فصلنامه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی
سال هشتم شماره 1 (بهار 1396)

Study of the long term dynamic of the lake is crucial to evaluate regional water resources management and environmental changes. The main aim of this study was to evaluate and mapping the impact of climate change in the dynamic of the lake Maharlo located in the boundary of Shiraz city. Landsat satellite images during the past 18 years (1997-2016) in mid-spring were used to determine dynamic changes of the study lake (After geometric, radiometric and Atmospheric correction of satellite images, the annual lake level was extracted using a thresholding method on the band 5 and NDWI index. The results show that, a general reduction trend was observed in the lake area. Most of the changes were occurring in the eastern part. The correlation between water level changes of the lake with some of the climatic parameter changes (evaporation January to May, annual rainfall, average temperature January to May, the average maximum temperature January to May) was also investigated). According to Pearson correlation coefficient between the lake level and evaporation of the months of January to May, annual rainfall, the average temperature of January to May, maximum temperature of the months of January to May were -0.44, 0.77, -0.28, -0.52, respectively. A significant trend was observed between rainfall change (decrease and increase) and lake level. Minimum annual rainfalls were 147 and 192 mm in the years of 2007-2008 and 2008-2009, respectively, which minimum lake level was observed in the same years (14146 and 15095 hectares). The maximum rainfall was occurred in 2004-2005 (745 mm) when the maximum water surface was measured in the lake (25806 ha). According to the results, 58% of the variability of the lake could relate to rainfall change.

Land degradation and desertification has intensified by the interaction of climatic factors, land use change and human pressure in recent decades. Awareness that desertification is taking place in which ecosystems, the most important step to control and deal with this phenomenon. The aim of this study was to determine sensitivity to desertification Lorestan province ecoregions using life cycle assessment. For this purpose, the study area was classified into six ecoregions in terms of climate and dominant type of vegetation. Then selected indicators of drought, water erosion and excessive extraction of groundwater as the evaluation criteria. Indicators were prepared using geographic information systems. Finally, combined with variable selection and ecoregion map. Calculation of the characterization factors for each of these factors using geographic information systems, and characterization factors were obtained from the sum of the factors, a total characterization factor. Results indicated that there is the greatest sensitivity 5 ecoregion (dry/Astragalus adscendens Boiss) with characterization factors 1.29 and the lowest sensitivity to desertification 1 ecoregion (dry sub humid/Quercus brantii) with characterization factors 0.29. The results showed that aridity with 2.69 value, is the most effective factors to increasing the sensitivity of the area to desertification. Therefore, should pay attention serious to this problem in planning, managing and Combating desertification.

The present study aims to improve the assessment, soil salinity accuracy, using of OLI Landsat satellite image dated to 26 May 2015 and topographic parameters in the eastern region of Isfahan. Ground data were collected in date second half May by using the random sampling method from 29 sampling sites from the depth of 0-30cm. Spectrum indexes include OLI sensor bands, salinity indexes SI1, SI2 and SI3, soil indexes SBI and SCI, and vegetation indexes NDVI and RVI were obtained from processing referenced ground images. Also, topographic feature including slope percent, orientation of slope and elevation from sea level were extracted from Digital Elevation Model (DEM), then to estimate the salinity linear regression the stepwise method model was used. From analysis, regression indicated that on 99% statistical level, there is a meaningful correlation between EC of topsoil samples, elevation from sea level and band 4 (R2=0.68). The salinity map acquired from the regression model indicates the salinity is very high in the region so that more than 70% of the area has a salt concentration of more than 60 ds/m. Finally, the reliability of the model was evaluated using 20 percent of the samples. Results indicated that the model can estimate soil salinity by an RMSE=6.54 ds/m. According to the research results, Conclusion They are using elevation from sea level parameter with satellite data is Beneficial in the soil salinity research and causes improve the accuracy of the assessment.

The aim of this study evaluates the use of satellite images to change detection in coastlines and evaluate the use of optimum index and the modified normalized difference water index (MNDWI) in examining changes coastline in Dayyer city. As well as for the evaluation of coastline change in the study area, 8 points were taken on April 24th, 2015 along the coastline city of Dayyer with regard to access to the beach, coinciding with the passage of the Landsat satellite, OIF index with a standard deviation and correlation, the correlation between bands is determined. MNDWI index, a combination of green and mid-infrared bands is to determine the boundaries between land and water is suitable. The results show, given that coastal study area and satellite imagery, the highest of OIF for OLI sensor is obtained RGB 156 composition. Also, the algorithm MNDWI is ideal for discriminating between land and water. The average distance from the baseline to the border extracted from the optimum index is 340 meters and the average distance from the baseline to the border extracted from the MNDWI index is 64.28 m is obtained. The results showed to check coastline changes in Dayyer city, MNDWI index is more accurate than the optimal index.

