a. r. sharifi

In recent decades, due to the various facilities in big cities that have caused the expansion of cities and urbanization and the increasing desire of citizens to live with a machine, this change in life pattern has also caused an increase in environmental pollution, difficult conditions for the livability of human life space, such as (The destruction of urban and suburban vegetation and the loss of ecological balance. The expansion of the population of cities and excessive population density in cities has caused the destruction of the natural environment and the construction of artificial structures that require physical and It has made the human spirit more visible to the environment. Considering that Iran is one of the countries located in the dry belt of the world, the cities to deal with noise and air pollution, as well as reduce environmental stress more than any other point to the space They need green. Considering the many problems that we see in changing the urban structure today, the heterogeneous quantification of the environment has been considered as a goal in landscape ecology, so that recently there have been efforts to develop methods In order to quantify the spatial heterogeneity (complexity and variability of the system characteristics, including the mosaic spatial layout of the land surface) (time and space) the features of the land have been done. Terrain metrics are a useful tool for expressing the mosaic pattern of urban green spaces and its changes in connection with urban development processes, which, in addition to interpreting the effect of the aforementioned processes on the ecological characteristics of the environment, can be used in decision making related to the growth of the city, distribution of uses and urban green space development planning. Therefore, according to the existing problems in defining and determining the urban green space, the application of remote sensing science, which is considered a powerful tool in the management of urban resources, and by providing the facilities of this science in order to provide up-to-date information, digital processing of images and the possibility of comparison Sometimes the data has helped experts to monitor the changes of the green space over time. Also, by using remote sensing in combination with terrain measurements, it can improve the understanding of urban spatial structure and change processes. Today, the high speed and extent of changes, both structural and process, in the face of the land, which are caused by destructive human activities, have made planners face many issues and problems. The present study was conducted in order to evaluate map production using Sentinel-1 and Landsat-8 radar images using local climate method and vector machine in Tehran metropolis. Using the proposed method, it was determined that the central and southern parts of Tehran have a very concentrated residential structure, so that urban green spaces are rarely seen in the urban context, while the green spaces in the north of Tehran are scattered among the contexts. It is residential, which indicates the existence of private green spaces in this part of the city. Also, in the south of the city, due to the presence of fine-grained texture in this area, due to the presence of residential centers in these areas, compared to the residential texture of the northern parts of the city, in the central and southern areas, private green spaces do not exist or rarely exist, and this warning increases. Heat islands and higher temperature are in the south of the city. Maps produced using remote sensing can be an alarm for municipal managers who can prevent future problems with planning and management. Also, considering the important role of green space in the morale of citizens and crime reduction, it is necessary for city managers to pay enough attention to the issue of reducing green space and the lack of proper distribution of use in Tehran, because neglecting this issue can lead to other problems. It created compensable for the citizens.

Environmental pollution and disasters have gradually increased with population growth. The presence of oil resources in the seas and the incidents related to their discovery, extraction and transportation cause the formation of oil slicks on the sea surface, and the leakage of these petroleum products into the seas has irreparable environmental consequences. That is why monitoring the effects of these accidents is very important for public health. Satellite missions are a very effective tool for detecting pollutants such as oil spills. Artificial Aperture Radar Sensor (SAR) is an active microwave detection system that can be used to detect oil leaks with optical sensors installed on Landsat-8, Sentinel-2 and Ester satellite systems, taking into account cloud cover and satellite re-visit time at the same location. Be. In this study, the oil spill area due to pipe leakage in Khark Island was studied with Landsat-8 and Sentinel-1 satellite images. Various image processing techniques were applied to Landsat-8 bands to highlight oil spills in connection with the accident, such as morphology and convolution filters. We used Landsat-8 images to support the Sentinel-1 results. Oil spills were successfully detected by analyzing SAR data and Landsat-8 results, and by visually interpreting the results, the selected methods are consistent in terms of displaying oil spill areas.

