hossein azarnivan

Terrestrial ecosystems depend on vegetation to connect water, soil, air, and other components. Using remote sensing technology, this study explores vegetation dynamics in Khorasan, including their response to land use changes and climate changes between 2001 and 2020. This study aimed to investigate and analyze the effects of climatic factors on vegetation dynamics.

In this study, satellite and climate data are used. The National Meteorological Organization provided climate data, and the USGS provided satellite data on vegetation indicators. This research used monthly NDVI and EVI indices to investigate the vegetation cover from 2001 to 2020. These monthly images with a spatial resolution of 1 km were prepared from the MODIS terra sensor satellite. Using the IDW interpolation method, the climate data of 39 investigated stations were prepared, and their maps were prepared in ArcGIS. Linear regression simulated trends in vegetation index and climate parameters over 2001-2020 in QGIS. NDVI and EVI indices were correlated with climatic parameters to investigate changes in vegetation cover.

Based on the trend of land use changes in Khorasan, the main land uses are barren lands, agricultural lands, forests, rangelands, open shrubland, savanna, and built-up areas. During this period, barren lands, agricultural lands, forests, and rangelands decreased by 2.57, 0.41, 0.0009, and 1.02 %, respectively, while open shrubland, savannas, and built-up areas increase by 3.98, 0.0031, and 0.0072 %. Examining the change slope of the vegetation cover index and climatic parameters in these 20 years showed that the change slope of the vegetation cover index EVI and NDVI in these 20 years are positive and increasing, respectively 72.81% and 85.46% of Khorasan, which can be said in general According to these two indicators, vegetation cover is increasing in more than 85% of Khorasan's natural lands. Examining the slope of rainfall and temperature changes in this period of time showed that these indicators had positive and increasing changes in 76.59 and 58.71% of the area of Khorasan, respectively. The correlation results between EVI and NDVI vegetation indices with rainfall show that there was a positive correlation between these two indices in 87.27 and 90.71 % of Khorasan. Correlation between vegetation indices EVI and NDVI and temperature showed that there was a negative correlation of about 74.27 and 77.26% respectively in the studied area. Most land use areas barren lands, agricultural lands, rangelands, and open shrublands have a positive correlation between the EVI vegetation cover index and rainfall in semi-arid, dry, and semi-arid climates. These correlation results show open shrublands, rangelands, and barren lands had 49.18, 80.96, and 100% positive correlations, respectively. The results of this correlation in the semi-humid climate in rangelands and forest land uses were positive at 95.30% and 1.15%, respectively. The results of the correlation between EVI and temperature in the semi-arid climate in semi-arid, dry and semi-arid climates show that this relationship in most barren lands, rangelands and open shrublands is negative. Also, the results of this correlation in the Mediterranean climate show that this correlation is positive in the use of barren lands, rangelands and open shrublands 40.99, 91.02 and 23.08 %. The results of this correlation in the semi-humid climate show that this relationship is 100 and 98.06 % positive in barren lands, and rangelands, respectively, and 1.94 % negative in open shrublands. In the majority of areas, such as barren lands, agricultural lands, rangelands, and open shrublands, there is a positive correlation between NDVI and rainfall in extra-arid, dry, semi-arid, and Mediterranean climates. In the Mediterranean climate, barren lands, rangelands, and open shrubland use are all 100% positive, 62.15 and 77.0.1 respectively. In semi-humid climates, barren lands and pastures are used 52.56 % and 38.63 %, respectively. A negative correlation was found between NDVI and temperature in extra-arid, dry, semi-arid and Mediterranean climates in most of the land use areas barren lands, agricultural lands, rangelands, and open shrublands. Based on the results of the correlation, barren lands, rangelands, and open shrublands are 99.60, 93.66, and 100% positive, respectively. According to the correlation results between NDVI and temperature in semi-humid climates, barren lands and rangelands have a 100% positive correlation.