Renewable resources which are good alternatives to non-renewable fossil fuels have caused communities to take an interest in energy sources such as solar energy. The purpose of this study is site selection suitable areas for the construction of solar power plants in Fars province based on meteorological and climatic parameters. In this research precipitation, temperature, relative humidity, sunshine hours, elevation, dust, aspect slope parameters was used. According to the importance and role of these factors, the statistics of parameters were analyzed and each criterion map was prepared in GIS software. All layers the IDRISI software was fuzzy. Finally, the location map of suitable areas was produced based on obtaining weights the method Fuzzy-AHP and results in four classes (excellent, good, medium and poor) were classified. The results of site selection solar power plants showed that the north and northeast parts of the province have more potential with an area more than 60% of the total area of the province while the southern parts of the province with an area totaling almost 0.026% of the whole area of the province have the least potential. The most area of the province in terms of potentiality for solar power plant is in an excellent category. In addition, climatic results indicated that the potential regions for constructing solar power plants are those with a dry and semi-arid climate where stations like Abadeh, Izadkhast, Bavanat, and Safashahr are located.

Soil is a non-renewable and dynamic resource that the improper land use and management, is susceptible to degradation. Soil salinity one of the important land degradation factors in arid and semi-arid region. Identification and mapping of saline soils often due to temporal and spatial variability, and the need for sampling and laboratory work is difficult. In recent years remote sensing technology, due to the ability to identify phenomena has always been of interest to specialists. Information that obtained from satellite images contributed greatly to the study of various phenomena and can be very helpful in detecting phenomena changes. Case study, Aji Chay river delta was selected that is located in the west of Tabriz city and east of Urmia lake, because this region's importance in terms of agricultural and ecological. In this study used ground data and OLI sensor images from Landsat satellite during 2015, and field sampling was taken at the 5 and 6 August 2015. This data used for study and evaluation, soil salinity indexes. With a significance level analysis and measure study between ground data and output of models, best salinity index selected and extraction soil salinity map. In this index, SIT index has the highest correlation (97%) and presented as best index for salinity study in this region that salinity maps extraction from this index. SI2 index with 52% correlation has lowest correlate between salinity index and ground data. In the study region most areas included very saline class with 42% of the total area.

Many countries in the world are facing the crisis caused by scarcity of water resources. One of the strategies for coping with this crisis, which is considered a suitable way of restoring fresh water resources, is construction of water desalination plants. However, despite the numerous advantages of desalination plants, their effluents have undesirable effects on the environment. The present research intended to locate suitable sites for constructing water desalination plants by taking into account the environmental sensitive zones. After developing the layers in a geographical information system, a distance map of each layer was developed. Criteria were weighted during the Delphi process. The geographical layers of each criterion were evaluated and classified in five categories. The layers of the criteria were normalized based on the coefficients of importance, integrated during their linear application, and reclassified in five categories. Nineteen suitable sites were identified for construction of water desalination plants by integrating the layers and through preparing the final layer. By reclassifying and reevaluating the final map, 2 high important locations, 7 important locations, 5 Middle important locations, 4 less important locations, 1 unimportant location. 2 high important locations were located in the coastal areas of the Bandar Abbas City. 16 were located in the coastal areas of the Persian Gulf, and three were in the coastal areas of the Sea of Oman.

The aim of this study was extensive ecotourism modeling in the Venaii Basin of Boroujerd County in Lorestan province. Also the determination of suitability classes, delete of barriers to the suitability and the priority of affecting factors on suitability were second aims. This study was conducted in 2015 based on literature, questioner and field data. At the first affecting factors on ecotourism ware ranked by Analytical Hierarchical Process (AHP) according to standard questionnaire, tourism comments, expert view points and literature review. Then incorporated and combined spatial and attribute layers corresponding to each factor such as topographic maps, satellite images, sharing date by county officials and basic maps in ArcGIS®9.3 software. Investigated factors fall into two main categories physical and non-physical. Totally 12 factors investigated according to kind of extensive ecotourism and then prepared maps based on priority. Results show that two main factors have equal value based on AHP method. Additionally, results pointed out that in physical factors, soil sensitive is the most important factor and road accessibility is less significant with 0.22 and 0.01 ranks respectively. Inconsistency was 0.4 that show logic comparatives. There was no difference priority between plant and animal diversity and land uses in non-physical factors in which show had equal indexes. Regions categorized into three sections based on the FAO method from very suit (S1) to low suit (S3). In addition, this study result appears practically useful for the development of tourism facilities and ecotourism resource utilization: First, for the highly suitable areas with S1 class (2150 ha, 36.66%), most of which are located in the mountain areas characterized by slopes and height. Low suitable in some part of the area which located on hills and low height was about 1235 ha (21.07%). Because of extensive ecotourism there was no any limitation to develop. Overall must attend that village development and decrease of plant cover cause negative effect on diversity and the degradation of nature and also region pollution. This unusual development cause less potential ecotourism in the future that must decision making. On the other hand, if create a shelter in suite location middle of the way to pick it will encourage to climbing.