جستجوی مقالات مرتبط با کلیدواژه « Pearson Correlation » در نشریات گروه « علوم انسانی »

The purpose of this research is to investigate the temporal changes and spatial distribution of the total cloud cover of the sky in the Ormia Lake drainage basin. In order to achieve the goals of this research, observational data on total cloud cover of the sky at five selected meteorological stations and the product of total cloud cover of the sky (CFFCM) from MODIS sensors (Tera and Aqua) were used. The observed cloudiness values according to the ICAO standard were classified into five classes: cloudless sky, slightly cloudy, partly cloudy, semi-cloudy, and full cloudy, and the sky cloudiness changes were investigated. Pearson's correlation test was also used in order to investigate the relationship between the total cloud cover of the sky and the elements of precipitation, temperature, evaporation, and sunshine hours.The findings of the research showed that in the study area, the sky is mostly clear (28.7%) and slightly cloudy (23.9%), and only about 30% of the cases are semi-cloudy and full cloudy.In the examination of the frequency of occurrence of each of the cloudy classes, it was found that, in most cases, there was an increasing trend in the clear and slightly cloudy classes and a decreasing trend in the semi-cloudy and full cloudy classes.The study of the correlation coefficients between the total cloud cover of the sky and climatic parameters showed that there is a direct and significant relationship between the cloudiness of the sky and annual precipitation and an inverse relationship with temperature, evaporation, and sunshine hours, which is weaker in the case of annual temperature than the rest of the parameters, and also that the relationships established with observational data are more logical than those established with those established with satellite data. Investigating the spatial distribution of average seasonal cloudiness showed that cloudiness in winter and autumn is different from spring and especially summer. The highest amount of winter (summer) cloudiness is observed in the southern (northern) half of the Ormia Lake drainage basin, and this arrangement is consistent with the seasonal synoptic currents and the distribution of altitudes.

The aim of the current research is to investigate the relationship between the dimensions of a smart university in the development of knowledge-based systems in Islamic Azad Universities in Tehran. This applied research was used to collect data from the field method and from the point of view of the implementation method, it was of the collaborative type. The statistical population included in this research includes the faculty of the Islamic Azad University of Tehran, and 120 people were selected as the sample size using the Karjesi and Morgan table and the relative random sampling method. The data collection tool of this research was a research questionnaire. The validity of this questionnaire was calculated by approved experts and reliability through Cronbach's alpha coefficient. For data analysis (Kolmogrof-Smirnov, Pearson correlation coefficient and regression) using spss26 software was used. The results showed that there is a relationship between the dimensions of a smart university and the development of knowledge-based systems.

Intra-urban air pollution is a major environmental and public health concern worldwide. As the capital of Iran, Tehran is increasing its population day by day, and it has caused problems such as air pollution, and its severity is subject to change every year. The aim of this study was to find a relationship between Remotely Sensed Indices with pollutants and air pollution modeling in Tehran. Pearson correlation coefficient was used to investigate the relationship between independent variables and pollutants and multivariate linear regression model was used to model it. Independent variables in this study are Land Surface Temperature (LST), Normalized Vegetation Difference Index (NDVI), Apparent Thermal Inertia (ATI), and Normalized Difference Built-Up Index (NDBI). The data obtained from Landsat 8 satellite images and MODIS sensor were used. Moreover, air pollution parameters were CO, NO2 and SO2, which were prepared in two spring (April) and summer (August July) of 2017. ENVI, ArcGIS and SPSS software were used to analyze the images and evaluate the relationship between the Remotely Sensed Indices and air pollutants and modeling. The results showed that the highest correlation between LST and SO2 is in the spring (0.24), NDVI and SO2 is in the spring (-0.36), ATI and CO is in the summer, and between NDBI and SO2 is in the summer. Also, the results of the model for the statistical coefficient of determination (R2) showed a value between 0.33 and 0.8, and for the statistical root-mean-square error (RMSE) showed a value of 5.05-47.47. It was also found that NDVI and LST are inversely related, and that NDBI was indirectly related to air pollutants.