One of the natural disasters of all is drought. Drought has long been one of the problems of Iran and has always been mentioned as a serious threat to the country. Drought is one of the natural and repetitive features of the climate and part of the climate that cannot be observed without a specific limit of occurrence and impact using high-speed ground station information. Drought rate is divided into severe, mild, moderate drought and long-term drought and short-term drought based on time components. Drought has had effects on land degradation, forest fires, reduced air and water quality, and reduced agricultural production. Frequent droughts have been a concern for many years, and on a global scale, in recent decades, especially in arid and semi-arid regions, the frequency, severity and duration of droughts have increased significantly. Drought according to different definitions in each area is divided into four main categories, including meteorological drought, agricultural drought, hydrological drought and socio-economic drought. In meteorology, drought, or in other words dry period, is the reduction of loss in a period of time compared to the average amount of rainfall in that period or the amount of long-term rainfall in the same period. Of course, if this amount of rainfall does not meet the needs such as economic and social needs. The duration or period of drought varies according to the climate of each region and depends on the location and time. In Iran, the drought period is approximately equal to the crop year. The severity of drought also varies in each climate and country. The same amount of rainfall in one country may be considered drought, while in another country, the same amount of rainfall does not indicate drought. Agricultural drought damages the economy, social conditions, agricultural products and consequently food security, so monitoring it is essential. For this purpose, agricultural drought in Markazi province has been studied. One of the factors affecting agricultural drought, soil moisture and plant evapotranspiration as a cause of water loss is the difference between the available water and its wastage. Therefore, to measure drought, an indicator that shows evapotranspiration is needed. In this research, RWDI index is used as an indicator of drought based on evapotranspiration. To obtain this index, one must first obtain the actual evapotranspiration and potential. Due to the advantages of remote sensing methods compared to traditional methods, remote sensing methods based on energy balance and SEBAL2 image processing model as well as Landsat 8 images, in dry and wet seasons, along with meteorological data to obtain heat flux Hidden, which depends on the parameters of soil heat flux, tangible heat flux and net radiation flux, is used. Using latent heat, instantaneous evapotranspiration is calculated daily and using the Penman 3 method, reference evapotranspiration is calculated. Potential method of Taylor 4, evapotranspiration and potential transpiration are obtained, and as a result, after calculating the actual evapotranspiration, the RWDI index is prepared, which shows the water shortage and the severity of agricultural drought. The results show that the values ​​of evapotranspiration are obtained with acceptable accuracy. Meteorological stations are obtained in REF-ET software. In addition, based on the results of the water deficit index, the values ​​of this index are expected to be higher in dry seasons than in wet seasons.

Water reserves are considered as renewable resources and the process of renewal is due to the water cycle in nature. However, the amount of water that emerges in this way on the surface of the earth or in any given geographical area is fixed, regardless of the changes between the years. In other words, the amount of renewable water that the earthchr('39')s surface receives now and annually is equal to the water that it may have received thousands of years ago since the dawn of human civilization. This is while the spatial and temporal distribution of the amount of renewable water is completely variable and is not commensurate with the distribution of population and water needs of human societies. Obviously, the most accurate rainfall measurements are provided using traditional methods such as climatological stations, ground synoptics and rain gauges, but the accuracy of using this method in a dependent catchment Due to the spatial distribution of the stations and the sensitivity of its trustees in the maintenance of the stations, the realization of this important issue requires a lot of money and time. Accordingly, and since remote sensing is able to provide continuous, homogeneous and near-real-time information on the location and time in a particular area, even in inaccessible areas. There are several factors involved in evapotranspiration, the degree of effect of each of which depends on other factors, which makes it difficult to accurately estimate evapotranspiration. Some of these factors are air temperature, relative humidity, atmospheric pressure, amount of water-soluble substances, altitude and longitude. Thus it is impossible to use traditional methods and to directly calculate evapotranspiration without any degree of accuracy over a wide range. When the amount of rainfall in a catchment is more than the soil infiltration capacity, part of the rainwater flows as runoff on the surface of the catchment. The amount of runoff in a catchment depends on several factors including soil characteristics, catchment concentration time, geological conditions, climate and climate, slope and direction of slope, land use and drainage density. Various devices such as lysimeter and TDR device can be used to estimate the penetration rate directly; However, it is obvious that using these devices to estimate the infiltration rate in a large catchment area is very time consuming due to changes in the soil type of the catchment. Therefore, this component is calculated through methods, equations and relationships resulting from some hypotheses in hydrology. It is obvious that the accuracy of ground stations is much higher than satellite data, but in large basins due to the high cost of construction and maintenance of these stations and also the time consuming use of it. This study was conducted in the location of Tajan catchment area, which seems to be the ground stations located in it, both in terms of number and in terms of health due to the prosperity of agriculture and the location of Sari city with the majority of farmers in the region compared to other basins.

