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Climate change and human activities have a direct impact on land vegetation. Some scientists have defined the land degradation as reduced potential for land production or long-term decrease in ecosystem performance, while others have determined land degradation as decreased resources over time due to the negative effects of human activities. Despite these differences in definition, all the definitions imply that land degradation causes decrease in potential of land resources to meet the ecosystem needs. There are several methods for assessing land degradation at different spatio-temporal scales. Land degradation is the result of a prolonged decrease in vegetation and initial production at spatio-temporal scales. Therefore, the long-term study of vegetation can be used as a strong index for assessing land degradation. According to studies, one can conclude that arid and semi-arid regions are very sensitive to climate change, and on the other hand, vegetation well illustrates these changes. Therefore, due to the fact that the Fars province occurs in arid and semi-arid regions of Iran, this study aims to investigate the process of land degradation using the trend analysis of climate data and vegetation indices in Fars province.
Materials and methods
The study area, ​​Fars province, covers approximately 133000 km2, which accounts for 7.4% of the country's total area. In this study, monthly products of NDVI index from Terra satellite, MODIS sensor MOD13A2 were used in this study in order to investigate vegetation. Also, the climate data of temperature and precipitation with the monthly lag from the synoptic stations in the region, with appropriate distribution at the province scale and a common time base during the period of 1385-1396. NDVI products was used to calculate vegetation index for the period of 1385-1396. Also, a 30-m DEM of ASTER sensor was used to study the elevation points of the province. After obtaining climatic (temperature and rainfall) data for the stations in the present study, temperature and rainfall maps were prepared using inverse weighted distance interpolation method. inverse weighted distance method interpolates the unknown quantity by weighing the data around the point. Mann-Kendall test and Theil–Sen estimator were applied to calculate the monthly changing trends of vegetation, temperature and rainfall in the study area. Theil–Sen estimator was used to confirm the accuracy of the trend changes. After analyzing the trend of climatic data and vegetation index, the correlations between these indices were investigated. The linear correlation model was used for monthly NDVI, temperature and rainfall time series.
The changes in NDVI index indicate that the value of this index varies from 0 to 0/55. The changing trend of NDVI index showed a decreasing trend for this index during the time period, climatic indicators of temperature and rainfall showed increasing trends. The trend of changes in the NDVI index showed that this trend is not the same throughout Fars province So that 22.4% of the area of Fars province showed a decreasing trend in terms of vegetation. The increasing trend for vegetation accounted for 64.4% of the area of province. The analysis of rainfall trends showed that this index had a decreasing trend in 86.1% of the area of the province. Rainfall changes without any trend accounted for 9.7% of the province's area, while the increasing trend for rainfall was found for only 4.2% of the province. Positive correlation between these two parameters also was found for 16.4% of the province. The relationship between temperature and vegetation indicates that the negative trend of this correlation is observed in 53.3% of the province's area. Also, about 11.8% of the province did not indicate any correlation between vegetation and temperature. The positive correlation between these two indices was found for 34.9% of the province, so that the temperature increased with increasing vegetation, of which in 13.3% of these areas the correlation was positive and significant. The correlation between temperature and rainfall also shows that there is a negative relationship between temperature and rainfall over 97.4% of the province, of which has a negative and significant correlation was observed for ​​24.5% of the province's area. Also, in 1% of the area of ​​the province, there was no correlation between these two parameters and in 1.6% of the total area of ​​the province, the relationship between rainfall and temperature was significant and positive.
Discussion and conclusions
The trend of changes in vegetation and climatic parameters in this study showed that their increasing and decreasing trends are different in different regions of the province, so that 64.1% of the province showed an increasing trend for vegetation, mainly dominated by agricultural land use. On the other hand, during this time period, the trend of climatic parameters of temperature and rainfall were increasing and decreasing until 1395, respectively. Therefore, one can conclude that more than half of Fars province is characterized by rainfall shortage and increased temperature, which ultimately would result in reduced water for agriculture. The analysis of the vegetation trend in Fars province showed that 22.3% of the region had a negative trend during this 12-year period. land-use of these areas are mainly rangeland and forests characterized by semi-arid and semi-humid climates. Correlation analysis between vegetation index and climatic data of rainfall and temperature also show a negative correlation between vegetation index and rainfall and a positive correlation between vegetation index and temperature in these areas. This can be due to irrigated agriculture for which farmers use groundwater (Karimi et al., 2005) (24). Another reason for this negative correlation is the adaptation of plants to the region conditions which has made the plants more resistant to drought and water shortages (Lamchin et al., 2018). The results of trend analysis using these statistics indicate that vegetation showed an increasing trend in agricultural lands. Decreased rainfall and increased temperature will lead to reduced surface water resources, and, on the other hand, decrease in such resources would reduce water for agriculture, thus increasing the use of groundwater resources, which in turn leads to land degradation and desertification.
Type of Study: Research | Subject: Land degradation
Received: 2018/12/5 | Accepted: 2019/07/14

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