Fatemeh Hadian; Seyed Zeinolabedin Hoseini; Mansoureh Seyed Hoseini
Volume 21, Issue 4 , March 2015, , Pages 756-768
Abstract
Precipitation is one of the factors affecting vegetation. Nowadays, satellite images are broadly used for monitoring the effects of precipitation variations on the vegetation changes. The aim of this study was to investigate the relationship between vegetation dynamic and precipitation variations using ...
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Precipitation is one of the factors affecting vegetation. Nowadays, satellite images are broadly used for monitoring the effects of precipitation variations on the vegetation changes. The aim of this study was to investigate the relationship between vegetation dynamic and precipitation variations using NOAA AVHRR images during the period of 1982-2006. Precipitation maps were created using the inverse distance weighting interpolation (IDW) method and time intervals of precipitation data. The study area was a forestland beside Caspian Sea, four rangeland vegetation types with grasses and shrubs, farmland areas and urban areas, located in Ardabil and Guilan provinces. To monitor the relationship between the precipitation and vegetation changes, the linear regression (NDVI, Y & Rainfall, X) method was employed. Based on the results, depending on the precipitation time, plant species, and growth form, the effect of precipitation on vegetation was different so that no significant relationship was observed between vegetation and precipitation in forestlands, farmlands, and urban areas. The highest correlation coefficient between spring precipitation and vegetation was related to the rangelands. In grassland areas, the correlation coefficient was higher than that of shrublands, whereas the reaction of grasslands to precipitation in various parts was different.
Fatemeh Alishah Aratboni; Hosein Arzani; Seyed Zeinokabedin hosseini; Sasan Babaie Kafaki; Khosro Mirakhorlou
Volume 20, Issue 3 , November 2013, , Pages 454-462
Hamid reza Moradi; Mohammad reza Fazel puor; Hamid reza Sadeghi; Zeinalabedein Hoseini
Volume 15, Issue 1 , January 2008, , Pages 1-12
Abstract
More than one-third of land in the world is located in the areas with arid and semiarid climate and desertification has increased in these areas during recent decades. Around 80% of Iran is located in arid and semiarid areas. Sand dunes as an indicator of desert land cover an area about 32 million hectare. ...
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More than one-third of land in the world is located in the areas with arid and semiarid climate and desertification has increased in these areas during recent decades. Around 80% of Iran is located in arid and semiarid areas. Sand dunes as an indicator of desert land cover an area about 32 million hectare. Among which 12-mil hectare has not been stabilized yet. Advancing moving sand dunes has resulted in much damage to agricultural products and urban areas. In this survey satellite images and aerial photos are used to evaluate the role of land use changes on desertification in 1955, 1997 and 2002. To do so, IRS image of 2002 and available aerials photos of 1955 and 1997 are used. Following making the aerial photos mosaic processing was done using ILWIS software and needed data completed by field surveying and the land use map was produced for two years. To produce the land use map using digital processing methods 10 sample set (training points) were selected uniformly in the area. After preprocessing including geometric corrections, image enhancement and band composition, image classification was done by maximum likelihood method and the land use map was produced. In this phase, obtained land use map was corresponded to the ground truth map which was achieved by field surveying and recording coordinate of points with GPS pixel to pixel and accuracy obtained from numerical classification estimated to be 45.3%. Then due to obtained low accuracy, the visual method used to produce the land use map so the accuracy of 78.5% achieved. Finally, the area of each land use and the rate of changes were calculated. The results indicate a decrease of 2000 ha in the area of the desert land from 1955 to 1997 and of 160 ha from 1997 to 2002 and an increase in the area of the other land uses. Results show no desertification in the study area, even though land degradation can obviously be identified in the area, which is resulted from the changes of gardens, and agricultural land uses to industrial and urban areas.
Khosro Mirakhorlo; Zein ... Hosseini
Volume 13, Issue 2 , February 2006, , Pages 127-138
Abstract
Estimating rangelandsۥ production is one of the range management tools. This requires detailed information about the present available forage of the rangelands. The assessment of the parameters is difficult and cost-intensive using clipping method. Therefore, new estimating methods are required. We ...
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Estimating rangelandsۥ production is one of the range management tools. This requires detailed information about the present available forage of the rangelands. The assessment of the parameters is difficult and cost-intensive using clipping method. Therefore, new estimating methods are required. We estimated available forage using remote sensing data in the production model that it extracted from ecological parameters and remote sensing data. For quantifying evaluation of vegetation cover stratified random sampling and transect sampling methods were selected. Plot size calculated from “minimal area and species curve” method. Overall, 28 transects (50m) one transect in each site that contain 280(1m2) sample plots were measured. Modeling performed using NDVI index, animal density and effective ecological factors (altitude, slope, aspect, precipitation, temperature and evaporation) on rangelandsۥ yield. After analyzing of ecological factors of Damavand region, some ineffective factors omitted. Finally three factors namely slope, precipitation and NDVI index were entered in the model for calculating the available forage in the study area. The calculated amount of average standard predict value of forage model is 38% and its standard deviation value is 97%. They show that the validation of model for predicting of forage is fairly acceptable.