Journal of Spatial Analysis

In the present era, most cities have been faced with numerous problems. But the environmental dimension has been more challenging. Many urban professionals constantly seek to present effective solutions in order to prevent damage to the environment. Thus, theories, models and many views in this subject have taken, including livability approach derived by the school of sustainable development. So today, as one of the views livability approach is rooted in the theory of sustainable development has been focused on, and the above approach can cause problems in multiple cities. In this research, Region 17 of Tehran as the most problem area, was selected; and the overall goal of this study is assessing the livability of the Region 17’s neighborhoods, and the objective aims are including the assessing of livability dimensions, i.e. the environmental, the historical pattern, the urban management policies, the social, services, activities and facilities, the urban economy at the local level and identifying the livability homogeneous clusters and assessment the impact of livability’s variables, dimensions and indicators in that area. According to the study of the history and theoretical foundations of livability, the most important dimensions, indicators and items related to livability were extracted and the all selected dimensions and indicators, rooted in history and theoretical basis of their livability. In the present study include the following six dimensions of environmental, historical pattern, urban management policies, social, services, activities and facilities, urban economy with 20 indicators and 94 items were considered and the pattern of research in terms of goal, is cognitive; in terms of nature and method, is comparative – assessment; and about location of territory is Tehran’s Region 17, in respect of timing, is temporal and related to the 2015. Combined data collection method is combined0 (documents, survey) and it is the type of quantitative-qualitative data (questionnaire). The data used in the research is preliminary data that were obtained by questionnaire. The statistical society are the residents and citizens of Tehran’s Region 17 who are questioning. The necessary actions to operationalize the research was conducted in several stages: 1) Adjustment of questionnaire (using five Likert scale ranging from very low to very high range, verifying the validity by experts, verifying the performance reliability of the questionnaire by using the Cronbach's alpha in software of SPSS as a result 0.8), 2) Determining the sample size and sampling (400 samples determined by Cochran formula, using multi-stage sampling), 3) Entering data into SPSS software and doing the statistical tests (parametric statistical tests such as one sample T-test, ANOVA, Friedman) analyzing the data by SPSS and statistical tests of one sample T-test, ANOVA, Friedman, represents the undesirable od livability and its dimensions, the difference between neighborhood in terms of livability and more economic effectiveness on the livability of Region’s 17 and its neighborhoods, 4) The showing of spatial diagrams of research findings and preparing the livability’s maps by using ArcGis software and interpolation method. Ultimately, according to the findings and viewpoints of researchers and field observations, it can be concluded that the causes of problems in this area should be within the region and neighborhoods, it's time to overcome the situation that has been searched. In other words, the root of the problems in the above range is due to its geographical bed’s situation and other substrate characteristics. The meaning of geographical bed’s situation, climatic and tectonic characteristics of the area and the order of the micro-feature is the problems with the nature of the social, economic, administrative, infrastructure etc, so that were formed following the influx of population. Until two important problems raised in this region is not considered to be flows: 1) Geographic bed features, 2) the capacity of Region 17 for accommodation of population and services to them.

Dust particles consist of important aerosols and resulting in blowing strong winds on the surface of desert areas. These particles enter the atmosphere under the influence of different factors including: weather condition (wind, precipitation and temperature), land surface (topography, humidity level, roughness and vegetation), soil features (texture, density, composition and land use (agriculture).

Today powerful dust storm destroys people lives and causes severe damages to their life and also causes financial problems in most regions of the world especially in west and southwest of Asia. Dust storm is one of the most important natural phenomena and also a kind of severe natural disaster that influence Iran and its west and southwest part. The location of Iran on the desert belt is accompanied by frequent increasing of sand and dust storm. Integral prediction of dust storm phenomena can be useful in decreasing damages caused by these storms. So synoptic-dynamic analysis of dust storms and their simulation play an important role in achieving to this goal.

In this research, we investigate severe dust storm in August 2005 that affected a large area of our country. Select of dusty days were based on minimum visibility and maximum durability of that dust storm. At first, we show the minimum of daily visibility table. These data has been provided by Meteorological Organization in 5 western cities. The synoptic maps were related to these phenomena derived from NOAA website and synoptic and dynamic interpretation has been done. We have got the data with resolution of 2.5 degree from NOAA website.

Then 700 hpa relative vorticity maps were drawn. We investigate MODIS images instrument on Aqua satellite and evaluate the amount of mass concentration of dust particles. Then the Lagrangian Integrated Trajectory Model has been used to determine the backward trajectory of dust particles. We run HYSPLIT model by GDAS data with a resolution of 0.5 degrees. At last we investigate the output of the WRE-CHEM model. This model was run to simulate dust storms in 7-10 August and FNL data with a resolution 1 degree use for initial and boundary conditions. WRF-CHEM is used to simulate dust condition and transmission. As a part of WRF model, its main application is the study of atmosphere chemistry.

At 500 hpa a very strong ridge entered Iran from the southwest. It covered all areas of our country which prevents the transference of dust to high levels of atmosphere. In 700 hpa relative vorticity maps show one day before dust storm reach to Iran a Positive voriticity is located in Iraq and Syria. So dust comes up to higher levels of the atmosphere and in dusty days in our country. There is a negative voriticity located in our country and because of downside movement of the air, dust storm happen in Iran.

Dust loading and friction velocity of outputs of the model has been drawn in dusty days. The time series of dust concentration of output models for Tabriz are compared with the concentration data of Environmental Organization of visibility data. Result show that a low pressure system is located over the Oman sea that its blaze has been extended to the northwest of Iran. On the other hand a high pressure center is located in the Europe that extended to the east of Mediterranean. So strong pressure gradient were in Iraq and Syria and they caused the creation of strong winds in their deserts which caused dust emission.

Friction velocity related to the model outputs show that the velocity of wind is high in dusty days in Iraq and Syria. So conditions are suitable for dust raining. Satellite images showed that WRF/CHEM model is simulated very well in emission, source, diffusion and the extent of the areas covered with dust. Comparing MP10 concentration of the model output with and Environment Organization data of Tabriz city show that WRF/CHEM model forecast daily changes well. But model underestimate significantly in quantity of concentration. This error may be due to a model considering only dust quantity but other pollutants affected on visibility. In general it can be said that in this event, dust concentration has been underestimated by WRF/CHEM model especially in maximum amount of PM10 concentration.

Iran, due to its geographical location and its human and environmental characteristics including those at risk of natural hazards there. In the area northwestern Iran, Zanjan city in three dangerous fault ,Zanjan in the north, fault Soltanieh in south and Byatlar located in West And based on a hazard map for earthquake country, prepared by the International Institute of Earthquake Engineering and Seismology as well as Based on Earthquake Resistant Design of Buildings (Regulations 2800) prepared by the Research Center, Department of Housing and Urban Development and Urban Country, the relative risk of high-grade is zone. A major part of the Physical structures of Zanjan in recent decades regardless of the strength and stability of the regulations, such as Regulations 2800 is applied.On the other hand the lack of required data, including geometric and non-geometric data of the infrastructure and buildings in the city Such as the problems that have not been noted. Accordingly, this study examines the relationship between resilience Zanjan city's Against Earthquake And indicators and factors affecting resilience Physical and infrastructure to identify And will evaluate the resiliency Physical and infrastructure in the city of the study.

The results of scientific and experimental studies in the field of natural hazards and the head of the earthquake, in the last few decades shows That the best way to deal with these risks, is be more resilient settlement in different dimensions. Settlements in risk reduction approach, resilient system that can temporarily or permanently absorb risks And with conditions changing rapidly, adapted without losing its function.

In this study, the analysis and evaluation; the region and evaluation criteria include Quality building, types of structures building, Old building, facade building, building density,  particle size distribution and land use compatibility. With the explanation that in the analysis of the dimensions and physical infrastructure and support multi-criteria decision-making methods (model Todim) and produced for the processing of the above mentioned methods, is used Arc GIS software. This study is applied and in terms of methodology, quantitative comparative and analytical. This study from to goal ,applied and in terms of methodology, quantitative- comparative and analytical.

International :::union::: strategy for disaster risk reduction program titled "Strengthening the resilience of nations and communities to disasters" in the Hyogo Framework for 2005 to 2015 plan adopted, The program, in addition to reducing vulnerability of communities in crisis, will tend to increase and improve the resilience of communities.

Hyogo Framework for Action (HFA) to motivate more active at the global level in the wake of the International Decade for Disaster Reduction natural framework (2000-1990) and Yokohama Strategy adopted in 1994 and the International Strategy on Disaster Reduction (UNISDR) in 1999, was formed. After the Hyogo Framework period (2015-2005) in order to improve the resilience of nations and communities to disaster, Sendai framework (2030-2015) aimed at the Third World Conference of the United Nations Disaster Risk Reduction in Sendai, Japan in dated March 18, 2015 was adopted.