In this study, the sudden heating of the Sunsphar, using NCEP/NCAR analysis data, was investigated in the statistical period of 1948-2020. The results of the analysis showed that the abundance of sudden heating events in February is 17 % more than other months. After calculating the intensity of the heating, it was found that in 2018-2017 heating, the average orbital component of the wind reached -48 m / s and the negative values of this quantity continued; This heating has been identified as the most severe sudden heating in the statistical period. The correlation between the changes of the orbital component of the wind is the time of the end of the final heating in all the years under the study of -0.6, which means that the higher the standard deviation of the wind orbital component data, the sooner the end of the cold season and the final warming. The correlation rate of the two winter heating and the final heating with the main heating intensity is -0.8 and indicates a strong and reverse relationship between the two parameters and indicates that the more intense (main) winter warming is more severe, the final heating occurs earlier and the distance The two main heating and the end are less

In recent decades, the excessive use of groundwater resources has led to a drop in groundwater levels in most plains of Iran. To this end, the use of remote sensing techniques has recently expanded to study the fluctuations of groundwater levels. GRACE satellite data is a valuable new tool for groundwater monitoring and is currently the only remote sensing satellite which is capable of monitoring groundwater level changes. Hence, considering the special and critical conditions of Jiroft plain from the point of view of water resources, the study on the identification of the change of groundwater resources (as the main water resource in the region) have special importance. Therefore, the purpose of this study is to investigate and analyze the fluctuations of groundwater levels in Jiroft plain using GRACE satellite images from 2003 to 2016

This study investigates the trend of groundwater level changes in Jiroft plain using GRACE satellite images during 2003-2016. In this regard, the data was firstly processed in Google Earth Engine based on three algorithms, including JPL, GFZ, and CSR, and their results were compared with observational data (piezometric) from 2003 to 2016. This comparison was performed by examining the linear correlation between the changes obtained based on the GRACE satellite algorithms and the observational data. Also, for temporal and spatial analysis, the aquifer water level was mapped using Kriging method in ARCGIS software.

The results showed a good correlation between algorithms and observational data. According to the results, JPL algorithm with 64% correlation was the most suitable model for monitoring the quantity of groundwater in Jiroft plain. The results of groundwater mapping from 2003 to 2016 indicated the most drop of groundwater level in the central, western and southwestern parts of Jiroft plain, due to more wells and the expansion of agricultural activities in these regions. The examination of groundwater change trend showed that both observational data and JPL, CSR, and GFZ algorithms had a significant decreasing trend at the level of 5%. The similarity trend of observational data and algorithms also indicated the relatively good accuracy of GRACE images to investigate the groundwater level fluctuations.

The recent droughts and increasing the number of exploitation wells have led to the decrease in groundwater levels. Therefore, the assessment of groundwater level fluctuations of Jiroft plain is necessary. In this study, GRACE satellite data were used to evaluate groundwater level fluctuations in Jiroft plain. The results of groundwater mapping from 2003 to 2016 indicated the most drop of groundwater was related to regions with more wells and more agricultural activities that are in line with Hao et al., 2019. The study of linear correlation between the results of the three algorithms of GFZ, CSR, JPL, and piezometers, showed a good correlation between the algorithms and the observational data. According to the results of JPL model with 64% correlation, it was the most suitable model for monitoring the groundwater level in Jiroft plain. Considering the appropriate correlation obtained, it can be concluded that researchers and organizations can apply GRACE data as a low-cost and easy method to monitor and analyze groundwater level fluctuations that are compatible with the findings of Farokhnia and Morid (2014); Faraji et al., (2017) and Nabavi et al., (2020). Investigating the change trend of groundwater showed that both observational data and JPL, CSR, and GFZ algorithms have a significant decreasing trend at the level of 5%. The similarity trend of observational data and algorithms also indicated the relatively good accuracy of GRACE images to investigate the groundwater level fluctuations. The findings of Farokhnia et al., (2014) also showed the similarity of changes trend of the total water balance of the basin by the Grace satellite and the observational data.

