ABSTRACT Today, climate change and its obvious negative effects on ecosystems have caused concern. This research seeks to test whether VEGETATION changes are sensitive to climate shocks and also how the ecosystem recovery process is through this index. In this regard, by using the GEE platform, Java coding, GIS and statistical analysis, VEGETATION and Palmer indices were calculated and based on time series climate data, VEGETATION and climate changes were presented. The results of Palmer's drought index show that during the statistical period (1985-2020) the study area is facing drought or is moving towards drought. Also, the results indicate the longest period of drought in the region from 2013 to 2020. Totaly from 420 evaluated months, the NDVI index is below the change threshold in 70 months. Among these, 31 months of the study period is below the acceptable threshold in green and non-reservoir seasons, which is ecologically worrying. The distribution of the VEGETATION index based on hexagons in 1985 and 2005 had a normal and almost normal distribution; But in 2020, the graph deviated from the normal state and skewed towards the VEGETATION cover index under stress or even thin covers. According to the analysis of the indicators, it is predicted that the Gorgan region is on the border of such ecological developments and the historical ecosystem of the region is moving towards new ecosystems or being in a new equilibrium state with climatic conditions and human disturbances Extended Abstract Introduction Today, climate change and its obvious negative effects on terrestrial ecosystems have caused great concern to humans. These changes are effective on VEGETATION performance, plant distribution patterns, and have economic and environmental consequences. Therefore, it is important to know the behavioral pattern of VEGETATION changes against climate changes. Reviewing the studies of scientists in the world shows many researchers have used the NDVI index to study temporal and spatial changes in VEGETATION and its relationship with the climatic index of precipitation in different parts of the world. Studies have shown that NDVI follows precipitation with different time scales. Surveys showed that there are very few studies on determining the threshold of changes in the VEGETATION cover index in the face of climate shocks. Determining these thresholds can provide a suitable solution for evaluating the state of the ecosystem, the consequences of climate shocks and the reversibility or disturbance in the ecosystem. This study was conducted with the aim of improving our understanding of the dynamics of VEGETATION in the forest city of Gorgan during 1985-2020 against climatic stresses.   Methodology The current research is a comparative and monitoring research and seeks to test whether changes in VEGETATION cover are sensitive to climate shocks and also how the ecosystem recovery process is through this index. To achieve the gole, first, NDVI index was selected among the optimal VEGETATION indices and its calculation process was done as a time series in the GEE system. In parallel with those climate shocks, the main elements including temperature, precipitation and storm were calculated during the historical process of 35 years and the average and standard deviation statistical indicators were calculated for them and the trend of changes in the thresholds was determined. The results of climate plots and climate changes show that in the years before 1985, 2005 and 2020, drastic changes have occurred in climatic elements and climatic factors. Therefore, these years can be considered as the periods when the climate shock happened.. Next, the region was divided into 436 hexagons and the NDVI index for each of the hexagons was calculated and modeled for the years 1985, 2005 and 2020 as selected years affected by climate shocks. In conclusion, to analyze the trend of changes in the time series of the VEGETATION index and compare the behavior of its changes with climatic indices, the Palmer index was calculated.   Results and discussion The results of climate change monitoring based on the Palmer index showed that during the statistical period the study area is facing drought in most years. The most severe climatic fluctuations and drought in the region were recorded in 2018 and in the months of October to December. The longest period of drought has also prevailed in the region from 2013 to 2020. During this period, rainfall, temperature and storm fluctuations have the most changes. The results of drought monitoring show that in 270 months, the region is facing climatic drought stress, 57 months of the study period, the region is facing severe and very severe drought stress. The results of the time series of the NDVI VEGETATION index showed that, out of the 420 evaluated months, 70 months of the year the NDVI index is below the change threshold, 31 of which are in the green and non-accumulating seasons, the seasons when the VEGETATION is expected to be at its maximum. Placing below the acceptable range means crossing the ecological thresholds and challenges the recovery and restoration of the ecosystem, also the ecological performance will be affected at this point. Based on the assessment of the Palmer index, from 2014 to 2019, the situation of the Palmer index is in the extreme drought range. Also, since 2015, i.e. with a one-year time delay, NDVI index has experienced the lower limit of the equilibrium threshold of VEGETATION cover. These conditions are also valid for the years 2008, 2009, 2002 and 1997. In general, it can be said that the VEGETATION cover index is dependent on climatic changes and fluctuations and shows high sensitivity to changes. The important point in this section is that in the years when the NDVI index changes are at the lower limit of the threshold, we witness the most climate shocks and temperature changes, the occurrence of severe storms and precipitation fluctuations. The distribution of the VEGETATION index based on hexagons in 1985 and 2005 have a normal distribution; but in 2020, the graph has deviated from the normal state and skewed towards the VEGETATION cover index under stress or even thin covers. The visual interpretation done on the VEGETATION cover index in 1985 confirms the condition of the VEGETATION cover in the southern and western limits of the region in a state with suitable dense and pasture VEGETATION and forest cover on the edges. However, in 2005 and 2020, this cover has been changed and mainly turned into agricultural land and poor rangeland. In such a way that in 2020, the situation of the region has revealed the critical state of VEGETATION. The VEGETATION cover index in the central areas of the city has also reached from a relatively favorable situation in 1985 to a critical situation with almost no dense and stress-free VEGETATION cover in 2020. The results of the present studies are consistent with the studies of Visentr Serrano et al. in 2013 and confirm the relationship between NDVI VEGETATION and climate change. In addition, the results of the studies are consistent with the studies of Alwesabi 2012, Xiai & Moody, 2005 and Yan et al. 2001. In such a way that the present study and the aforementioned studies all confirm the influence of the VEGETATION index on climate fluctuations and precipitation with a one-year time difference.       Conclusion In general, the threshold is defined as a border with different conditions. After crossing the thresholds, the stability and positioning of the NDVI in the equilibrium range is often difficult, and the ecosystem is constantly spending energy to restore itself or to position itself in a new stability state. The result of the mentioned disorders is the reduction of resilience and resistance in the region, which leads the ecosystem to alternative states or crossing the threshold or being in a new equilibrium state. The results showed that the areas where green VEGETATION is concentrated and denser are less affected by climatic stresses and show more resilience. However, the areas that have become spots and islands due to destruction in the urban areas are more affected by climatic stress and destruction and show less tolerance against the destruction factors. The results help managers to focus their management plans for the preservation and maintenance of urban green spaces as well as forest and pasture ecotones on the edge of the city by knowing the thresholds.   Funding There is no funding support.   Authors’ Contribution Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