Generally, in this paper, according to the definitions and objectives resilience, resilience include: 1. The destruction and damage that a system can absorb, without being out of equilibrium, 2. The ability of a system to organize and self-renewal in different situations and 3. Create and increasing learning capacity and strengthen the system's ability to cope with the situation.

In this study, the analysis and evaluation; district and Evaluation criteria include the quality, type of structure, building, old building, the facade of the building, building density, particle size distribution and consistent user. With the explanation that in the analysis of the dimensions and physical infrastructure and support multi-criteria decision-making methods (Todim,s model) And for processing materials produced by the above mentioned methods, GIS software ARC GIS, is used. Todim,s technique is one of the techniques used to solve multi-criteria decision making problems. The technique using pairwise comparisons among decision criteria, accidental incompatibilities of this comparisons to remove it. In this study, according to seven criteria affecting the physical dimensions and infrastructure (quality building, building structures, old building, the facade of the building, building density, particle size distribution and consistent user) to assess the resilience of the 24 districts in Zanjan, a matrix of 24 * 7 production was.

After performing calculations according to the formulas described in steps 1 and 2 of this technique, the performance of each supplier to obtain. Finally, according to the formula Step 3 to obtain the minimum and maximum for each criterion to rank the areas according to the values 0 and 1 action. The highest value obtained from the best available option. This study is applied and in terms of methodology, quantitative comparative and analytical.

Our results can be inferred from That regions corresponding to the North and East of Zanjan due to Old low and relatively new texture That neighborhoods Zibashahr, Amirkabir and PayenKoh, Golestan Andishe and Daneshgah alley, Golshahr Kazemieh, poonak, Vahidieh and Ansarieh covered And most have regular access to the local system and network resilience were presented. But the central and southern parts of city, That old and historic neighborhoods such as Hosseinieh and Bazar, Yidde Borogh, Yery mosque and Dbaghlar are included ,Because of Ancient and worn out textur and also Islamabad Neighborhoods, trans and Bisim, Fatmieh as problematic texture, the degree of resilience of poor and very poor were evaluated. Given the discussion above earthquake fault lines that crosses the city from two sides, Strength and high-level security measures should also be implemented in the arteries of infrastructure and structural elements. On the other hand, in the historic old city neighborhoods in the city should strengthen endogenous development based on standard building regulations 2800 and the geographical structure of the region be made available.

Human communities are affected by hazards, disasters and catastrophic events throughout history, including natural disasters (such as: earthquakes, hurricanes, floods, tornadoes) man-made disasters (such as: nuclear accidents, explosions, socio or political crisis, economic disturbances). Therefore, catastrophic events can have human or natural causes. These conditions show that human communities not only ever been stable, but they are continuously unstable and are exposed to disarranging events. Godschalk knows resiliency an important goal for two reasons. “First, because the vulnerability of technological and social systems cannot be predicted completely, resilience –the ability to accommodate change gracefully and without catastrophic failure- is critical in times of disaster. If we knew exactly when, where, and how disasters would occur in the future, we could engineer our systems to resist them. Since hazard planners must cope with uncertainty, it is necessary to design communities that can cope effectively with contingencies. Second, people and property should fare better in resilient communities struck by disasters than in less flexible and adaptive places faced with uncommon stress. In resilient communities, fewer building should collapse. Fewer power outages should occur. Fewer households and business should be put at risk. Fewer deaths and injuries should occur. Fewer communications and coordination breakdowns should take placeStructural analysis is first of all a tool of structuring the ideas. It gives the possibility to describe a system with the help of a matrix connecting all its components. By studying these relations, the method gives the possibility to reveal the variables essential to the evolution of the system. It is possible to use it alone (as a helps for reflection and/or decision making), or as part of a more complex forecasting activity. This method has 3 phases. Phase 1: considering the variables: The first stage consists in considering all the variables characterizing the studied system (external as well as internal variables); it is good at this point to be the most comprehensive possible and not to exclude, a priori, any possible path of research. Phase 2: description of the relations between the variables: In a systemic vision, a variable doesn’t exist other than as part of the relational web with the other variables. Also, structural analysis allows to connect the variables in a two-entries table (direct relations). Phase 3: identification of the key variables: This last phase consists in identifying the key variables; first, by a direct classification (easy to realize), then by an indirect classification. Direct classification:  The total of the connections in a row indicates the importance of the influence of a variable on the whole system (level of direct motricity). The total in a column indicates the degree of dependence of a variable (level of direct dependence). Indirect classification: One detects the hidden variables thanks to a program of matrix multiplication applied to an indirect classification. The structural analysis method seeks to highlight key variables, hidden or not, in order to ask the right questions and encourage participants to think about counter-intuitive aspects or behavior within the system. The direct influences of each variable on the set of other variables are illustrated in matrix form. Each element of the matrix represents an influence (0 = no direct relationship of influence on the two variables considered; 1 = a direct relationship of influence). We also took into account the level of influence between two variables. The following convention was used: 1 = low relationship; 2 = average; 3 = strong; P = potential relationship.. P levels were also given 0-3 ratings. By reading the matrix, we can classify the variables by their -level of direct influence: importance of influence of a variable on the whole system, obtained through the total of links created per line; - level of direct dependence: degree of dependence of a variable, obtained by the total of links created per column. The direct and indirect influences of the variable represent the system the most realistically. Highlighted are the determining factors (main determinants) of the situation under investigation. The input variables and result or output variables help participants understand the organization and structuring of the system under the microscopeBased on the results of direct influence matrix, social, economic and institutional variables are effectiveness in comparison to others. They have a great impact on system but physical variable effectiveness is much less than its impact. Among of mentioned variables, institutional variable had a significant numerical difference. Indirect cross-impact matrix showed significant differences in the institutional and social variables compared to other variables in the effectiveness and affected. The results indicate the high impact of these two variables on the system. In other words, institutional and social variables were influential factors in their community resilience. According to the results of direct influence matrix, strategic and key factors are including participation, assistance and interactions from social variables, readiness from intuitional variable and in indirect influence matrix; these factors are including participation, social identity, assistance and interactions from social variables and readiness from intuitional variable. Distribution of factors in axis influences of direct and indirect suggests that this system is unstable.

Risk is an inevitable part of life, every day people are somehow at risk. Different risks in various forms and perspectives have different functions. Kurdistan province, with various heights and relatively good rainfall, It results the country's cold spots. Since most of seasonal rainfall occurs in winter, Snow cover is often the domain and passes it hillsides. One of the concerns of people in the mountainous area is a snow avalanche phenomenon. Sudden loss of massive snow is avalanche snow that may include rocks, soil, plants or ice. It seems that the name of the snow avalanche adopted from the eleventh month of the solar year. The possibility of snow in mountainous areas during this month of year is more than other months. Snow avalanches every year around the world, especially in alpine impose huge human and financial losses. Statistics and local evidence also show that the province of Kurdistan expect or accept to soil erosion and destruction of infrastructure and natural resources had a casualty. Actually, this is the most vital reason why zoning area danger avalanche was conducted in this study.

 First, avalanche pathways was recognised and selected as a field visit by department of urban development The purpose of the visit was to extract the geography’s coordinates of the avalanche. The Background of the study shows some of the land criteria are more important than others. For this purpose we performed a literature survey to explore indicators that had a significant impact on avalanche snow like such as; slope, aspect, elevation, convexity and concavity, distance to roads and land. To facilitate greater accuracy, all criteria were used in geographic information system (GIS) for mapping. Thereafter, produced map can be categorised into four classes of low, moderate, high and very high. In the next step. Analytic hierarchy process (AHP) and Analytic Network Process (ANP) model were used for weighting and ranking all criteria (slope, aspect, elevation, convexity and concavity, distance to roads and land use) by using pairwise comparisons with judgments that represent the dominance of one element over another with respect to a property that they share. The Analytic Hierarchy Process (AHP) is a method for decision making which includes qualitative factors. In this method, ratio scales are obtained from ordinal scales which are derived from individual judgments for qualitative factors using the pairwise comparison matrix. The Analytic Network Process (ANP) is a more general form and extension of Analytical Hierarchy Process also uses a pairwise comparison matrix to obtain ratio scales. The difference between these two methods appears in modelling the problem and computing the final priorities for the criteria from ratio scales previously obtained. The ANP feedback approach replaces hierarchies with networks, and emphasizes interdependent relationships among all decision criteria were used in this study).

 Based on the resultant Maps, AHP and ANP had a good overlap with visited points and with high accuracy lay in areas of high risk and very high risk. According to the map provided by Analytic Hierarchy Process from the total number of 30 hillsides, thirteen of them lay in very high risk and seventeen of them in the area of high risk. Thereafter, resultant maps of Analytic network Process shows from the total number of 30 hillsides twelve of them lay in very high risk area and eighteen of them in the high risk area.

