Setareh Bagheri; Reza Tamartash; Mohammad Jafari; Mohammad Reza Tatian; Arash Malekian
Abstract
Plain ecosystem is highly vulnerable to environmental changes, and drought is the most famous ecosystem change driver that is difficult to identify after its occurrence. In this research, to study the slope of vegetation changes against drought, the NDVI index of MODIS images and the SPI index from 2001 ...
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Plain ecosystem is highly vulnerable to environmental changes, and drought is the most famous ecosystem change driver that is difficult to identify after its occurrence. In this research, to study the slope of vegetation changes against drought, the NDVI index of MODIS images and the SPI index from 2001 to 2016 were used and the map of vegetation changes against drought with five drought stress classes included very low classes, Low, moderate, high and very high, so that a suitable assessment of the drought can be made at specified time scales. The results of slope pattern of spatial change of vegetation against drought showed that across the plain vegetation changes have declined, and from east to west of Qazvin plain, the slope of vegetation changes and land susceptibility to drought have been reduced. So that the most percentage of area in a one-month drought related to the drought class is very low, but in droughts of 3, 6, 9, 12, 24 and 48 months, the highest percent of the area belonged to moderate and high drought classes. The results of this study, the determination of the level of vegetation changes in against drought in the past years and prediction of these changes in the future years, can be used in the planning and optimal use of resources, control changes in the future.
Leila Yaghamei; Reza Jafari; Saeed Soltani; Hasan Jahanbazi
Abstract
Snow is one of the effective fators on vegetation rate and function in mountainous areas. The aim of this study was to investigate the impact of snow cover area index and snow cover duration index on two declining and dominant plant species including Astragalus adscendens and Quercus brantii in Chaharmal ...
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Snow is one of the effective fators on vegetation rate and function in mountainous areas. The aim of this study was to investigate the impact of snow cover area index and snow cover duration index on two declining and dominant plant species including Astragalus adscendens and Quercus brantii in Chaharmal and Bakhtiari Province from 2003 to 2016. For this purpose, Normalized Difference Snow Index (NDSI) and Normalized Difference Vegetation Index (NDVI) were extracted from MODIS satellite images and compared using Pearson analysis in forest decline regions (Barz, Seveh, Helen and control area) and in rangeland decline regions including Astragalus adscendens decline and control areas. Results showed that about 32% of the snow cover in the study area has been reduced, although a constant trend was not observed. The studied snow indices showed the highest relationships with rangeland and forest vegetation cover in March. The decline region of Astragalus adscendens had the maximum relationship with the snow cover area (R>0.70) and snow cover duration (R>0.71) in March. According to the findings, snow precipitation in late winter season and its duration is more effective on the rangeland Astragalus adscendens species than forest vegetation cover and this pecies can be more sensitive to decline in case of snow reduction.
saeed barkhori; elham rafiei sardooi; mohammadreza ramezani; ali azareh; maryam nasabpoor
Abstract
One of the most important and main components of ecosystems is net primary production, which is an important index for assessing the ecosystems performance in the face of environmental changes. To this end, with regards to the importance of the subject, in this study, to quantify the climate change impacts ...
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One of the most important and main components of ecosystems is net primary production, which is an important index for assessing the ecosystems performance in the face of environmental changes. To this end, with regards to the importance of the subject, in this study, to quantify the climate change impacts on ecosystems, NPP values in Jiroft plain was simulated in two periods (2001- 2015and 2016-2030) using the BIOME-BGC model. To assess change in climatic parameters in future, LARS-WG 6 downscaling model was used. After ensuring the capability of the LARS-WG model to create climatic data, climatic variables were simulated in 2016-2030 under the RCP 4.5 scenario. NPP values in 2001-2015 were simulated using the BIOME-BGC model and validated with NPP data derived from Modis images (MOD17A3) that the results showed high accuracy of the model to simulate NPP. After ensuring the model accuracy, NPP was simulated under precipitation and temperature data in future (2016-2030). The results indicate an increase in precipitation, minimum and maximum temperature in the future period (2016-2030) compared with the baseline period (2001-2015). Also, according to the results, NPP value in future has increased in all biomes that this increase is due to increase in precipitation. There is the highest NPP value in the northern and western parts of the region that is related to biome 4 (with agricultural vegetation), biome 5 and 2 (with rangeland vegetation), respectively, and the lowest NPP value is related to the southern parts of the study area.
Behzad Rayegani; Susan Barati Ghahfarokhi; Ahmad Khoshnava
Abstract
The aim of this study is to develop a comprehensive approach to identifying dust & sand sources and to investigate their changes over a set period of time using remotely sensed data. For this purpose, data OLI data of Landsat 8 during the years 2013 through 2015 were used to make maps of vegetation ...
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The aim of this study is to develop a comprehensive approach to identifying dust & sand sources and to investigate their changes over a set period of time using remotely sensed data. For this purpose, data OLI data of Landsat 8 during the years 2013 through 2015 were used to make maps of vegetation cover, soil moisture and land cover sensibility to wind erosion. These maps were combined with geology and roughness by multi-criteria evaluation method to obtain a map of sand & dust source potential areas. In the second step, information of synoptic stations, meteorological and air pollution measurements was prepared, and using statistical analysis and with the help of Modis data, the history of local events was obtained. These regions were integrated with the map of sand & dust source potential areas using the MCE method (WLC) and based on a stratified random sampling plan, susceptible sites of sand & dust sources were identified. In order to validate the identified areas and investigate the trend of their changes, the time series of satellite data and weather stations data were used and the trend of vegetation, soil moisture and surface temperature at the location of identified areas during a 15-year period were monitored. Validation results show high accuracy of identified areas and significant reduction trend of vegetation, soil moisture and surface temperature in the locations of identified sites during the study period
Fatemeh bahreini; Fatemeh Panahi; Mohammad Jafari; Arash Malekian
Abstract
The complexity of drought phenomenon hinders our full understanding of its impact. Field sampling, Geographic Information Systems, SPI and NDVI, EVI and SAVI indices derived from 16-day interval MODIS images during 2000-2015 were used to better understand the effects of drought on vegetation In recent ...
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The complexity of drought phenomenon hinders our full understanding of its impact. Field sampling, Geographic Information Systems, SPI and NDVI, EVI and SAVI indices derived from 16-day interval MODIS images during 2000-2015 were used to better understand the effects of drought on vegetation In recent study, ground true map was prepared by sampling and field surveys and vegetation cover data was obtained from 32 sampling units in 320 plots over the entire study area. Then, the correlation between field sampling data and vegetation indices was estimated and vegetation cover models were produced for different indices. In this study, precipitation data of 14 stations within and around the study area were used and SPI was calculated at the same time scales with the vegetation indices to study the effect of drought on vegetation. The results showed that NDVI has had the highest correlation coefficient (R2=0.56) amongst the indices so it was selected for vegetation cover percentage mapping. Investigating NDVI rates and drought index in different temporal periods, 9-month SPI was found to have the best correlation with NDVI. On the basis of SPI analysis, it was found that the study area had the most severe drought in 2012 and the best wet condition in 2004. The similar trend was observed in NDVI. The comparison of classified images between 2004 and 2012 (with 42 % changes in poor vegetation) indicates the effect of drought on vegetation in the study area.