The destruction and restoration of vegetation have become a major challenge in Iran. Land degradation and desertification conditions will increase due to the interaction of human activities and climate change. North Khorasan, Razavi and South Khorasan were studied separately and in detail at the climate and land use levels. Consequently, the findings of this study can be very useful and necessary for the implementation of policies and projects to promote vegetation restoration by men and politicians in the field of natural resources and the environment.

As a hazardous complex climate condition, drought has affected many parts of the world, and in times when its duration is prolonged, its damage would be tremendous, affecting various sectors such as agriculture, environment, economic, social, etc. Due to the wide range of this phenomenonchr('39')s effects on all ecosystems, especially in arid and semiarid regions, continuous monitoring of drought is particularly important. Vegetation and its products are among the most significant parameters affected by this destructive phenomenon. Observation of such harmful effects can be done using remote sensing science. In recent years, this science has played a significant role in managing and monitoring drought, vegetation, and their interactions by increasing sampling points, widening the coverage area, improving temporal resolution, lowering costs, and applying regular and higher spatial resolution. Considering the importance and necessity of this issue, this study set out to investigate and monitor drought indices (SPEI, SPI), vegetation index (NDVI), and these indiceschr('39') interactions from 2000 to 2016 in Hormozgan province, Iran.

To study meteorological drought and potential evapotranspiration, the required data concerning the monthly rainfall and temperature of 164 rain-gauge stations in the region were collected. Then, the homogeneity test was applied to all stations. Statistical deficiencies were reconstructed for the data, and finally, the annual SPI values were calculated using MATLAB software. Kriging geostatistics was used to map the SPI drought. Due to the availability of satellite images for 2000-2016, a drought map was prepared for this period. The NDVI index obtained from the Modis satellite images (MOD13A2) was also used to study the vegetation. Finally, to investigate the effects of meteorological drought and potential evapotranspiration on vegetation, the average NDVI and drought index was calculated for each year, and the severe effects of drought on vegetation were examined. Moreover, the correlation between vegetation and drought was studied through the Pearson correlation coefficient.

According to the results of the study, the highest values of SPI and SPEI were found in the years 2009, 2014, 2012, and 2011, respectively. NDVI and annual rainfallchr('39')s changing trend indicated that these indiceschr('39') mean values were significant at 95 levels over the 17 years, showing an increasing trend. The trend of temperature, SPEI, and SPI changes was decreasing during this time interval. Also, the vegetation index peak was in accordance with the highest rainfall value in this time period. In other words, the highest rainfall occurred in 2005 in this region. The vegetation index showed the highest increase this year, suggesting that vegetation was affected by rainfall fluctuations in the region. Based on the results of the Pearson correlation coefficient between meteorological drought, evapotranspiration potential, NDVI vegetation index, precipitation parameter, and temperature at a 12-month time-scale, the highest correlation was reported between SPI index and precipitation, which was equal to 0.99, and the lowest correlation was found between temperature and SPEI, being 0.48. Moreover, this correlation coefficient analysis showed a high correlation between the meteorological drought index and NDVI vegetation index at 95% level in the study area. This correlation was reported as 0.792. The correlation between SPEI and NDVI was also reported as 0.797, indicating that with an increase in precipitation rate, the NDVI increased.

It could be concluded that, depending on the prevailing conditions of the area, the extent, time, and type of rainfall affect the amount of vegetation. Therefore, studying and identifying vegetation in each area could lead to the discovery of each regionchr('39')s conditions and the vulnerability status of the area. Any reduction in the effects of drought on these fragile and sensitive ecosystems requires careful planning according to each regionchr('39')s conditions. Planners and relevant authorities should take appropriate measures to improve the irrigation system, reduce evaporation, enhance the crop system, mitigate the damages caused by drought, and get the ecosystem adapted to climate conditions. Moreover, this study used Modis images with a kilometerchr('39')s pixel size. For a closer look at the vegetation index, satellite images with smaller pixel sizes, such as Landsat ones, could also be used to increase spatial accuracy. Finally, a more detailed study is recommended to investigate the effects of drought on vegetation in different land-uses.