The results of (AHP) indicates that from the total area of Kurdistan province, about 1049.7 square kilometres is classified in the low risk area, 11.392 square kilometres in moderate, 14.341 in the high risk area and 2009.1 square kilometres in very high risk area, respectively . In view of the process of the network as map about 978 square kilometres is in low risk area, 10245 square kilometres in moderate risk area, 15410 square kilometres in the high danger area and 2158 square kilometres is located in very high danger area. Therefore, we can use ground data for snow avalanche zoning areas along with Analytic Hierarchy Process and Analytic Network in zoning areas avalanche risk which is applicable. Weather parameters like snow, wind and temperature have an important role in terms of snow avalanche. Decreasing rainfall from west to east of study area. The number of freezing and snowing days indicates the critical situation for snow avalanche in the highlands and the pathways. More prevailing wind direction in the cities are in the Southern west, Southern and in area with high elevation blowing from western direction. Looking at the range of high and very high can be seen, mostly in the North and South and North East which show the impact of prevailing wind upon snow and putting snow in hillsides that can produce snow avalanches

. The hillsides show most of avalanche dangers are at west, northwest and south of Kurdistan thus they are compatible with rainy areas. To build any recreation centred including, winter sports, road construction and expansion, snow avalanche risk areas should be considered. Now pathways don’t have any risk signs warning about avalanches. The warning signs of avalanche at the pathways are essential.In the hierarchical model 198 villages lay at low-risk areas and 20 villages in the area were extremely dangerous. Also in the network model 184 villages in low-risk areas and 23 villages in the area were very dangerous.

Resilience are concepts that are finding increasing currency in several fields of research as well as in various policy and practitioner communities engaged in global environmental change science, climate change, sustainability science, disaster risk-reduction and famine interventions (Vogel, et.al, 2007). Where the risk is a probability of damage, injury, liability, loss, or any other negative occurrence that is caused by external or internal vulnerabilities, and that may be avoided through preemptive action (Benson, et.al, 2004). Among natural disasters, earthquakes, due to the unpredictable nature of these events, are one of the most destructive. Iran is one of the most earthquake-prone countries in the world that its cities most affected by this phenomenon. Among the cities of Iran, Tehran, as the country's first metropolis, due to dense population, poor physical development, structural density, and lack of standards, is potentially facing a serious threat. The purpose of this study is to investigate the spatial flexibility of Tehran over the region 12 after the earthquake incidence.

The present study is dealt with the data preparing and analysis using geospatial methods. The several geospatial data such as Peak Ground Acceleration (AGA) map, urban structure, infrastructure and population collected from Tehran Disaster Management Center were provided and analysis based some GIS known algorithms. In other to urban spatial resilience zonation the AHP (analytical Hierarchy Process) was implemented to generation risk map. Finally OWA (Ordered Weighted Average) method was implemented in order to Production spatial flexibility map of earthquake incidence over the District 12 of Tehran. AHP model uses of priorities straight experts, but OWA provides of control the level of compensation and risk-taking in a decision. Using the conceptual of fuzzy quantifier with OWA makes the qualitative data analysis enter to decision.

    According to flexibility of the final map with fuzzy operator (All) equivalent to the operator MIN, the worst result Was obtained and resulting the highest risk and lowest flexibility respectively (Districts Nos. 2,12,7,8 and 11).By taking all the criteria of a criterion without compensation by other criteria as "non-risk" is obtained .

Map obtained with fuzzy operator (Half) has the high potential to provide suitable options,  because in addition to integration criteria the importance of each parameter based on the weight given to the criteria are considered. In this map Districts Nos.2.6 and 8 (Baharestan, Emamzadeyahya and Sanglajedarkhangah) respectively were most Risk to earthquakes and therefore less flexibility to the earthquake. The map obtained with the fuzzy operator "Atleast one" is equivalent to MAX operator districts Nos. 2,12,7 and 8 (Baharestan ,DarvazehGhar of Shush,Abshardardar and Sanglajedarkhangah)  respectively were most Risk to earthquakes and therefore less flexibility to the earthquake.

The fuzzy conceptual map quantifier showed that districts Nos. 2 and 12 (Baharestan and DarvazehGhar of Shush) were most vulnerable and therefore less flexibility to the earthquake as final results.

The latest report of the Intergovernmental Panel of Climate Change (IPCC) on climate and global warming Indicates that climate change and global warming in particular is one of the most important challenges of the world and drought, as a consequence of climate change around the world, has always influenced the many countries, including Iran. However, it seems that the climate changes, particularly in the West and Iran, especially among farmers and rural communities vulnerable to the effects of economic, social and environmental impacts that are more significant. In other words, Continuous droughts are faced villagers and farmers with various problems and challenges, In this regard, villagers Choose the local and specific strategies in the face of this creeping disaster that improve them adaptive capacity to drought. Nowadays, special emphasis is put on the notion of adaptive capacity instead of vulnerability. So the need to have research in rural levels obvious, especially in Iran where there has not yet been any deep and encompassing study on the concept of adaptive capacity in rural level. adaptive capacity to climate change is the ability of a system or an individual to adjust to climate change or climate variability so as to minimize the potential damages or cope with the consequences. Therefore, adaptive capacity is the ability to plan and use adaptation measures to moderate the effect of climate change. There is an increasing need to develop indicators of adaptive capacity to determine the robustness of response strategies over time and to understand better the underlying processes.

Adaptive capacities of villagers depend on certain factors or attributes such as their knowledge on and number of times they use a particular adaptation strategy. Other factors are the availability and accessibility of the adaptation strategy. Also, the number of consultations that a villagers makes on a particular adaptation strategy affect whether the villagers will be lowly or moderately or highly adaptive to drought.

Identifying the overall level of adaptive capacity to drought in rural areas, in order to Effective management is special importance, Because that by identifying and ranking of adaptive capacity in rural areas, adopt appropriate management strategies to reduce the damage caused by drought is possible.

Therefore, the purpose of this study is assessing the adaptive capacity to drought of between four villages in the central part of the city Rawansar in Kermanshah province. For this purpose five most effective and important index to measure the  adaptive capacity to drought as follows:  Knowledge, Use, Availability , Accessibility and Consultation, according to the literature, were selected. Then by using one sample T-test, the effectiveness of each of the above-mentioned indicators on the villagers adaptive capacity were reviewed and approved from the point of view Village contributors of the central city Rawansar (N = 48) who were selected by census method. In the next step, to determine the index weight, using the snowball technique and purpose sampling, 10 experts in jahad  agricultural  office in Rawansar city were selected and their comments were used. The results by TOPSIS technique based on these indicators, showed that rural areas of Hasan Abad and Zalu Ab  in the Rawansar city, had the greatest adaptive capacity to drought, While  rural areas of Dawlat Abad and Badr had fewer adaptive capacity to drought. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which  is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution (PIS)and the longest geometric distance from the negative ideal solution (NIS).It is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalising scores for each criterion and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion.The findings of this study could have recommendations for rural planners to effective crisis management in order to reduce vulnerability and enhance resilience villagers to drought.

The results of this study indicated that the synoptic patterns that lead to heavy rainfall in 22 March 1996, 24 mar 1995 and 17 November 1994 in the northern portion of FARS province includes: the low pressure that located in eastern part of Mediterranean and Black sea and southern part of Caspian Sea that created by trough that located at the middle level of atmosphere. In addition to this low pressure, the bipolar pattern in of Saudi Arabia  having negative vorticity that lead to transporting moisture from (India ocean, Red sea, Arab sea, Persian gulf and Oman Sea )   and also to be alignment with east Mediterranean sea and black sea low pressure as ascending agent lead to precipitate of rainfall in mentioned days . and also we found that in 29feb 1996 as second patterns rainy day, a strong deep trough transporting moisture from Soudan region and east Mediterranean  low pressure, cause alignment of this atmospheric systems. In fifth patterns (21 mar 2001), existing an low pressure and positive vorticity center in east of Pakistan simultaneously with existing negative vorticity center in central part of Iran, lead to high pressure gradient which cause rainfall events in study area. The main founding of this study were that reveals the role of low pressure of east, north and south of Caspean sea in heavy rainfall events in study area.

Pre-warning of natural hazards events such as heavy rainfall has a significant effect in damage reducing. The analysis of synoptic-dynamic condition of atmospheric circulation patterns, has great importance in recognize affective agents in heavy rainfall events. Especially this heavy rainfall could lead to flash floods suddenly. This study's aim is to analysis and extraction of daily heavy Rainfall lead atmospheric patterns in northern portion of Persian gulf (Helle and Mond Subbasin).