In 2018, about fifty-five percent of the world's population lived in urban areas and is projected to increase to sixty-eight percent by 2050. The increasing population of cities emphasizes the optimal use of urban neighborhoods for housing. Urban morphology is one of the topics related to the population of neighborhoods. The purpose of this study is to identify morphological indices in the middle scale and explain the relationship between morphology of residential areas and the population living in them. First, based on the internal-cognitive approach, the opinions of thinkers in the field of morphology were examined and the criteria of "land use diversity", "road network pattern", "compaction" and "public transportation network pattern" were identified in 9 indicators on a local scale. Then, the indicators were measured by space layout and network analysis by Depthmap10 and GIS software in 12 neighborhoods of Tehran. In the next step, first the normality of the data was checked by Kolmogorov-Smirnov test method and the correlation of morphological variables with the population index of the neighborhoods was evaluated by Pearson two-way correlation method and SPSS16 software. The results show that the interconnection index with an intensity of 0.724 has the highest correlation and access to public transportation with an intensity of 0.578 has the lowest correlation with the population index. Examining the severity of correlations provides an opportunity for better prioritization to intervene in the existing fabric of neighborhoods with the aim of resettling the population. The results can be used in the field of evaluation criteria for residential design options, selection of road network and quantitative and qualitative assessment of preparation plans in order to accommodate more population and setting the criteria for detailed plans.

Drought is one of the most prevalent and dangerous disturbances around the world, which cause significant economic and agricultural losses. Kerman province located in the center of Iran is in the first places of drought. The purpose of this research was to investigate the meteorological and hydrological drought condition of the study area. The relationship between meteorological and hydrological drought was also investigated. For this propose, 11 hydrometric stations and 10 precipitation hydrometric stations were extracted. The hydrological and drought indicators were measured using SPI and SRI were calculated at different time scales. Then, the relationship between meteorological drought and hydrological drought, as well as the relationship between meteorological drought with hydrological drought occurring with different time delays, were analyzed using Pearson correlation. The comparison between SPI and SRI indexes showed that in all meteorological stations, drought periods have increased since 2000. The highest correlation between these two types of droughts in the region was related to 48 month periods. The results showed that hydrological drought severity is more than meteorological drought in the region. At the beginning of the study period, meteorological droughts have not an important different with hydrological droughts; however, since the year 2004, the severity of hydrological drought has increased continuously in the region. The correlation between SPI and SRI index at different stations was not the same. The results of the Pearson correlation between SPI and SRI index with delay of 1, 2, 3 and 4 months showed that the highest correlation between SPI and SRI were occurred for the same period. These results also indicate that meteorological droughts immediately affect the river flow and consequently, the hydrological drought was happened

Air pollution is one of the environmental challenges of today's world in most major cities. Considering the importance of atmospheric conditions in the occurrence of air pollution, this study was conducted to investigate the relationship between urban pollution and atmospheric conditions of Tabriz. At first, 32 air pollution periods (125 days) were identified in Tabriz by studying changes in PM10, CO and SO2 during 2008-2013. In order to create the database, 12 effective climate variables were collected at the mentioned days, and their correlation with the changes in the concentration of pollutants were investigated through descriptive analysis, Pearson correlation statistics and stepwise regression. The descriptive analysis of the values of the sustainability indices showed that the KI index in 12% of the cases and the TTI index in the 17-day period was between relatively unstable and relatively stable range, and in the rest of the cases, there was complete stability. The horizontal visibility proved to be between 600 and 10000 m, while the air temperature was between 12.6 to 21.7 TºC, which fell down to below zero at 37 days. Surface pressure in 91% of days was more than 1015 hpa, and the maximum daily wind speed in 64% cases was less than 5 m/s. A quantitative analysis of the inversion layer characteristics indicated that its ∆T average with 4.89 TºC is in intensive category. The temperature inversion depth was 9 to 1769 m and their height was 454 m above the station, indicating the formation of inversions at low altitude in contaminated days. According to the Pearson correlation results, maximum wind speed and air pressure had the highest correlation with PM10. Also, there was a significant correlation between PM10 concentration and all three stability indices, and this contaminant produced the highest correlation coefficient with inversion intensity and top height of the inverted layer with 0.26 and 0.20, respectively. Carbon monoxide concentration had significant correlation with climatic parameters of the land surface except the wind. Meanwhile, the highest correlation was estimated between temperature and relative humidity with coefficients of 0.64 and -0.77, respectively. Although the concentration of SO2 in the studied years never reached unhealthy conditions, its concentration changes showed the highest correlation with the temperature, maximum wind speed and sea level pressure.

