فصلنامه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی
سال پنجم شماره 2 (تابستان 1393)

Astragalus gossypinus Fischer is one of the most important range plants in west region of Isfahan، which is very critical for soil conservation and people''s economic life. Nevertheless، the grazing pressure and overuses cause habitat destruction. This study has been done for determination of its potential habitat in Lenjan and Flavarjan parishes of Isfahan province. To achieve this purpose، spatial data of this specie''s presence used as suitable places for its growth and the environmental condition (Climate، Soil & Physiographic) used for recognition of its habitat''s necessities. Soil data turned to soil maps using antecedent studies and interpolating soil profile points. Climatic and physiographical data have been prepared as well and got ready to be imported to the ultimate model. By importing the information layers in ENFA model and using harmonic mean analysis in Biomapper software; the map of Astragalus gossypinus potential habitat has been created. The results show that gravel percentage، soil potassium، saturated moisture، electrical conductivity and annual precipitation are the most important factors in habitat choosing by Astragalus gossypinus in study area. 25300 hectares of the study site are potential habitat of Astragalus gossypinus which is 16 percent of the study site. To evaluate the verity of this model، Boyce''s index has been used and model rectitude in this test was determined 85. 2 percent.

Landscape includes a mosaic of landscape elements in a context of a major land use/cover. Much emphasis has been placed on developing methods to quantify landscape patterns in recent years. Landscape elements include various types, including urban areas and patches, which were used for change's identification in the current study. Any urban area has been considered a landscape patch and their patterns for the Gorgan city between the years 1987 and 2001 have been compared in this study. Number, shape and neighborhood metrics was the major groups of metrics calculated. To do so, urban areas were fed to Fargstats Software as patches. Comparison showed that development pattern in Gorgan city has led to the creation of larger and simpler patches with and less fractal dimension during the 14-years period of our study. In fact, urban growth was shown to be adhering to the previous urban patches. This is also visible to the spatial investigation of the largest patches (a complex of continues areas), such that, for example, two large patches in 1987 had been joined because of infill. Despite the tendency of urban growth around previous urban patches and in their vicinity, patches did not show a uniform distribution in the area, rather, they were irregular. This result is confirmed by the fact that the urban area has increased 2.1 times during the study period.

Selecting an appropriate sample size is quite important to achieve acceptable accuracy in evaluating vast natural areas with field and remote sensing methods. This study aimed to evaluate the effect of different sample sizes on the correlation of vegetation cover and remote sensing based indices such as NDVI in three rangeland types, Semirom-Isfahan. Landsat5 (TM sensor) and IRS-P6 (AWiFS sensor) satellite images were used to conduct this research. The percentage of vegetation and ground cover components including canopy cover, litter, rock, gravel, stone and bare soil were determined using step-point method in 4 radial direction in 30, 50, 100 and 150 meters (1200, 2000, 4000 and 6000 points per rangeland type). In other words, the ground cover and NDVI indices correlations were compared in 2826, 7850, 31400 and 70650 square meters using the satellite images. NDVI indices were calculated in all vegetation types and correlated with different components of ground cover. According to results, TM sensor data had more appropriate correlation than AWiFS sensor with field vegetation cover in all studied sample sizes. Vegetation cover and NDVI correlations were decreased in degraded vegetation types with increasing ground heterogeneity. For example, the correlation was not significant (p<0.05) in all studied sample sizes in degraded Astragalus spp-Scariola orientalis vegetation type, while the highest correlation was obtained (77%) in 7850 square meters sample size in more homogeneous Bromus tomentellus vegetation type.

Albedo is determined in new and old method based on SEBAL algorithm. In the new method that has been used since 2004, the extracting albedo was based on the experimental models. To determine the albedo of the object to the surface in large-scale and with consideration of the varied topography at the surface, the measurement of object's albedo was impossible, thus they should use remote sensing methods. In this research, the surface albedo was determined by use of ETM+ and MODIS images and tries to compare the obtained results from these two devices in various land uses. To determine the abode, we used the following programs, ERDAS® 9.1 and ArcGIS® 10.1. The result of study shows the average albedo in agricultural land extracted from ETM+ and MODIS images are 0.186 and 0.344, respectively, that the lowest, between all land use categories the highest albedo belonged to watercourse land use with the 0.242. Furthermore, the minimum albedo in follow agriculture in the ETM+ and MODIS image was 0.088, 0.274 and 0.374, 0.464 relatively. By determining albedo in different land use, we can determine the difference between net received energy and use it as one of the factors in determining the evapotranspiration with using the METRIC or SEBAL remote sensing algorithm.

The main aim of this study was the evaluation of the Forest Canopy Density model (FCDm) for prediction of forest canopy density, using Landsat-7 ETM+. The study area was the eastern part of Marivan city that situated in Kurdistan province. A Landsat image was geo-referenced with sub pixel accuracy. First, all bands (1-5 of ETM+ imagery) except band 6 was normalized and then four main indices of FCD Model, including Advanced Vegetation Index, Bare soil Index, Shadow Index and thermal Index was calculated, and the forest canopy density map was derived finally. Forest's canopy densities according to 6, 4 and three classes were classified. To assess the accuracy of classified maps, a ground truth map using aerial photos with the scale 1:20000 was produced. The overall accuracy and kappa coefficient for classification 6 and four classes were obtained equal to 52%, 0.29 and 53%, 0.30, respectively. Spectral similarity between open density classes and irradiance of background soil in these classes reduced the accuracy as the result. Actually, in the dense forest, the result will be more accurate. According to the results, this method could be relatively desired for Zagro's forests.

The goal of this paper is reviewing and comparing of Shadegan international wetland changes during last two decades. To achieve this goal, the trend of changes in Shadegan international wetland and the relative consequences were examined by supervised classification of LandSat satellite images. For this purpose, maximum likelihood algorithm, in ENVI®4.8 software was utilized during 20 years period (1990-2011). WRASTIC index, one of the existing methods for evaluating risk and vulnerability of the surface water, was used for finding inflow water quality to the wetland. Results of this study show six percent decrease in area of Shadegan wetland during these years, about 1796.61 Km2 (25.71%) declination in water and soil areas, and by 1796.76 (9%) increase in the total area of vegetation cover. Growing vegetation cover denotes water pollution, eutrophication, and early devastation of this international wetland. A result of calculation WRASTIC index showed that wetland basin components have the great impact on pollution of inflow water to wetland. Continuing of this trend, make irreparable effects on this existence and integrity of this wetland.

In this study, the effect of urban reforestation on carbon sequestration in arid soils was evaluated, using the Quick Bird satellite image. Soil samples were collected (0-15, 15-30 cm) from the field visits and soil organic carbon content of the samples was measured. Correlation coefficients between the satellite bands and vegetation indices with the results obtained from the analysis of geospatial data and data analysis using regression method, the best fit model for preparation the soil carbon sequestration maps were obtained. The results of verified analysis showed the accuracy of the produced maps and corresponded well with the ground sampling points. The survey maps prepared to show that the reforestation on barren land area in Isfahan is caused of increased carbon sequestration in the dry land soil. Furthermore, a higher rate of carbon sequestration in the surface soil layers and decreases with increasing depth. Depending on the species planted in soil, the rate of carbon sequestration is varying. Soil carbon sequestration in areas that have been cultivated conifers species is greater than the hardwoods species.