The study area, Helle and Mond basins, with about 21,274, 47653 km2 area,respectively are located in the south of Iran. The Helle basin approximately is between 28° 20'N and 30° 10'N latitudes and between 50° E and 52° 20'E longitudes and Mond basin is between 27° 20' and 29° 55' latitudes and between 51° 15' and 30° 27'E longitudes.These basins are located in sides of a massive sources of moisture, Persian Gulf.

In this study we investigate the data of daily rainfall of 37 synoptic and meteorological station of study area during 1991 to 2011(20 years) to extraction the atmospheric patterns lead top heavy rainfall. In this study in order to archiving heavy rainfall days based on 95 percentile in study area, the data of sea level pressure, geopotantial high of 300 and 500 hp and also data of verticit and stream line and omega in the spatial framework of -10 to 100 longitude and 10 to 70 Latitude has been selected. Then we create the sea level pressure matrix as rainfall associated days, based on Lond method of Correlation to classify days.

Our founding indicated that the main synoptic systems that lead to heavy rainfall is related to low pressure in eastern Mediterranean  and southern part of Caspian sea. So that in detected rainfalls patterns shown that the transporting moisture from nearby sea by high pressure of Saudi Arabia by associating eastern Mediterranean low pressure and deep strong trough in east and southern part of Caspian sea  cause heavy rainfall events in study area. So that the low pressure located in eastern and southern portion of Caspian sea could affect the study area.

One of the most important components of the extent of pollutants mixing and air quality at near the Earth's surface is the height of boundary layer. Many variables involved in determining the height of the boundary layer of atmosphere. Although all of the troposphere (the lower ~10km of the atmosphere) is affected by surface conditions, most of it has a relatively slow response time. The lower part of the troposphere that is affected on a shorter time scale is commonly defined as the Planetary Boundary Layer (PBL). The depth of the mixed layer has a significant effect on the concentration of air pollution, which itself is dependent on the intensity and duration of solar radiation and wind speed. According to Stull, one can describe the planetary boundary layer as “that part of the troposphere that is directly influenced by the presence of the earth’s surface, and responds to surface forcing with a timescale of about an hour or less.”  Surface temperature has a strong relationship with height of the PBL. As the surface cycles between daytime radiation and nighttime cooling the amount of convection taking place changes. When the temperature gradient is steep, more convection takes place to dissipate thermal energy in the most efficient manner. In other words, the greater the temperature difference between the surface and the lower troposphere, the higher convective eddies must reach to alleviate the gradient. Relating this to Stull’s definition of turbulence, it can be concluded that the height of the PBL varies with surface temperature. In fact, the spatial range of the PBL can vary from less than one hundred meters to several kilometers. The strong relationship between convective turbulence and height of the PBL is sometimes used to define the boundary layer and call it the Convective Boundary Layer (CBL). Analogous to the Stull’s definition but focusing on turbulence, Lloyd et all describe CBL as “a layer of air typically of order 1km in depth, well mixed by turbulence maintained by buoyancy due to heating at the ground. It is bounded above by stably stratified, no turbulent air and grows through the day.  In this study we aimed to analysis the status of ABL in 3 dust period days in Khuzestan province of Iran.

The Data were used in this study includes: The Daily data of dust concentration during 27Jan to 1 Feb 2015, the daily height of ABL also were used. The daily data of ABL were given from ECMWF with 1/8 degree spatial resolution. We used the Pearson correlation and synoptic analysis to assessment the condition of boundary layer at the mentioned days. For analysis the characteristic of ABL the climatic data of Wyoming University were used to assessment the thermodynamics of atmosphere. The spatial distribution of ABL height at the dusty day also were used for 12 UTC.

The results indicated there is the direct relationship between the ABL height and the concentration of dust in the mentioned days. So that in the days that the concentration of dust reaches maximum we fund that the height of ABL reaches maximum simultaneously and vis versa. The spatial distribution of ABL height shown that the height of ABL in the 29Jan reaches maximum that the maximum concentration of dust related to this day. And also the minimum concentration of dust observed in 27Jan and 1Feb that the in this day the height of ABL was minimum. The synoptic analysis also reveals that locating the low pressure system at the 500hp level that the Khuzestan province has been locating at the front of this system lead to transport the dust to study area.

In this study we reveal that the height of ABL in the dust days of Khuzestan has a totally revers behavior in compare to the air pollution days in Tehran. In the pollution days in Tehran the lowing of ABL height and inversion lead to intensify the concentration of pollution while in the dust days of Khuzestan the height of ABL were increased in compared with non-dusty days.

Due to the growth of industries and factories, deforestation and other environmental degradation as well as greenhouse gases have been increasing on the Earth's surface in recent decades. This increase disturbs the climate of the Earth and is called climate change. An Increase in greenhouse gases in the future could exacerbate the climate change phenomenon and have several negative consequences on different systems, including water resources, agriculture, environment, health and industry. On the other hand to evaluate the destructive effects of climate change on different systems, it is necessary to initially study the area affected by climate change phenomena. One of the most important effects of climate change on water resource is Drought.  On the other hand, one of the most serious consequences of climate change is how it will affect droughts and water resources.

Drought along with warmer temperature and less precipitation will threaten the water supplies for the crop irrigation, which will directly reduce the production of crops.The climate of the 21st century will very likely be quite different from the climate we observed in the past. The changes will continue to be large in the future period with increasing carbon dioxide emissions. Analyzing and quantifying the signal of climate change will be much in demand considering the above sectors, which are highly relating to the sustainability and human living.

In the past several decades, global climate models have been used to estimate future projections of precipitation [Intergovernmental Panel on Climate Change (IPCC), 2007], and have led to future estimation of drought, to quantify the impact of climate change and comparing the duration  and intensity of droughts under future climate conditions with current climate by using Atmospheric-Ocean General Circulation Models AOGCMs to predict future Precipitation. Global circulation models namely, coupled Atmosphere-Ocean Global Climate Models (AOGCMs) are current state of the art in climate change research. in This study aims at investigating the impact of climate change on droughts conditions in Iran using the Standard Precipitation Index (SPI).

The precipitation time series have been used for the estimation of Standardized Precipitation Index

(SPI) for three timescales, 3, 12 and 24 months, for the region. The outputs of HadCM3-A2 and A1B were applied for the assessment of climate change impact on droughts. One of the major problems in using the output of AOGCMs , is their low degree of resolution compared to the study area so to make them appropriate for use, downscaling methods are required. In this study we have used lars WG for downscaling monthly average of rainfall of AOGCM-HadCM3, and The HadCM3 outputs were downscaled statistically to the study area for a future period 2011-2040.then, was evaluated by the coefficient of determination (R2) between observed and downscaled data.  A method has been used for the estimation of annual cumulative drought severity-time scale-frequency curves. According to the rainfall results, in the 2011- 2040 period rainfall would decrease  to compared to baseline period in the study area.

The SPI time series were estimated (2011-2040) and compared with the respective time series of the historical period 1961-1990. Results revealed that there are decreases in the frequency of severe and mild droughts for the three examined SPI time series while there are increases in the duration of moderate droughts. This implies that droughts will be a concern in the future during the growing season (for the dominant crop) which should be considered in water resources management. specially in the west station of Iran.

Also, these frequency ratios were mapped by GIS on study area. Results showed that generally in the future periods, frequency of droughts ratio of three months drought time- scale will be increase in the North, North West and some parts of the south Alborz mountains and, The Ratio of long ( 24 months) drought for scenario A2 compare to the current climate shows increasing drought in the parts of the North khorasn, sistan and baluchestan and kerman provinces and parts of South West of Iran. scenario A1B shows increasing drought in the parts of the East of Mazandaran , Tehran , Horozgan and parts of Fars and Yazd  provinces.

Finally ,further  more analysis of drought, AWCDS-Timescale-Return Periods computed. These curves integrate the drought severity and frequency for various types of drought. The AWCDS time series were estimated

for basic period and 2011-2040 under scenarios A2 and A1B. The comparison indicated the three types of drought intensity increases for the three examined SPI time series in the South East of Iran.

Drought is the most important natural disaster, due to its widespread and comprehensive short and long term consequences. Several meteorological drought indices have been offered to determine the features. These indices are generally calculated based on one or more climatic elements. Due to ease of calculation and use of available precipitation data, SPI index usually was calculated for any desired time scale and it’s known as one of the most appropriate indices for drought analysis, especially analysis of location. In connection time changes, most studies were largely based on an analysis of trends and changes in environment but today special attention is to the variability and spatial autocorrelation. In this study we tried to analyze drought zones in the North West of Iran, using the approach spatial analysis functions of spatial statistics and detecting spatial autocorrelation relationship, due to repeated droughts in North West of Iran and the involvement of this area in the natural disaster.