The monitoring of VEGETATION changes has a fundamental role in planning and management of environment. There are various methods to determine the changes in a region using satellite images that each has advantages and limitations. The use of VEGETATION indices is one of the methods to detect the changes. The aim of this study was to evaluate four VEGETATION indices including NDVI, SAVI, RVI and WAVI. This research was performed in Qeshm Island using Landsat images during 2001 and 2014. In this research, ETM+ and OLI data were used. After calculating each indicator, 100 sample training points were used to assess the accuracy of indicators by ENVI. 5. 3. Four classes including bare land, mangrove forests, agriculture and water were classified. Based on Dlapyan & Smith method, the product accuracy and user accuracy for each class were evaluated. The results showed that the SAVI index with the highest kappa coefficient, 0. 93 in 2014 and 0. 83 in 2001, had the best results and WAVI index with the lowest kappa coefficient, 0. 43 in 2001 and 0. 81 in 2014, had the weakest results. To evaluate the changes, crosstab method was used. The results showed that during 13 years the area of mangrove forests and agricultural lands and natural VEGETATION of Qeshm Island increased up to 21% and 60%, respectively.

Satellite images are currently used as a fast and low-cost tool for rangeland assessment. In this study, 10 VEGETATION indices from different groups were calculated using spectral bands. The correlation of these VEGETATION indices with canopy cover was then measured for three VEGETATION types in Semirom region-Isfahan. The percentage of canopy cover and other earth surface components such as litter, rock, gravel, stone and bare ground were determined using step-point method. Ten random points were selected in each VEGETATION type and four 150 meters transects in two perpendicular direction were established from each point, therefore 6000 points were studied per rangeland type. Ten different groups of VEGETATION indices including slope-based, distance-based and plant–water sensitive indices extracted from IRS-P6 satellite data (AWiFS sensor) were evaluated against total ground cover. The results indicated that VEGETATION indices have higher relationships within VEGETATION types based on their characteristics but the correlation for each VEGETATION index was not consistent among different types. Considering all photosynthetic VEGETATION cover, the correlation between these factors and VEGETATION indices were much higher than degraded sites due to greater reflectance from bare soil and less photosynthetic area. In general, the results indicate that each VEGETATION index is appropriate for mapping a specific VEGETATION type and we should consider this issue in mapping and monitoring VEGETATION cover.