Air pollution is one of the problems most of the major cities, including Tabriz, face with. The large industries located in the west and southwest of Tabriz have been introduced as the most important causes of the pollution of Tabriz until the 80s. However, based on the results of the recent research, motor vehicles have been regarded as the most important source of air pollution in this city. Considering the effects of air pollution on water, soil, air, climate, living organisms, and also the human health, the study of the conditions creating and intensifying the air pollution was required. With a disadvantage in natural air conditioning and the atmospheric stability in the cold period of the year, the air of Tabriz always faces a temperature inversion, which often causes the air pollution in the city. Therefore, the present study was conducted to investigate the relationship between atmospheric parameters and air pollution in Tabriz.

The statistical periods studied in this research are from 2008 to 2013 during the cold period of the year. In this study, three data types were used: a) daily and hourly meteorological variables such as horizontal visibility, relative humidity, temperature, pressure (mean sea level), mean and maximum wind speed; b) daily and hourly statistics of atmospheric pollutants including CO, SO2, PM10 and PM2.5. The data is related to the mean data of the stations of the Namaz square (Raste Kooche), Rah Ahan, Hakim Nezami, Bagh Shomal and Abersan. Data recorded for the concentration of aerosols from 2008 to 2013 is related to particles less than 10 microns, but since 2013 onwards, the particle concentrations of less than 2.5 microns (PM2.5) were recorded instead of 10-micron particles; c) the upper atmosphere observational data (from the radiosonde) including atmospheric stability indices (SI, KI, TTI), and information on the properties of temperature inversion layer (including temperature inversion intensity, reverse layer depth, and top height of temperature inversion layer were obtained from the  Wyoming University website.

Based on the data used, 32 air pollution incidents, which included 124 days, were identified. To form the database, 12 effective climate variables were collected at the mentioned days and their relationship with the changes in the concentration of pollutants was investigated by descriptive analysis, Pearson correlation statistics and stepwise regression. The descriptive analysis of the values ​​of the stability indices showed that the KI index in 12% of the cases and the TTI index in the 17% of days were between relatively unstable and relatively stable conditions, and for the rest of the days the complete stability was observed in the atmosphere. Horizontal visibility was at 600 to 10,000m and the temperature was between 12.6 and 21.7 ⁰C, which was below zero at 37% of days. The sea level pressure in 91% of days was more than 1015 hPa, and the maximum daily wind speed in 64% of days was less than 5 m/s. The analysis of the quantitative properties of temperature inversion layer shows that the temperature inversion with an average of 4.89 ⁰C indicates a relatively intense temperature inversion in the polluted days.
According to the results of Pearson correlation, the maximum parameters of wind speed, mean wind speed, and air pressure have the highest correlation with the changes in the concentration of PM10 aerosols. There was a significant correlation between PM10 concentration and all 3 stability indices. Also, among the properties of the temperature inversion layer, PM10 concentration had the highest correlation coefficient of 0.26 with the temperature inversion intensity.
Other than with wind, the CO has a significant correlation with other climatic variables of the land surface. Meanwhile, it has the highest correlation with temperature and relative humidity variables with the coefficients of 0.44 and -0.57 respectively. Between the quantitative properties of the temperature inversion layer, the concentration of CO had the highest significant correlation coefficient at 95% confidence level with the temperature inversion intensity. During the studied years, the concentration of SO2 was not close to unhealthy conditions, but the concentration of this pollutant in days with atmosphere stability and temperature inversion has increased and reached 53 ppb at the highest rate in study periods. SO2 concentration has the highest correlation with daily pressure and temperature.
The result of stepwise regression for PM10 pollutants revealed three maximum variables of wind speed, temperature inversion intensity, and KI index as the most effective determinant factors of PM10 contamination. Among 12 independent variables, the final output of stepwise regression determined only the temperature and temperature inversion intensity as the most effective atmospheric parameters in changes in CO pollutant concentration. Also, the results obtained from the stepwise regression model for SO2 proved that the average temperature, maximum wind speed and temperature inversion intensity had the highest effect on SO2 process.