In this study, the study area is North West of Iran which includes the provinces of Ardebil, West Azerbaijan and East Azerbaijan. In this study, the 20-year average total monthly precipitation data (1995-2014) was used for 23 stations in the North West of Iran. In this study, to study SPI drought index, the annual precipitation data of considered stations were used. According to the statistical gaps in some studied meteorological stations, first considered statistics were completed. The correlation between the stations and linear regression model were used to reconstruct the statistical errors. Stations annual precipitation data for each month, were entered into Excel file for the under consideration separately and then these files were entered into Minitab software environment and the correlation between them was obtained to rebuild the statistical gaps. Using SPI values drought and wet period’s region were identified and zoning drought was done using ordinary kriging interpolation method with a variogram Gaussian model with the lowest RMS error. Using appropriate variogram, cells with dimensions of 5_×5km were extended to perform spatial analysis on the study area. With the establishment of spatial data in ARC GIS10.3 environment, Geostatistic Analyze redundant was used to Interpolation analysis Space and Global Moran's autocorrelation in GIS software and GeoDa was used to reveal the spatial relationships of variables.

The results showed that most studied stations are relatively well wet and this shows the accuracy of the results of the SPI index. Validation results of the various models revealed that Ordinary Kriging interpolation method with a variogram Gaussian model best explains the spatial distribution of drought in North West of Iran. So, using the above method the stations data interpolation related to SPI index in North West of Iran was done. The results showed that Moran index values for the analysis of results of standardized precipitation index (SPI) in all studied years, is more than 0.95. Since Moran’s obtained values are positive close to 1, it can be concluded that drought, in the North West of Iran during the statistical period has high spatial autocorrelation cluster pattern of 90, 95 and 99 percent. Results also showed that in all the years of study, Moran's global index is more than 0.95 percent. This type of distributed data suggests that spatial distribution patterns of drought in North West of Iran changes in multiple scales and distances from one distance to another and from scale to another and this result shows special space differences in different distances and scales in this region of the country. Results also showed that drought in North West of Iran in 2008 is composed of two parts: Moderate drought in parts of West and North West region (stations of Maku, Khoy, Salmas, Urmia, naghadeh, Mahabad and Piranshahr) and severe drought in the southeastern part of the study area (stations: Sarab, Khalkhal, Takab, Tabriz and Mianeh). So the pattern of cluster drought in the North West of Iran in 2008 is on the first and fourth quarter. The results of this index showed that drought and rain periods are similar in the studied stations. The results of the application of Moran's index about identifying spatial distribution of drought patterns showed that The values of the different years during the period,  have a positive a positive coefficient close to 1 (Moran's I> 0.959344) and this shows that the spatial distribution of drought is clustered. The results of the standard score Z values and the P-Value proved the clustering of spatial distribution of drought.

The results of the analysis of G public value, In order to ensure the existence of areas with clusters of high and low values showed that The stations of Maku, Khoy, Salmas, Urmia, naghadeh, Mahabad, Piranshahr and Parsabad follow the moderate drought pattern in the region and are significant at the 0.99 level. Jolfa station also has a mild drought of 0.95 percent confidence level and for Sardasht station is significant in 0.90 percent. High drought pattern in Sarab, Khalkhal, Takab, Tabriz and Mianeh stations was significant in 0.99 percent level and also for Ardabil, Sahand and Maragheh stations very high drought pattern was significant in 0.95 percent level and for Meshkinshahr and Ahar high drought pattern is significant in 0.90 percent. By detection of clusters of drought and rain in the North West of Iran using Moran’s spatial analysis technique and G general statistics a full recognition of the drought affected areas in this region can be obtained and take the necessary measures in its management 

Most of the large cities in developing countries have faced with the problem of informal settlements. The formation and growth of these settlements for reasons such as rapid and outside the customs building construction are the threatening issue for their communities. Informal settlements are areas that often shaped and expanded in major and middle cities of the Iran’s cities including the city of Parsabad. During the last decades, the rapid growth of urbanization and the lack of appropriate planning for low-income families housing leads to the formation of the urban informal settlements in most cities of the Iran. In most cases, these settlements have a structural and demographic dense texture. The structural texture of these settlements is often fine aggregate, impermeable, and unstable. In times of crisis, the possibilities of human and material losses to them are high.

Environmental hazards such as earthquakes are a serious threat to these settlements. However, these hazards in most developing countries, due to the unavailability and lack of preventive actions, end to the crisis. We cannot prevent earthquakes. But we can reduce the losses and damages caused by the earthquakes. Remove of the disaster is impossible, but it is possible to reduce the damage caused by the disaster. One of the most important ways to reduce the risk of earthquakes is preparation to deal with earthquakes. Preparation means having previous programs and plans.

     Iran is one of the countries where earthquakes always happen. Because Iran located in the world's earthquake belt, each year on average about 1,000 earthquakes happening in Iran. Ardebil and Pars-Abad city, located in an area that the possibility of earthquakes shakings in these areas, is more. The Zire Nahre Torab Neighborhood is one of the Parsabad city’s informal settlements that located in the northwest of the city. Regarding the possibility of an earthquake in the city of Pars Abad, identification and assessment the vulnerability of the neighborhood during an earthquake, is essential. Therefore, identifying and assessing the vulnerability, especially in the poor neighborhoods to offer strategies for dealing with the injuries, is essential. The aim of this study is assessing vulnerability of the informal settlements during an earthquake by using spatial data and GIS. This study, have been prepared in fifth main parts including: introduction and background, methodology and presentation of case study, theoretical framework, analysis and conclusions.  

This research in terms of the nature is practical and is descriptive and in terms of the method is analytical. Three methods including library, documentary and survey have been used for data collection. In the first phase, data and base maps were extracted from documents and reports of projects such as city comprehensive and detailed plans. Also, in this phase of the study data were updated. In the second phase, the problem, questions and research objectives were defined. In the third phase, the 3 criteria and 12 sub-criteria based on research literature and according to available data were selected. In the fourth phase, after preparation of databases related to each of the criteria in GIS, input layers were prepared for each of them. In the fifth step, the method of network analysis process (ANP) was used to determine the significance of criteria. In the sixth phase, the weighted overlay index (WOI) was used for combining output layers.

The results of this study show that more than 80% of neighborhood buildings are vulnerable against the risk of a possible earthquake. Also, research findings suggest that physical characteristics such as building structure, quality and age of the buildings will have the greatest role in determining the neighborhood buildings vulnerability level. Doing activities such as resisting buildings, improving roads, locating facilities in appropriate places, training and informing citizens to prevent a crisis caused by the possible earthquakes, is essential. Other recommendations are listed in below:

1. Identifying vulnerable buildings
2. The use of GIS in the management of settlements
3. Preparations cities, to deal with urban hazards
4. Empowering citizens to deal with environmental hazards
5. Action to reduce earthquake risk
6. Civil engineering Renovation of buildings
7. New practices in the urban construction
8. Equip cities with facilities and relief supplies.
9. The use of specialists in urban planning.
10. Conducting workshops on urban resilience.

Erosion is one of the most destructive and continuous phenomena that cannot be prevented and only could be controlled by studying the chemical and physical properties of soil. Marls are one of the most important sedimentary units in Iran which have high rate in sediment production and erodibility because of their Physico-chemical characteristics. These properties caused large environmental and civil damages and so, the study of erosion and erodibility of the marl units is essential. One of the most important points about marls is grain size nature and elements in them and their effects on amount of erosion. The physical and chemical proprieties of soil are very important in the development of badlands. This study deals with Physico-chemical properties of Marl and its impact on various land forms of erosion in Lotshur-Pakdasht region. Badlands are a typical landform of greatly dissected fine-grained materials in arid or semi-arid environments like Lotshour, although they are also found in different climatic conditions. Climate and geology are several factors determining the tendency to badland formation. Runoff, rain splash, marl and loose formations together with massive wasting processes such as creep, sliding and flow, become the dominant factors determining landform genesis, resulting in the formation of badlands in Clayey-silt slopes.

In this research, in addition to sampling the soil and sediments, rain simulated (using rain simulators) in two marl, two conglomerates and two alluvium  units, in area with different forms of erosion and runoff and produced sediment amounts in each point were measured in laboratory. Also, at the same time, soil samples were taken from adjacent plot and the amount of runoff and sediment produced in the laboratory, separated and measured in the lab for all points. parameters such as Ph, electrical conductivity, content of sodium, potassium, calcium, magnesium, gypsum, chlore, carbonate, solfate, nitrate, organic carbon, CEC was measured. In analyzing the data, analysis of correlations and Pearson and Spearman comparison of means method were used in SPSS software. Also, grain size and Aterberg limits for all samples were determined in lab.

