Migration is among important issues that less developed and developing countries have confirmed during the recent five decades. This issues in Iran has attraced a lot of researcher and planner views. Irregular and increasing migrations have created a lot of consequences for cities and the target settlements, social effects of migration on the cities is among such consequence these, in this project, ethnocentrism, linguistic diversity and conformance quality are considered among the city's residents. This issue has been studied in Takestan Qazvin. For illustrating the issue, theories of Michael Todaro, Edward Sapir, Benjamin Whorf and William Samner have been used. The research has been done according to library methods (documents) and field methods (special for questionnaires and measurement).In addition to confirming the questionnaire by the experienced faculties, its reliability has been obtained in accordance with Cornbrash’s Alpha coefficient by 82,2 percent and the SPSS software is used for analyzing and processing. The result obtained by analyzing questionnaire filled in by 400 people that the number has been chosen according to Morgan's Table, and the people have been chosen randomly, shows that there is a meaning full relation ship between ethnocentrism and linguistic diversity with development of the city. 

A most important part of the world’s tourism activities is based on the use of nature and areas having valuable natural potentials. one most considered in this regard the aim of this research is priorititing the affecting factors on development of ecotourism in villages of Barzok district. As a need for tourism planning. The research method is descriptive – analytical And Results are combined using ANP and DEMATEL methods. MATLAB and Super Decisions software used for Results analysis. The results show that among the 17 criteria participate of local and regional investors and giving respansibilitis of Assignment, Tourism organizating and managment to local people have the highest score and stand in the first rank. Visiting tours, especially during Rose water production and during growing season of Medicinal Plants and the use of local and interested people as a tour leader and stand the second and third respectively.

The aim of this study is to retrieve land surface temperature (LST), air temperature (AT) and precipitation and to study their relationship with vegetation in rang lands of Karun watershed of Khuzestan province. For this purpose, land surface temperature (LST) and NDVI was drived from NOAA-AVHRR for maximum amount of greenness (April) for a period of 27 years. In order to extract LST, Price algorithm was used. Also air temperature and precipitation were interpolated for selected weather stations using IDW method. Spatial correlation outcomes (on 0.05) between NDVI with LST and air temperature show a reversed relation. This spatial relation is stronger for LST, so that this coefficient is often upper than 0.6, while seldom is 0.4 for air temperature and precipitation. Spatial regression models show that 62 percent of NDVI changes is determined by LST (R²=0.62) and air temperature and precipitation determine very limited amount of NDVI dynamics.

In recent years, the severe fluctuations in precipitation have affected various parts of the country. On the southern coasts of the Caspian Sea, precipitation as one of the important climatic parameters has undergone changes due to global climate change. In the present study, we tried to evaluate the effect of climate change on rainfall in this region by applying a suitable model. In this study, observational period rainfall (1961-2001) was analyzed. the output of the HadCM3 model was used. At first, seven synoptic stations were selected and their data were analyzed in terms of accuracy, and length of statistical period, and lost data was restored. The AOGCM data were simulated using the SDSM model and the rainfall values were simulated for the observation period. After confirming the matching of the simulated data with observational data, the values of the Future (2039-2011) is estimated. The estimation errors of the SDSM model were calculated monthly by MBE and MAE criteria, and then compared. The output of the SDSM model was used to study the total annual precipitation in days with rainfall of more than 1 mm in the observation period and the upcoming period (2011-2039) by the R-Climdex model and the values of the PRCPTOT index Became zoning in the Future. The results showed that the model error in season with high rainfall is more than seasons with low rainfall. On a monthly scale, the maximum error occurred in the months of September, October, November and December. The maximum error in the fall and the minimum error was calculated in the spring and April and May months. According to the results, the total annual rainfall in the period of 2039-2011 will decrease in Anzali, Babolsar, Gorgan and Noshahr stations and rainfall will increase in stations of Astara, Ramsar and Rasht. Geographical distribution of selected were 5 sites in the Khuzestan, 20 sites in Bushehr, 24 sites in Hormozghan and 12 sites in Sistan and Baluchistan provinces. In total, 9000 sites were selected with a 2 km2 were suitable for large scale microalgae cultivation. The total area of these sites were estimated to be 18000 km2. The highest number of proper sites were found in Hormozghan province and lowest numbers of sites were found in Khuzestan province. The availability of technical service, carbon dioxide point resources from oil and gas units are an advantages for microalgae related activities in the Bushehr and Khuzestan provinces. The higher quality of water in the Sistan and Baluchistan province is an advantages for development of microalgae biomass production in the area.
 

