---

plants needs a certain amount of heat at the time of planting and during its growth period, The temperature requirements of the 704 single-cross cultivar of maize in Moghan weather conditions have been found in this study to determine its temperature requirements in its different growing stages in order to investigate the feasibility of its planting in the north west regions of Iran. Daily weather statistics presenting the minimum, maximum and average temperature of 51 Synoptic stations from Meteorological Organization of Iran have been used in this study, their statistical periods range from 1 to 30 years (1365-1395), the statistics and information about 5 main phenology stages of 704 single-cross variety maize which are recorded continually in Agricultural Weather Service of Moghan station in Pars Abad from 1390 to 1391 are provided. Then the 15-day averages from April 21st to July 22nd is obtained. The relationship between the temperature and the height in the linear regression is calculated .Map of heat supply date for seed sowing in all stations from the first half of May was drawn in the GIS. The plant collective growth degree days and the number of days in every phenology phase are calculated for all of the stations and the related maps are plotted.Then,the final map plotted by combining the layers thermal, height, slope and land use in the study area. The results of this study only 27.6% of the study area is able of maize cultivating.

---

The country of Iran, with its geopolitical foundations, which is influenced by its geography, has always been the focus of the countries of the world, especially the world powers, throughout history. The use of this capacity and conditions for the economic prosperity of the country depended on the ability of the statesmen and the type and structure of the government systems in formulating foreign policy, and how effective they were in changing the social environment and the way of economic livelihood of the people. In a fundamental and theoretical way, this thesis has analyzed the formulation and presentation of the national strategy of the Islamic Republic of Iran based on its geopolitical characteristics.
The results of this research show that the spirit that governs it according to the structure it entails (statehood), is economic regardless of geographical and geopolitical infrastructure, and this field of foreign policy has not only failed to achieve success, but is also passive. And it has become introspective and stopped from being effective and dynamic. While looking at Iran's geopolitical and geographical foundations, we find that its geopolitical position does not have a global effect and is not below the regional level.

---

Greenhouse emissions from agricultural as a consequence of human activities are causing climate change. Small changes in agricultural practices have a large potential for reducing greenhouse gas emissions. Intention of Agriculture Experts in order to mitigation climate change Can play an important role in finding appropriate solutions for each region in climate change mitigation and deliver them to their farmers. However Intentions to take mitigation actions are, most likely, influenced by a range of factors. The purpose of this study was to investigate of factors influencing on Agriculture Experts in order to mitigation greenhouse gases. This research in terms of purpose is an applied research and in terms of methodology is survey research. The statistical population of this research consisted of 520 Agriculture Experts in Khuzestan Province. A sample of 320 persons was selected through Random Stratified Sampling method. The survey instrument was a questionnaire which its validity confirmed by experts. The reliability of the questionnaire using Cronbach's alpha coefficient (α= 0/67-0/87) has been approved. Our analysis reveal, direct experience were predictors of risk perception, self-efficacy and environmental attitude. The changes in self-efficacy and environmental attitude were also strong predictors of changes in intention.  The variables of self-efficacy and environmental attitude could predict 61 percent of variations in willingness to mitigating climate change. Therefore experience indirectly affected on the mitigation intention. Lastly we provide recommendations on how these findings can be used to climate change mitigation.
 

---

This research study aims to investigate the effect of climatic variables, specifically precipitation, temperature, and humidity, on changes in vegetation indices of orange orchards in Hassan Abad, Darab County, using satellite data. Consequently, observational data, including orange tree phenology data and meteorological data from the agricultural weather station, were collected over a period of more than 10 years (2006 to 2016). MODIS images from 2006 to 2016 were referenced based on territorial data and 1:25000 maps from the Iran National Cartographic Center. These images were used to calculate remote sensing vegetation indices, namely the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The results demonstrated that the variables of maximum humidity, minimum temperature, and precipitation have a significant positive effect on the NDVI variable. Additionally, the variables of maximum temperature and minimum humidity have a significant negative effect on both the NDVI and EVI. To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. Moreover, the effect of these variables on the NDVI index is equal to their coefficients, which are 0.2, 0.28, 0.22, 0.11, and 0.17 respectively. Finally, the ARMAX regression method was used to improve the explanatory power of the model. The results indicated that this method enhanced the explanatory power of the model and reduced the forecasting error.