Among the studied climatic variables, the maximum wind speed, temperature and air pressure are more correlated with pollutants. Among the sustainability indicators of atmosphere, the suspended particles showed the most significant correlation with the KI index and with SI and TTI in the next orders. Between the stability indices studied, CO showed a significant correlation with non-critical states of KI, and SO2 pollutant showed a significant correlation with SI and KI indices. Results obtained indicated that the temperature inversion intensity has a positive correlation with all three pollutants, which manifests an increase in the amount of pollutants in intense temperature inversions. A reverse correlation of horizontal visibility with the concentration of PM10 and SO2 pollutants also indicates the effect of these pollutants on reducing the horizontal visibility. Also, the temperature was the most effective element in the process of pollutants of CO and SO2. The wind speed has the highest correlation with aerosols. Of the studied variables, the temperature inversion intensity, the KI index (condition of atmospheric stability), and the rate of pressure affect the trend of increasing and decreasing the concentrations of all three pollutants.

Introduction Zayandeh-Rud Basin (ZRB) is one of the most strategic river basins of Iran where the majority of the basin has a typical arid and semi-arid climate with frequent droughts. Drought is a recurrent phenomenon that affects humid as well as arid regions to some degree which has large adverse consequences on the socio-economic condition of people living in drought-prone areas through its impact on water availability and quality and ecosystem health. Standardized precipitation index (SPI) is a station-based drought index which measures precipitation. The limitation of SPI is continuous spatial inability and coverage. On a regional scale, SPI cannot monitor and illustrate the detailed pattern of drought conditions spatially, particularly in regions with a high degree of spatial variability or inadequate meteorological stations. As the spatiotemporal identification of drought events is very complex, drought indices are mainly beneficial in order to monitor the impact of climate variability on vegetation (Khosravi & Akhund-Zadeh, 2015). Remotely sensed spectral indices can determine the quantification of vegetation drought. Moderate Resolution Imaging Spectro-radiometer (MODIS) has been used by various researchers from diverse disciplines globally. Monitoring vegetation using satellite imagery is also comprehensively applied to monitor and assess drought condition and etc. The Normalized Difference Vegetation Index (NDVI) (Tucker, 1979) is the oldest remotely sensed vegetation index in use and remains as the most widely used by the remote sensing community. The efficiency of NDVI in evaluation of vegetation response to drought has been tried out (Tucker & Choudhury, 1987) which provides a common measure of the health and condition of vegetation. Nevertheless, NDVI has some deficiencies; NDVI is not sensitive to soil color, atmospheric effects, and illumination and observation geometry. The limitation of NDVI in drought monitoring is that NDVI cannot indicate the drought severity alone because of obvious time lag of NDVI response to precipitation and little effect of weighty rainfall events later in the growing season (plant seed production period) on NDVI (Ganesh, 2007). Therefore, NDVI-Vegetation Condition Index (Kogan, 1995) normalizes NDVI for each pixel over time based on its minimum and maximum values. The VCI was applied successfully for drought monitoring by various researchers. Onset of drought and the duration, intensity and impact of drought can be measured and detected by the VCI. In addition, identifying the spatio-temporal variability of vegetation conditions associated with perturbation as a result of precipitation shortage is allowed by VCI. VCI has been compared with field reflectance measurements, biomass and vegetation density. It is proven that VCI could be a suitable sign of the impact of climate on health and conditions of vegetation. The clear benefit of VCI is simplifying of the computation because it does not need station observation data. As VCI is a satellite-based drought product, it can process globally near real-time data at a reasonably high spatial resolution. VCI is appropriate to make a relative assessment of variations in the NDVI signal by filtering out the contribution of local geographic resources to the spatial variability of NDVI. In addition, VCI evaluates variations in the NDVI signal during time through decreasing the effect of local ecosystem variables. This research aims to assess spatial distribution of VCI index through spatiotemporal monitoring of it using MODIS NDVI time series products in growth season over ZRB from April to October 2003 to 2014 (Mrahsani, Salman Mahini, Soffianian, Modarres, Jafari & Mohamadi, 2015).
Material and 2.1. Study area
