The drying of Lake Urmia has had many environmental impacts on the surrounding areas of the lake. In this research, efforts have been made to identify vegetation coverings that are compatible with the study area and then it use of multiplicative decision-making models for identify areas susceptible to cultivation of these products. In the present study, following the study of species in the region of rapeseed, was selected as a suitable halophytes plant. Initially, using Landsat 5 and 8 images, the changes in the land use type and vegetation cover type of the region were investigated from 2000 to 2016, and after calculating the changes, the potential planting of the halophytes plant was sought. The ANP Fuzzy method was used to estimate the ability to cultivate rapeseed. Main criteria used in this research are topography, soil and meteorology. The topographic sub criteria are included: height, slope and tilt direction, soil criteria including soil texture, soil salinity, and soil pH and soil organic matter. Finally, the criteria for meteorological data are total annual precipitation, Relative humidity, average annual temperature, maximum annual temperature and annual minimum temperature. These layers first be changed to fuzzy and then, applying the weight of each of the following criteria, a map of the main criteria of soil, topography and meteorology was prepared and finally, by combining these three main parameters, the potential mapping was obtained. The results indicate a 25.43 percent reduction in water content and an increase of 21.03 percent in saline areas between 2000 and 2016, and the results of identifying areas susceptible to cultivation of halophytes plants have identified 14.28 percent of the study area suitable for rapeseed cultivation.

Tourism is now considered as one of the most important income industries of the world. Tourism as one of the main and basic approaches can be used in solving problems resulted from unemployment problems and downturn in different countries and the twenty-year vision of Iran specially consider tourism and attracting tourists. The huge volume of the tourists in the world are religious tourists and most of these religious tourists choose Mehran international border for entry and exit from Iran for doing pilgrimage and their religious affairs due to being safe and vicinity to The Holy of Holies in Iraq. This research aims at designing and explaining religious tourism model in Mehran International Border. Having determining the sample size qualitatively via snowball method, 14 experts of religious tourism including academics and trustees of religious tourism were recognized and they were interviewed directly and the research findings showed that religious tourism pattern in Mehran International Border has six main components including casual conditions (religious and tribal communities, provincial infrastructures, common border of Iraq and vicinity to The Holy of Holies, advertisements) categories (tourism and its subcategories, religious places in Iran and Iraq, security) grounds (commercial free zone in Mehran welfare and health services, economic part of religious tourism), interferer factors (political factors, conveying affairs to non-governmental sector, weather changes), strategies (cooperating with educational centers and universities, increasing governmental investing, using capacities of religious days) consequences & results (income and creating jobs, people’s persistence in border and non-immigration, cultural development of province, destruction of environmental, road and jungles of province) which could be introduced as a proper pattern for religious tourism in Mehran International Border according to the opinion of experts.

Keywords: tourism, religious tourism, pilgrimage, Mehran International Border.

Wetland cover classification is of special importance in order to identify the type of plant species inside the wetland and also to distinguish it from the wetland margin vegetation and to study their ecosystem changes.  Due to the spectral similarity between different plant species of wetlands and plants along the wetlands and agricultural lands, this is faced with problems using multispectral data and hyperspectral data can be very useful in this regard. in this study power of hyperspectral and multispectral sensors in identifying the characteristics of the wetland and the ability of ETM + (2011), Hyperion (2011) and ALI (2011) sensors to study the characteristics of Shadegan wetland during 1390 and different spectral indices with a suitable combination of The satellite imagery bands of these sensors were compared as input to a variety of classification methods including maximum likelihood, minimum distance, neural network and support vector machine. The results showed that the support vector machine and neural network methods with closer classification accuracy of 85% in all three images show closer results to reality. The classification accuracy for all three images was at its highest for the backup vector machine method, with a total accuracy of 95.73 for the Hyperion image, 88.03 for the ALI and 89.34 for the ETM +. Therefore, the characteristics considered for the wetland, in the three images obtained from the SVM algorithm showed that showing the differentiation of wetland vegetation use from irrigated agricultural land use is more ambiguous than other wetland features. Studies have shown that this part is less recognizable in ALI and ETM + images than Hyperion images, or in some areas these parts are not separable from aquaculture land at all, while Hyperion due to having 220 bands and having a higher level of Spectral details have the ability to distinguish between the two classes.