Mineralogical, geochemical and grain-size composition of soil and pore-water chemistry parameters was characterized on both eroded (south-facing) and non-eroded (north-facing). Only a few grain-size parameters and mineralogy discriminate eroded from non-eroded slope substrates. Erosion occurs where the fine fraction is abundant. This may be due to reduced permeability in the eroded soil, whereas the non-eroded one is more stable with respect to weathering, as it is more permeable. The abundance of clay minerals is affected by pedogenetic processes in the non-eroded slope, which increases in mixed layers and indirectly reduces the amounts of other minerals, making clay mineralogy a discriminating parameter in the two different types. Chemical data enable discrimination between eroded and non-eroded slopes. pH, SAR (sodium adsorption ratio), TDS (total dissolved salts), mineralogy and PS (percentage of sodium) are distinctive parameters for both eroded and non-eroded slopes. TDS increases in depth in the non-eroded slope, whereas the maximum TDS is just below the crust in the eroded one. On average, eroded substrates are higher in pH, SAR and PS than non-eroded ones. The ESP (exchangeable sodium percentage) of the eroded slope has a higher value than the non-eroded one. Crusts are less dispersive than eroded substrates, and non-eroded substrates behave as crusts. This suggests that the portion of the slope most severely exposed to weathering tends to stabilize, due to strong decreases in SAR, PS and ESP. Several diagrams reported in the literature show similarly anomalous crust samples on eroded slopes, compared with other samples coming from greater depths on eroded slopes. In the present case study, the exchangeable form of Na characterizes crusts more than the soluble form. The meaning of maximum SAR and TDS (and covariant parameters) is interpreted as the effect of decreased permeability, as suggested by a local increase in the fine-grained fraction, which coincides with maximum TDS. Variations in SAR values are of primary importance for soil erosion, because many authors have used solution chemistry (i.e., SAR, PS, TDS, EC) as a descriptor of dispersity.

            Based on results of analysis of variance in various forms of erosion are significantly different in the sodium ion, sodium absorption ratio and the percentage of clay. The average amount of sodium ion and sodium absorption ratio in marl samples of region, increase from sheet to gully erosion forms while average clay percentage decreases in this trend. Finally, three variables of sodium ions, sodium absorption ratio and clay percentage of marl samples can be significant factors in erosion and related forms in this region. This study describes the erosional mechanism, which involves morphological and geographic exposure and climatic elements, as well as grain size, mineralogy, chemistry and exchangeable processes of soils.

In analyzing the data, correlation analysis and comparison of averages by the SPSS software has been used. As well as a brief comparison between north and south facing slopes that are different in terms of erosion, was also performed. Based on statistical analysis of in various land forms of erosion are significantly different in the sodium ion, sodium absorption ratio and the percentage of silt and clay. The average of sodium ion value and sodium absorption ratio increase from surface to gully erosion form and average silt percent reduced from surface to Gully erosion in marls outcrops in this area. Also, three variables of sodium ions, sodium absorption ratio and clay percent factors can be seen in the erosion of marl and create various land forms of erosion in the region.

Understanding the changes in extreme precipitation over a region is very important for adaptation strategies to climate change. One of the most important topics in this field is detection and attribution of climate change. Over the past two decades, there has been an increasing interest for scientists, engineers and policy makers to study about the effects of external forcing to the climatic variables and associated natural resources and human systems and whether such effects have surpassed the influence of the climate’s natural internal variability. The definitions used in the 5th assessment report were taken from the IPCC guidance paper on detection and attribution, and were stated as follows: “Detection of change is defined as the process of demonstrating that climate or a system affected by climate has changed in some defined statistical sense without providing a reason for that change. An identified change is detected in observations if its likelihood of occurrence by chance due to internal variability alone is determined to be small.  Attribution is defined as the process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence”. Detection and attribution of human-induced climate change provide a formal tool to decipher the complex causes of climate change. In this study the optimal fingerprinting detection and attribution have been attempted to investigate the changes in the annual maximum of daily precipitation and the annual maximum of 5-day consecutive precipitation amount over the southwest of Iran.

This is achieved through the use of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources Project(APHRODITE) dataset as observation, a climate model runs and the standard optimal fingerprint method. To evaluate the response of climate to external forcing and to estimate the internal variability of the climate system from pre-industrial runs, the Norwegian Climate Center’s Earth System Model- NorESM1-M was used. We used up scaling to remap both grid data of observations and simulations to a large pixel. This remapped pixel coverages the area of the southwest of Iran. The optimal finger printing method needs standardized values like probability index(PI) or anomalies as input data, since the magnitude of precipitation varied highly from one region to another. The General Extreme Value distribution (GEV) is used to convert time series of the Rx1day and Rx5day into corresponding time series of PI.  Then we calculated non-overlapping 5-year mean PI time series over the area study. In this research, we applied optimal fingerprinting method by using empirical orthogonal functions.  The implementation of optimal fingerprinting often involves projecting onto k leading EOFs in order to decrease the dimension of the data and improve the estimate of internal climate variability. A residual consistency test used to check if the estimated residuals in regression algorithm are consistent with the assumed internal climate variability. Indeed, as the covariance matrix of internal variability is assumed to be known in these statistical models, it is important to check whether the inferred residuals are consistent with it; such that they are a typical realization of such variability. If this test is passed, the overall statistical model can be considered suitable.

Results obtained for response to anthropogenic and natural forcing combined forcing (ALL) for Rx1day and Rx5day show that scaling factors are significantly greater than zero and consistent with unit. These results indicate that the simulated ALL response is consistent with Rx1day observed changes. Also, it is found that the changes in observed extreme precipitation during 1951-2005 lie outside the range that is expected from natural internal variability of climate alone and greenhouse gasses alone, based on NorESM1-M climate model. Such changes are consistent with those expected from anthropogenic forcing alone. The detection results are sensitive to EOFs. We estimate the anthropogenic and natural forcing combined attributable change in PI over 1951–2005 to be 1.64% [0.18%, 3.1%, >90% confidence interval] for RX1day and 2.5% [1%,4%] for RX5day.

Urmia Lake is one of the largest hyper saline lakes in the world and largest inland lake in Iran which located in the north west of Iran, between the provinces of East Azerbaijan and West Azerbaijan. The lake basin is one of the most influential and valuable aquatic ecosystems in the country and registered as UNESCO Biosphere Reserve. In addition, it is very important in terms of water resources, environmental and economic. Unfortunately, lake water level has dramatically decreased in recent years, due to various reasons. This issue has created some problems for Local people, especially people living in rural area in east of the Lake. The results of this research are of great importance for regional authorities and decision-makers in strategic planning for people of inhabits in east coast village.

The present paper is an attempt to integrate a semi-automated Object-Based Image Analysis (OBIA) classification framework and a CA-Markov model to show impacts of Urmia Lake Retrogression On eastern coastal villages. OBIA present novel methods for image processing by means of integration remote sensing and GIS. Process and outcome of this methodology can be divided in three step including: Segmentation, Classification and Accuracy assessment.in the process of segmentation aims to create of homogeneous objects by considering shape, texture and spectral information. A necessary prerequisite for object oriented image processing is successful image segmentation. In our research the segmentation step was performed by applying multi-resolution segmentation and considering 0.2 for shape and 0.4 for the compactness. The scale of segmentation is also an important option which leads to determine the relative size of each object. Having great values for scale leads to create large objects while smaller value would result small objects respectively. In this study the scale parameter of 100 has been selected based on the size of objects in Scale of study area as well as spatial resolution of the satellite images were used for segmentation. In doing so, we employed spectral and visual parameters contains: texture, shape, color tone and etc. for developing object based rule-sets.  To determine the characteristics of the spectral data and geometric features classes the fuzzy based classification was performed by employing fuzzy operators including: or (max) operator with the maximum value of the return of the fuzzy, the arithmetic mean value of fuzzy and the geometric mean value of fuzzy, and (min). After this step, the validation process was performed by using overall accuracy and Kappa coefficient. Then, using the CA-Markov Model The trend of changes was predicted in the future (For 2020). Another way to predict changes in land use and cover, used the CA-Markov model. Markov chain analysis is a useful tool for modeling land use changes. Markov chain model consists of three step: First step Calculating the probability conversion using Markov chain analysis, second step, Calculating the Cover and land use maps competently on the basis of multi-criteria evaluation, third step, assign locations cover and land use simulation based on the CA position operator.