Solar energy is an important source of renewable, sustainable, and accessible kind of energy in the world. Halting environmental degradation, this kind of energy is what can reduce the damaging consequences of fossil fuels. Iran or other counties located in the arid area can use this type of energy. In fact, the geographical position of Iran in word's dry belt makes this country a proper land for constructing facilities of using solar energy. One of the most usual facilities, which use solar energy are photovoltaic power plants. Photovoltaic power plants need special situations to get the best efficiency. First of all, they need the highest portion of sunny days in a year. Moreover, to reduce the cost of construction, they must be built near the roads and power transmission lines. To find the places which include the best conditions, GIS is a useful system. GIS is able to prepare maps of the desired conditions and then combine them using various approaches to find the best locations. Many researches have already been done around the world for site selection of photovoltaic power plants. There are some researches in Iran, as well. However, the criteria used in these researches seems not to be comprehensive enough for such a sensitive site selection. Thus, this research aims to take as much as possible criteria for site selection of photovoltaic power plants into account.The goal of this research is to find the potential area for constructing photovoltaic power plants in Iran. This purpose contains four main sections such as assessing effective factors on the operation of photovoltaic power plants, preparing factor maps (criteria maps) in GIS environment regarding the spatial nature of the effective factors, the maps conversion into fuzzy form and proper combination, and finally, classification of result into four levels. Using fuzzy logic helps us to consider unavoidable uncertainty that exists in spatial data. In this study, the prepared factor maps are first converted into a fuzzy form using fuzzy membership functions. Then, using fuzzy overlay, the maps are combined. To set the most strict situation, among the fuzzy logical operators, fuzzy AND was selected. Thus, we will be sure that the final selected sites will have the best possible conditions. The results indicate that six provinces, including Kerman, South Khorasan, Fars, Yazd, Hormozgan, and Sistan-o-Baluchestan, achieved the highest score for constructing photovoltaic power plants in Iran. Overlay, more than 557000 square kilometers of Iran have a high potential for gaining solar energy. The results also show that north and north-west of Iran in compare to the other areas, achieve less suitability for constructing photovoltaic power plants. The most important criterion that causes these situations is the portions of sunny days. While in the north side of Iran, as well as the mountainous areas such as Zagros Mountains, the precipitation is higher than the other regions, the number of sunny days in a year is less. This study detects the proper sites in a general form. The scale of the study covers the whole country. Thus, most fine-scale studies must be performed on the selected regions to find the best specific sites.