ZRB or Gavkhuni Basin is known as a very important river basin of Iran. ZRB with area of 41485.65 km2 (5.2% of the country's total area) is located between the 50° 24′ to 53° 24′ longitudes and 31° 11′ to 33° 42′ latitudes. Temperatures have been recorded to be hot in July, with an average of 30 ̊C, and with an average minimum temperature of 3 ̊C in January. Rainfall, which is generally very limited, is around 130 mm per year (Salemi, & Rust, 2004). In ZRB, the annual precipitation recorded ranges from 1500 mm (in snow which is only likely to be melted when temperature rises around April) in the western part to 50 mm in the eastern part (Sarhadi & Solatni, 2013).
2.2 Data Collection
2.2.1. Monthly MODIS/Terra NDVI
The Monthly MODIS NDVI time series product (MOD13A3, 1 km ×1 km) images of the study area were applied from 2003 to 2014.
2.2.2. Meteorological Drought Index
The SPI is a station-based index which calculates the probability of precipitation in different time scales. The SPI calculation for any location is based on the long-term precipitation record for a desired period. In this research, SPI values are calculated based on precipitation data collected from 26 meteorological stations around ZRB which had the same available beginning from January 2003 to December 2014.
2.3. Vegetation Condition Index (VCI)
VCI is calculated and normalized using long term NDVI ranging from 0 to 100. Low values indicate vegetation stress and median values indicate average condition while high value indicates the optimized and normal condition.
3.1. Metrological Drought Index (Monthly SPI)
The long-term SPI (12 months) were calculated based on precipitation data collected from 26 meteorological stations around ZRB which had the same available beginning from January 2003 to December 2014. The severity-duration and relative frequency of drought were then determined per time scale and station.
3.2. Vegetation Condition Index (VCI)
In the present study, the annual VCI time series maps were prepared in order to quantify drought from a long-term observation. It was found that sign and onset of drought can be clearly observed from the VCI maps from July to October 2003 and July to October 2005. The slope of fluctuation of the precipitation is slow during 2004 to 2006. From October to June 2007 the condition was improved all over the basin. Nevertheless, a severe drought condition prevailed all over growth season of the year 2008 all over ZRB. The slope of precipitation is slow during 2008 to 2009. The onset and extent of drought can be clearly observed from the VCI maps of April 2008 to end of growth season. Acute water stress is evident over the basin during June 2008 to April 2009. From April to May 2010, the condition was improved all over the basin. For a second time, a severe drought condition prevailed all over growth season of the year 2011 all over of ZRB. From April to May 2011, the condition was improved all over the basin, while in September the basin have faced drought again, this cycle is repeated in the end of growth season of the year 2014. Uneven distribution of rainfall causing spatial variation in vegetation health has a great influence on variation of agricultural yield of ZRB. Since the precipitations in the eastern, northern and central districts of the basin are much less than the western districts, the vegetation condition was visibly stressed in the Gav-Khuni wetland and agricultural lands in east of the basin. The vegetation health was only found normal in ZRB during the year 2007 and 2010. In 2008, the basin had been covered mostly by very high drought categories, followed by 2010 and 2014. High drought categories were mostly formed in 2011, followed by 2012 and 2013.In addition, in 2012, ZRB was mainly covered by relatively high drought, followed by 2014. The biggest area covered by moderately drought category belongs to 2012. The biggest area covered by normal category belongs to 2007, followed by 2006.
Conclusion One of strengths of the MODIS sensor is the conciliation and reconciliation between reasonable spatial resolution and regular image acquisition. It is necessary to use remote sensing data beside other datasets from other sources because of the growing demand for data and escalation analysis. This causes an essential role for remote sensing techniques in the climatological and meteorological applications. The drought was assessed through monitoring vegetation condition using VCI; subsequently, its correlation with SPI was obtained to be 0.83, respectively. Then, the area of each category covered by VCI was calculated. Results indicate that VCI can present consistent results with strong correlation to SPI. In addition, results show usefulness of VCI in drought monitoring studies despite the wide range of climatic conditions in the region. In addition, the area of normal category covered by VCI in the basin is coincident during the time period except 2008 and 2011 during which severe meteorological drought had been occurred. However, it seems that vegetation condition is affected by facilitating irrigation of cultivated lands. In addition to extraction of groundwater and wells, the irrigation is influenced by opening the floodgate of Zayandeh-Rud Dam in the basin. Hence, it is essential to consider hydrologic drought in seasonal time scale to have a better image of water scarcity for different water demands such as agriculture and have a better water management and planning in future studies (Modarres & Silva, 2007).