In this research, to evaluate VEGETATION cover percentage an to determine optimum VEGETATION indexes for multivariate regression modeling in the Ab-Mahi subbasin of Doorodzan dam watershed basin with the area of 15, 800 ha, usimg spectral reflection detected by ETM+ sensor of landsat satellite in the year 2002. In the first step, after primitive image processing, including radiometric and geometric correction using optimum index factor (OIF), false color composite map with band combination: RGB=741 were prepared for field studies. Then, by doing field studies, considering false color composite map 63 plots (1m *1 m) were randomly selected at the region area. The percentage of canopy cover were estimated in the field studies. In this regard the coordinates of each point was determined using GPS. These information were used in order to construct the VEGETATION cover incorporated with ETM+ imagery data. To obtain a reliable VEGETATION map six main bands of ETM+ and 26 artificial imagery were applied to training data set in ILWIS software. Finally the overall accuracy of prediction was calculated by coefficient of determination (r2) and root means of square error (RMSE). The constructed VEGETATION canopy map was used in land qualitative evaluation of rangeland for the study area. At last, It was shown that it is possible to model and determine the vegetative land cover percentage with an acceptable accuracy using satellite images (ETM+) and implementing appropriate digital analysis.

In this paper, an entirely novel, theoretical restoration/conservation tool will be described. This tool will take the form of self-sustaining ‘synthetic VEGETATION’ designed, through the use of solar energy, to generate Oxygen through the electrolysis of water and sequester CO2 in a disposable form through the formation of Carbonic acid amongst other things; in short simulate many of the major functions of living VEGETATION. The environmental role of synthetic VEGETATION as a terrestrial ecosystem ‘prosthesis’ is evaluated with a Carbon acquisition calculation and a cost benefit analysis reviewing the benefits of utilization in the context of material costs. It is proposed that synthetic VEGETATION could greatly aid in conservation by regenerating degraded environments and speeding up the process of restoration.

In this research, Floristic and ecological characters of Saivan region that is situated in 45th km northwest of Tabriz were studied. This region is located between 45° 50' 40" to 45° 52' 57" E longitude and 38° 20' to 38° 21' 12" N latitude with an area of 1000 hectares. The region of vascular flora was exactly determined and 230 species belong to 179 genera and 50 families were determined. Some ecological conditions such as: soil tissue spoils pH. Soil salinity. Quality and quantity of average precipitation and average temperature in year was studied. The region VEGETATION was studied by floristic and physiognomic methods. By physiognomic study of the VEGETATION region. Different biological types were determined and the region life spectrum was designed. The floristic study of the VEGETATION region was carried out by Braun - Banquets method. In this way after determing minimal area. 17 releves were made inn the region. Then this releves were treated by mathematical and comparative methods. So that. VEGETATION Units of the region was recognized. In mathamatical method. Jackard coefficient and in comparative method .raw. constancy. partial and ordinated partial tables have been employed. As a result. edaphic factors are most important factor: in distribution of VEGETATION units.

VEGETATION indices have been developed to characterize and extract the Earth's VEGETATION cover from space using satellite images. For detection of VEGETATION changes, usually temporal images are independently analyzed or VEGETATION index differencing is implemented. A review on previous studies reveal that, in spite of developing several VEGETATION indices, to extract VEGETATION cover or VEGETATION changes usually NDVI and EVI are used. Therefore, the aim of this study is to compare and investigate the applicability of these indices in detection of VEGETATION changes in different climate and environmental conditions. For this purpose, several test sites in Malaysia, Iran and Italy with different environmental conditions including Tropical, Subtropical and Mediterranean were selected. Then, index differencing method using temporal Landsat-7 ETM+ and Landsat-8 OLI images belonging to the years of 2001 and 2014 were applied. In order to evaluating the accuracy of the output maps, confusion matrix was made to calculate overall accuracy and kappa index. Subsequently, commission and omission errors were calculated to assess nature of the errors in the results. Accuracy assessment analysis indicated that however the results of EVI in some of the test sites were acceptable, but in all of the test sites with variety of weather and environmental conditions, NDVI provided higher accuracy outcomes in detection of VEGETATION changes.