The indigenous stocks play an important role in villager economy in developing countries, especially in Iran. Indigenous breeds could maintain higher level of performance under Incompatible environment compared to commercial strains. In classic breeding programs for poultry, selection of birds was based on phenotypic and pedigree information. The development of genomic selection prefers new strategies in animal breeding. Genomic selection has a major limitation for implementation. This method need genotyping of large numbers of markers for implementation and the costs of genotyping for these markers is high, especially for developing countries. To overcome this problem, before applying genomic selection, different scenarios have to be compared using computer simulation. The objective of this study was comparison of results in genomic selection and classic selection method in Iranian native fowls by using ZPLAN software (Täubert 2010). ZPLAN software is a very useful tool to optimize conventional and genomic breeding programs this software allows modeling of all relevant breeding structures, while taking all relevant biological, technological and economic parameters for complex breeding programs into account (Sitzenstock et al. 2013). This software then generates results such as the annual genetic gain for the breeding objective using a pure deterministic approach (Dekkers 2007). This program has been based on the discounted gene flow-method (Hazel 1943) and selection index theory (Hazel and Lush 1942). This software calculates genetic gain, discounted return, profit and costs within and over selection paths. The results of monetary in ZPLAN are standardized to an animal unit and are given per year (Sitzenstock et al. 2013).
Material and A reference scenario and a genomic scenario were simulated on 3460 birds in both sexes. Reference scenario was simulated based on phenotypic information and genomic scenario was simulated based on combination of phenotypic and genomic data with two reference populations of 500 and 1000 birds. Genomic data was based on the information of 4000 hens and variable numbers of cocks (800 to 4000). Studied traits included egg number, body weight at 8 weeks, mean of egg weight and age at sexual maturity. In this simulation, genetic and phenotypic parameters were used (Table 1). These parameters included: phenotypic standard deviation, heritability, genetic and phenotypic correlations and traits economic coefficients. Economic weights were based on the study of Kianimanesh et al. (2001) and the other parameters were extracted from the study of Yousefi 2012. The variable costs of rearing a cock or a hen were assumed to be 440000 Rial per animal (over a period of 20 weeks). During production, daily feeding costs resulted from a feed consumption of 0.11 kg per day at a price of 12000 Rial per kg. For each cock and hen, additional costs for the animal care (20000 Rial) were assumed. The costs of selection were assumed 40000 Rial per animal. The fixed costs were not considered in conventional scenario, because it was difficult to quantify them in breeding program. But these costs must reduce from profit. The interest rate was set to %7 for discounted costs and %2 for discounted returns (Sitzenstock et al. 2013).
The generation interval for both scenarios was 14.5 months. By adding genomic information to reference scenario, accuracy of estimations increased from 0.62 for chocks and 0.64 for hens in reference scenario to 0.77 for both sex in genomic scenario. Genetic development of traits increased with increase in the number of genotyped birds and the number of birds of reference population. Genetic development for traits egg number, body weight at 8 weeks, mean of egg weight and age at sexual maturity increased from 0.22, 2.57, 0.09 and -0.23 (Table 2) respectively in reference scenario to 0.30, 3.60, 0.11 and -0.27 respectively in genomic selection with 1000 reference population. The profit of breeding program was higher than reference scenario only in genomic scenario with reference population with 1000 birds (Figure 2). The discounted return per animal unit in the conventional scenario was 20102400 Rial per year. The variable costs for conventional scenario were 1057200 Rial per animal unit. This resulted in a profit of 19044800 Rial per animal unit. The accuracy of the genomic information and the size of the reference population have a large impact on the benefits from genomic selection. Dekkers 2007 showed that with increasing of marker information increased the benefits from genomic scenarios.
The use of genomic information caused increasing genetic development in all traits. Although in this study costs were not reduced, but genomic information increased the accuracy of selection of breeding program. This study showed that genomic selection can increase the genetic improvement rate of native chickens. However, the costs of genomic scenarios were higher than conventional scenario, but genomic information increased accuracy of selection and genetic gain of breeding goals traits. To overcome this problem, use of low density SNP chips is suggested.

The administrative reform is one of the means to achieve economic social and cultural policy development. Given the necessity of administrative reform monitoring, this study aimed to identify and measure the indicators of administrative reform in the medical school of Tehran University of Medical Sciences. A mixed sequential qualitative-quantitative approach was employed. The indicators of evaluation were identified through document analysis. In the first phase, 8 semi-structured interviews and the views of 5 experts were collected. Then, we used a researcher- developed checklist to evaluate the current status of the selected school. The checklist was completed through on-site visiting, observation, interview and document review which were then analyzed manually. A set of 150 indicators of administrative reform evaluation, categorized in 10 domains and 36 areas was identified. The total score of evaluation was 28%. The employment equity and payment system domain showed the highest score (55%) and the organizing of human resources domain lowest score. Given the relatively poor results of the administrative reform and the continuity of the reform in Iran development plans, we recommend accelerating the efforts of defining and implementing the administrative reform. Our developed checklist can be used by policy makers and managers.

Runoff resulting from rainfall is a complex and non-linear process and، therefore، its modeling is not so easy. The aim of this study was the application of the Gamma test to select the optimal combination of input variables for runoff modeling in Amameh watershed. M-test was used to identify the optimal number of required data for modeling. Data of rainfall (P(t)) and runoff (R(t)) in daily time scale were used in the period of 2000 to 2009. Totally، eight input variables namely four variables of daily streamflow: lag-1 (R(t-1))، lag-2 (R(t-2))، lag-3 (R(t-3)) and lag-4 (R(t-4)) as well as four daily rainfall variables: without lag time (P(t))، lag-1 (P(t-1))، lag-2 (P(t-2)) and lag-3 (P(t-3)) were used. Streamflow modeling was performed based on the optimum number of the selected variables using the artificial neural network (ANN) and local linear regression (LLR) methods. The results showed that the six variables of P (t)، P (t-1)، P (t-2)، P (t-3)، R (t-1) and R (t-2) belonged to the optimum combination of variables in streamflow modeling of the mentioned watershed. Moreover، based on the M-test output، only 1405 points were found to be adequate for modeling in the training section. Results indicated the fact that the LLR method had greater accuracy in training process compared to ANN. However، the ANN had large amount of accuracy in the model testing process. In training section the R2 and RMSE values were found to be equal to 0. 96 and 1. 7، respectively.