One of the important purposes of Archaeology, is studying the interaction of humans with the environment: This paper is trying to focus on and analyze the role of natural, geographical, and environmental factors in the appearance of human settlements in Neolithic and Chalcolithic, of Laran County. Laran County is located in the Southern branch of the Zayandeh- Rud Rive and Due to the potential environmental and geographical conditions has caused appropriate human settlements are formed in different periods. Because of this area is located in a mountainous area, has a cold weather, with abundant rainfall and for this reason, landscape is causing many environmental constraints. Subsistence ways of the people in this region are agriculture and livestock. This area is now the number of Bakhtiari nomad's countryside come to this area in summer.
The study of this part of the Zagros, as one of the important areas is located in the between two central plateau region of Khuzestan, And the natural environment role in shape, continuity or the collapse of archaeological sites is one of the gaps that needs to research in the studies of this area. Therefore, our records of the changes of the region in different periods of prehistory and its mode of relationship with other environment are incomplete. In this study, is used a total of 19 Neolithic and chalcolithic sites have been identified of the 2010 survey in the Laran county. Identify sites in the study were analyzed by using descriptive and analytical methods and by using GIS and SPSS software. In this study, the extent of the archaeological sites as the dependent variable And environmental conditions, such as distance and proximity to water resources and communication paths, vegetation type, slope direction, slope degree and altitude were considered as independent variables. The reasons for the lack of Correlation or correlation archaeological sites back to the relationship between man and environment that creates a special kind of the landscape. According to the results of the correlation is determined that the height above sea level, the seasonal water and vegetation resources have more impact as compared to other factors And others factors such as slope direction, slope degree, distance from communication routes and Permanent sources of water are very low. The overall results of this study suggest that Neolithic and chalcolithic sites in the Laran County are Low depended to environmental factors and this suggests that these sites are used seasonally.This area is high and has a cool climate and these factors have created special and different conditions, forming human settlements similar to other areas in Zagros Highland. According to the above, we must ask which one life style is that the height, seasonal water sources and pasture vegetation plays an important role for human life. What characterized that in the Neolithic and Chalcolithic period, way of life in the region is similar to todays and life style has been nomadic pastoralist that is still ongoing.
Key Word: Neolithic and Chalcolithic, Zayandeh- Rud Southern area, Laran County, Pearson correlation, environmental factors

The purpose of this paper is determining the relationships between teleconnection patterns and temperature in Northwest of Iran. The relationship between 17 teleconnection patterns and Monthly temperature of 24 stations in Northwestern Iran by using Pearson correlation analysis and Stepwise Regression Model during the statistical period of 1992-2011, were used for measuring the relations. Finally, the spatial distribution of the correlation between these patterns and temperature of stations in the study area was drawn and its zoning was prepared by use of Kriging method in GIS environment . The results showed that there is a significant correlation between teleconnection patterns and temperature of the region. So that AO, EP/NP, SOI, MEI and EA/WR patterns have the strongest correlation with the temperature of region and were identified as the most influential patterns. According to lag correlation calculations that were done on lag time of one month, two months and three months, the more significant correlation is the lag time of one month. The strongest significant correlation is related to Sardasht station and EA/WR teleconnection pattern with Correlation coefficient -0.771 in February.

Solar radiation is one of the most important and influential parameters in thermal balance of the atmosphere and thus it is considered to be the basis of many climatic studies. Evapotranspiration is defined by the amount of available energy for evaporation. Since energy at ground level is mostly supplied by the sun, many researchers have been interested in the influence of solar radiation on agriculture and especially irrigation sciences. Main research variables include total radiation received at ground level and the slope of radiation changes which are calculated and analyzed using data quality control and routing methods recommended by World Meteorological Organization, and measured at two different geographical points with semi-arid climate. Regarding Pearson correlation coefficient, the significance level of Kermanshah station was set at 99% and Tabriz was set at 95%. Total annual radiation and statistical period are positive related. With an increase in statistical years, annual radiation increases with an appropriate slope which shows the ascending trend of annual radiation in stations.