Remote sensing technology is one of the most efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is known as a new method of satellite image processing which integrates spatial and spectral information for satellite image process. This approach make use of spectral, environmental, physical and geometrical characteristics (e.g. texture, shape) together images contexts for modeling of land use/cover classes. The main objective of this study is to classify micro land use/cover of Meyandoab County by applying appropriate and effective algorithms and parameters in the object based approach. For this goal, Quick Bird and Aster satellite images were used within the integrated approach for processing and land use modeling. Accordingly, the land use map was classified in 9 class based on spectral and spatial characteristics.  In order to perform OBIA, the segmentation was applied in the scale of 10, shape parameter of 0.7 as well as the compactness of 0.3. In terms of the classification task, fuzzy based algorithm and operators (AND, OR) was applied to detriment the membership functionality of segments for each class as well as classifying the related objects.  We also applied textures, geometric, NDVI, GLCM, brightness algorithms based on fuzzy operators and assign class algorithm. In order to applying the validation of results, the accuracy assessment step was performed and the finally overall accuracy of 93.6 was obtained for the derived map. The Kappa coefficient was also detriment to be 0.92. The area under cultivation included respectively for lands of wheat and barley, prunes and plums, apples, vineyards and alfalfa hay2622.42, 4505, 4354.55, 4457.85, 14110.58 hectares.
 

Paleo-climate reconstructions based on multi-proxy such as sedimentology is current in climatology investigation. In this way, National Institute of Oceanography and Atmospheric Science cored 960cm from Arzhan wetland SW of Iran than we have investigated of sedimentology. Primarily the core was measured on magnetic sensibility per 1_cm and secondly was subsampled according to magnetic sensibility and were analyzed include TOC, CaCO₃, and Grading laser and etc. Finally four samples of pace of plant were selected and have been dated in carbon 14 dating laboratory of Poznan, Poland, and calibrated trough of core based on Calib rev. 7.1. Dating have determined that core had covered 15000 Cal. BP. According to this investigation, we obtained 5 period of climate conditions during Pleistocene to Holocene in this area. 15000-13000 Cal. BP. Late Pleistocene climate conditions were colder and wetter period that indicate end of the Ace age.  13000-11000 Cal. BP. Climate begin to warmer and dryer. 11000-9000Cal.BP. because of this period shows many fluctuations in all proxies we named this period to the period of transfer from ace age to interglacial period. 9000-7000Cal. BP there have been warm and cold conditions compare to late Holocene. 7000- Present indeed in this period radiantly modern pattern of atmospheric circulation has been performed due to all of proxies in late Holocene begin to fixed on the same pattern. So probably atmospheric circulation from meddle Holocene begin to get harmonic to present. Any way for determinate of paleo-climate in this area we need to use of multi proxy investigation in area.
 

Survey of advection of cold waves in Iran is the main aim of this study. In this regard, 45 synoptic stations were employed and studied. In order to investigate the thermal advection of cold waves, 1000, 850, 700 and 500 hp levels were reviewed and analyzed. Results indicated that cold waves in Iran most affected thermal advection caused by Tibet- Siberia, Siberias integrated Turkmenistan high-pressure, High pressure belt of Siberia - East Europe High pressure, Siberian high-pressure multi-core pattern and High-pressure belt of East of Caspian Sea integrated Black Sea High pressure. In the meantime, thermal advection of Siberian high pressure has been more impressive than other patterns. This system moved towards lower latitudes by anti-cyclone moving, So the cold weather of northern latitudes loss in lower latitudes North East of Iran, North West and Central parts of Iran. However, when Siberian high pressure combined with other patterns, its role in the advection of cold air have been considerable

Human thermal comfort and discomfort of many experimental and theoretical indices are calculated using the input data the indicator of climatic elements are such as wind speed, temperature, humidity, solar radiation, etc. The daily data of temperature، wind speed، relative humidity، and cloudiness between the years 1382-1392 were used. In the First step، Tmrt parameter was calculated in the Ray Man software environment. Then UTCI and PMV index values were calculated using Bioklima software. The results showed that the most severe cold temperature stress on PMV index is in the winter and late autumn and UTCI index in January and February are the coldest stress. The power of neural networks, prediction of future performance network (generalized orientation) it simply is not possible and the new model presented in this paper have been restricted Boltzmann machine-based neural networks or neural networks is used deep belief. Using this structure, metrics Mean Squared Error (MSE) and mean absolute percentage error (MAPE) benchmark ate for seven indexes derived from data gathered by three factors related to the occurrence of weather conditions and other indicators of thermal comfort of human the system was evaluated. Assessment by dividing the data into training and testing parts, and the ratios have been of two-thirds, fifty percent and one-third And two benchmark MSE and MAPE were calculated. The proposed system performance in forecasting the human thermal comfort is desirable.