Results of Satellite image processing indicate that the area of garden, Farmland, Zones of muddy-salty (Saline soils), moist salt and newly formed salt have increased while area of Urmia lake has rapidly dropped between 1984 and 2015. The area of Urmia lake declined from 4904.51 square kilometers in 1984 to 676.79 square kilometers in 2015. The farmland area increased from 177.72 square kilometers in 1984 to 542.37 square kilometers in 2015. The garden area increased from 83.71 square kilometers in 1984 to 227.28 square kilometers in 2015. The moist salt area increased from 111.89 square kilometers in 1984 to 945 square kilometers in 2015. Zones of muddy-salty (Saline soils) area increased from 859.01 square kilometers in 1984 to 2986.5 square kilometers in 2015. The newly formed salt increased from 171.27 square kilometers in 1984 to 921.99 square kilometers in 2015. Markov chain model results indicate in 2020 the garden area will be 638 square kilometers, the moist salt area will be 717 square kilometers, Zones of muddy-salty (Saline soils) area will be 4127 square kilometers, the farmland area will be 644 square kilometers, the newly formed salt area will be 363 square kilometers and the Urmia lake area will be 118 square kilometers.

Drought is one of the most important hazards that occur in all the earth especially in arid and semi-arid climates. Every year, about half of the earth’s surface experienced droughts and while drought is not a constant feature of any climate but occur more frequently in arid and semi-arid regions of the world. Although the occurrence of droughts cannot be prevented but by studying the nature and characteristics of droughts and also identify factors that affecting their occurrence useful information can be gained about drought and their destructive effects. The researches in recent years designed and proposed a lot of indices to study and analyze the droughts and today various characteristics such as intensity, duration, area and so on with these indices are studied. Many indices used by researches to analysis and identify properties of climatic droughts and dry periods. In these indices often the variables of precipitations, combination of precipitations and temperature, humidity or evaporation, crops yields and teleconnection climatic indices are used.

In this study using the CPEI index and 30 years (1980-2009) daily rainfall data in 40 synoptic stations overall Iran, to analysis and assess of Iran droughts suitable variables detected. Four seasons and annual period is considered in this study. To determine the appropriate variables in the design of suitable models and modeling of drought to assess and predict droughts Otun in 2005 proposed CPEI index as Conjunctive Precipitation Effectiveness Index. He selected 10 conjunctive precipitation variables as ORS(Onset of Rainy Season), CRS(Cessation of Rainy Season), LRS(Length of Rainy Season), TWD(The Total no of Wet Days), TDS(Total no of Dry Spell), TDW(Total no of Dry Days within a Wet Season), TDY(Total no of Dry Days within a Year), LDS(Length of the Dry Season), MDL(Maximum Dry Spell Length within a Wet Season), MAR(Mean Annual / Seasonal Rainfall Depth) and determined the relationships between variables in each synoptic stations and climatic regions. Since the units of measurement the rainfall variables are diverse, it is essential that the units be converted to a standard unit, in other words variables be standardized. The relationship between variables was determined by Pearson correlation coefficient. Finally, the right combination of precipitation variables for each station through the proposed formula Otun(2005) were determined. In the end, for each of the seasons and the annually period regionalization maps were prepared.

 All 40 synoptic stations were evaluated by Otun’s method (Aton, 2005). The results showed that 95 percent of stations in spring, 75 percent in fall, 57 percent in winter and 75 percent in annual period are compatible with used method. Thus, spring, fall and winter seasons and also annual period are compatible with above mentioned index. Among the used variables MAR, MDL, TDY and TDS which with respectively are as follows: total amount of precipitation in any period, the maximum duration of dry periods in a wet period, the total number of dry days in a wet period and the total number of dry period during wet period among the stations are more abundant. In annually period, in addition to the above mentioned variables, precipitation variable of LPS (length of dry period) also seen among some stations. Also, results showed that CPEI index can be used on most stations and climatic regions of Iran. It was also found that the spring compared the other seasons and annual period is more comparable on the base of CPEI index.   

  Otun in 2010 used the CPEI index in semi-arid region of Nigeria and has achieved good results. The results of our study show good agreement with Otun’s work. The use of this index in the study of meteorology, climatology, agriculture and many environmental projects can be beneficial because in many of these fields of study, precipitation and its characteristics have an important role. In general we can say that in regions where CPEI index does not show a high proportion or set of variables are not enough it is better to use other indices such as SPI and RAI. The results obtained in similar climate zones such as Nigeria has shown that CPEI index has very good ability to identify and explain the precipitation effectiveness variables which can be used in modeling of droughts and dry periods. There are many similarities between combination of precipitation variables that identified by CPEI index for Iran and other regions of the world. Similarities, especially with respect to MAR, MDL, TDY and TDS are abundant.

Today slum refers to those areas of the city which are not necessarily situated at the corners of the city, but to those which are in margins from economic, social, cultural, and other urban life aspects, that has formed a settlement in which the least living-supplies of healthy water, electricity and gas, transportation system and a clean environment suffice their lives. This type of settlement is due to the asymmetry and commonality of features and conditions of living in the main parts of the city. And generally indicate the low level of living conditions in comparison with the average standards in the main city specifically, and also in living conditions in cities as a whole. On the other hand, informal settlement refers to the discordance of settlement with the approved regulations of governmental organizations and particularly of municipalities. Those areas which are situated outside the servicing scope of the general and governmental organizations such as electricity, gas, and telecommunications offices, along with municipalities accompany various phenomena such as urban poverty, poor housing, immigration from countryside to cities, environment pollution, unhealthy environments and etc.

            In Iran, slum began in the 30s (solar calendar) with the immigration of village dwellers to the cities, and after a decade, it was prospered due to land reforms and economic-social policies of the day, a growing increase which has never stopped since. Slum or informal settlement in the outer parts of the cities is not just a physical notion but is an outcome of the macro structural factors in economic, social, cultural, and political aspects in a national or regional scope. The reasons for this phenomena vary which can differ from one place to another. Nevertheless immigration is one of the main reasons for slum settlements. It can simultaneously play two roles; it can be a solution to demographic crises. It leads the surplus population out of the region and accordingly the human power is directed where is needed most. It balances the structural asymmetries of population and by reducing the development imbalances in different regions result in the betterment of the status quo. And on the other hand, it might be possible that by immigration of the human power, the economic equilibrium between the source and destination community would be disturbed, and by having a community without any human power, it generates complex social and cultural situations; which all in all leads to a congested crowd overpopulating specific big cities and regions.  In this way, it brings about problems in servicing and efficient regulation of issues and thus be regarded as a disturbing element of development and mutual understanding. The investigated region has been exposed to the crises of immigration and slum settlements recently, so much so that based on the population and housing census of 2006, population growth rate of Shahriar rose by a far distance from other cities to 8.7 percent. Thus, this research was conducted to investigate the elements of immigration and slum dwelling in Shahriar city. And it aims to answer these questions:

1. How social, economic, and demographic factors influence the slum settlements of those who have migrated to this city?
2. How is the local dispersion in Shahriar?

On this basis, with the researches and investigations conducted at the outset of the study, district 2 was selected as a fit choice out of the three districts of 1, 2, and 3 which settled slums. Since all the locals were not slums in this specific districts, with proper investigation the slum areas were identified which had a high rate of immigration; with whom interviews were ran and questionnaires distributed. To this end, by following Cochran formula, 200 people were selected as samples through cluster random sampling out of the statistical community. To analyze data, descriptive statistical methods such as central index, dispersion and inferential statistics like Chi-square, Wilcoxon and Friedman tests were utilized.

The results of the  study indicates that the slum in Shahriar are situated in the old and cheap sections of the three districts of 1, 2, and 3. Also, after a detailed examination it was proved that Shamloo local in district 2 is more suitable than the other ones. On the other hand, by investigating the economic factors (such as job opportunities and income) it was indicated that immigration is very important from the aspect of providing job opportunities. Secondly, social factors are more important in slum settlements issues. For instance, one can refer to urban and welfare facilities, educational facilities, health and recreation facilities are all social factors. On the other hand, those people who have migrated due to pursuing education, higher level of welfare, better facilities etc. are all below 30 years old. Based on the findings of this research, families were not significantly changed after immigration in comparison with the period before it, but it is a vital element in three membered families in times of immigration. All has been done to meet the financial needs of the family. Therefore, one can claim that most immigrations to slum areas have been due to economic and social deficiencies of the source society.

