time can be beneficial in the management of land and natural resources in this province. Therefore, the present study focused on investigating changes in the Enhanced Vegetation Index (EVI) in southern Kerman. The results showed that the EVI reaches its peak in April and March in the study area. Considering that the EVI has a high predictive power for green vegetation cover and plant production, it can be concluded that vegetation cover is in a better condition during these months compared to others. In other words, the growing season for vegetation cover in the study area is during these months. The evaluation of EVI changes trend showed that 75.4% of the study area has a more than 90% probability of decreasing vegetation cover changes trend. In other words, vegetation cover is being degraded.
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