Accessibility to precise spatial and real time data plays a valuable role in the velocity and quality of flood relief operation and subsequently, scales the human and financial losses down. Flood real time data collection and processing, for instance, precise location and situation of flood victims may be a big challenge in Iran regarding the hardware facilities (such as high resolution aerial imagery devices) owned by the correspond organizations. To overcome the mentioned inabilities as well as reducing the financial costs for real time monitoring purpose of a flood, the current research intended to use the capacity of the flood victims and other volunteers to collect and upload real time data to rescue themselves. By means of this, flood real time spatial and non-spatial data collection is applicable via public and per-person participation based on the needs of each victims. The current Open Source workflow has been so designed that by using a browser like Mozilla, Explorer, Chrome and etc., and without the need for installing any software, the victim transmits his/her exact geographic location (captured automatically by the designed web service) and other multimedia data such as video-photo. Also, the flood-affected person announces the type of the damage and consequently, demanded rescue operation to the managers as a text information. After data processing on the server, the information is represented as a real time rescue map for decision making. The rescue plan may be mapped based on the singular aid as well as plural plan in the cluster form specialized for a particular group of victims in each bounding box. To design the web service, a client architecture for victims, other volunteers and managers has been developed, for implementing the service, Open Source technologies, server-side and client-side programming languages, Geoserver and WFS (Web Feature Service) standard adopted by OGC for spatially-enabled representation of victims demands, have been exploited. The research result is a browser-based service in which the client service offers automatic zooming to the current location of the clients and sends the rescue request including personal identifications and the type of injury using PHP (stands for Hypertext Preprocessor) and SQL (Structured Query Language). In the other side, on the client side designed for managers, the requested rescue submitted by the victims and other volunteers are mapped and displayed real time by OpenLayers and WFS. The result introduces an efficient applicable method for gathering real time and high accuracy geographic-multimedia-text data collection and consequently, extremely reduces the relief operation costs. Finally, the proposed methodology causes better performance and spatially clustering of victims to decrease the aftermath of the flood in a region like Iran suffers from the lack of expensive hardware technologies for precise data collection and transmission.

Trees in urban areas have survived in a wide variety of conditions and constrains, whether developing in natural or manmade habitats. Due to environmental constrains and stresses, urban trees rarely achieve their biological potentials. Indeed, some of trees, in small groups, could excel in terms of age, biomass structure and dimensions in urban areas. In definition, tree hazard includes entirely dead or dying trees, dead parts of harmed live trees, or extremely unstable or unsteady live trees, which could be in result of structural defects and disorders or other factors that have the high risk to threaten the safety of people or property in the event of a failure especially in urban green spaces. Although the pruning or other rehabilitation and mitigation program of trees is known as the one of the principal domains of green space management, it is still includes shortcomings in terms of models and methodologies to classify or prioritize hazardous trees which need to be treated timely. The main objectives of this study were to: (1) model old Sycamore failure hazard in urban green spaces to elucidate the general and defects tree factors affecting on failure hazard; (2) prioritize the impacts of model inputs (general and defects tree factors) on tree failure hazard using model sensitivity analysis and (3) determining the trend model output changes in respond to model variables changes.

The following types of data (target trees characteristics) were solicited for each target tree: (1) General features: Tree Height (TH), trunk Diameter at Breast Height (DBH), Butt Diameter (BD) at ground surface and Vertical Length of Crown (VLC) were calculated from measured girth. Crown Spread (CS) was measured as the average of two diameters of projected drip line of the tree canopy.

(2) Tree defects: Detailed evaluation of individual trees was made according to 6 key physical defects, namely Internal Decay (ID) in percent, Length of Cracks (LC) in m, Crown Defoliation (CD) in percent, and Degree of Leaning (DL).

(3) Sycamore failure hazard classification: Sycamore Failure Hazard Risk (SFHR) classification was the probability that an entire tree, or part of it, will break and fall within the first or second year after study. Considering results of tree regular monitoring after two years, the following classes of tree failure hazard were determined. 1. Extremely Hazardous: Tree failure in the first year. 2. Semi-Hazardous: Tree failure in the second year.

ANN has been recently developed for data mining, pattern recognition, quality control, and has gained wide popularity in modeling of many processes in environmental sciences and engineering. ANN learns by examples and it can combine a large number of variables. In this study, an ANN is considered as a computer program capable of learning from samples, without requiring a prior knowledge of the relationships between parameters. To objectively evaluate the performance of the network, two different statistical indicators were used. These indicators are Mean-Squared Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R²).

In this study, the year of Sycamore failure in urban ecosystems is evaluated using tree variables and artificial neural network to determine the most effective tree variables in SFHR in urban green space. Various MLFNs were designed and trained as one and two layers to find an optimal model prediction for the SFHR and variables. Training procedure of the networks was as follows: different hidden layer neurons and arrangements were adapted to select the best production results. Altogether, many configurations with different number of hidden layers (varied between one and two), different number of neurons for each of the hidden layers, and different inter-unit connection mechanisms were designed and tested.

In this research, 200 trees were totally selected, then general and defects tree variables were recorded in urban green space. Considering the aim of study, which is discovering the relation between general and defects tree variables with SFHR class for modeling, the year of tree failure, was recorded.  

In the structure of artificial neural network, general and defects tree variables were tagged as inputs of artificial neural network and SFHR class was tagged as output layer. Considering trained networks (the structure of optimum artificial neural network has been summarized in Table1), Multilayer Perceptron network with one hidden layer and 4 neurons in layer created the best function of topology optimization (Table2) with higher coefficient of determination which equals 0.87 for class 1 and 0.9 for class 2. Sensitivity analysis respectively prioritizes Crown Spread (CS), Vertical Length of Crown (VLC), Degree of Leaning (DL) and Butt Diameter (BD), which effect on SFHR in class1 (Fig1) and class 2 (Fig2).

The determined procedure of SFHR changes with CS changes in the region declares SFHR increase nonlinearly with an increase in CS. The determined procedure of SFHR changes with VLC changes o declares that SFHR increase nonlinearly with an increase in VLC of tree. The determined procedure of SFHR changes with DL changes in the region declares SFHR increase nonlinearly with an increase in DL. The determined procedure of SFHR changes with BD changes o declares that SFHR increase nonlinearly with an increase in BD of tree.

Nowadays, artificial neural network modeling in natural environments has been applied successfully in many researches such as water resources management, forest sciences and environment assessment. The results of research declared that designed neural network shows high capability in SFHR modeling which is applicable in green space management of studied area. Sensitivity analysis identified the most effective variables which are influencing SFHR. So, to identify hazardous trees in study area, we should pay attention to the CS of Sycamore trees as the variable with high priority in determination of SFHR. We believe that, in hazardous trees management in urban green spaces, we should pay attention to some modifiable factors of tree, which are CS and VLC, by timely tree pruning. We suggest urban green space manager to run SFHR model, for tree stability assessment, before decision making on hazardous trees.

Hazard is potential source of harm or a situation to create a damage. So identification of zones exposed to hazards is necessary for planning or land use planning. But this situation becomes more critical when they appear at the population centers. So applying the principle of passive defense based on environmental capabilities is unarmed action that caused the reduction of human resources vulnerability, buildings, equipment, documents and arteries of the country against the crisis by natural factors such as drought, flood, earthquake, etc. Considering the possible occurrence of such risks in population centers, ready to deal with what is known unpleasant and undesirable consequences is necessary. On this basis and given the importance of population centers in Helle and Mond basins, in this study, the authors tried to analyze the Rain hazards of drought and flood.

The study area,Helle and Mond basins, with about 21,274, 47653 km² area, respectively are located in the south of Iran. The Helle basin approximately is between 28° 20'N and 30° 10'N latitudes and between 50° E and 52° 20'E longitudes and Mond basin is between 27° 20' and 29° 55' latitudes and between 51° 15' and 30° 27'E longitudes.These basins are located in sides of a massive sources of moisture, Persian Gulf.

In this study, data from 23meteorological and synoptic stationsstations, during aperiod of20 years (1992-2011)in northern region of the Persian Gulf (Mond and helle basins)were used to calculate Standardized Precipitation Index (SPI). The data were collected by the Iranian Meteorological data website (http://www.weather.ir). The SPI is primarily a tool for defining and monitoring drought events. This index may be computed with different time steps (e.g. 1 month, 3months, 24 months). The SPI is defined for each of the above time scales as the difference between monthly precipitation (xi) and the mean value ( ), divided by the standard deviation. To assess flood risk zones, the flood, annual evapotranspiration, cities and populations centers layers were collected in Helle and Mond basins position. The annual precipitations and the SPI maps were drawn by Geostatistics, Kriging. It also the flood and annual evapotranspiration layers were weighted by Euclidian distance method, separately. Finally, all layers are weighted by AHP and fuzzy-linear methods (descending and ascending linear function) into vulnerable layers. The final map of vulnerable areas with flood and drought high risk was drawn based on the algorithm of linear-Fuzzy in a raster format.

According to the results, eastern, north eastern and south eastern part of Mond basin had high annual precipitation. Based on this result, it said that these parts of study area were known the least dangerous areas of vulnerability. The results also showed that with passing of the western regions and going to the center of the study area the annual rainfall have been added over the years. Kazeron, Chenar Shahijan, Firouz Abad, Borm plains and some parts of Khane Zenyan and Dash Arzhan are cities located in this regions. Low latitude, Proximity to the warm waters of the Persian Gulf, low annual precipitation and high temperature causing evaporation and inappropriate environmental conditions in Boushehr province and some coastal cities such as Genaveh, Deilam, Boushehr, Baghan, Lar and Khonj. Accordingly, west, north west, south and south west regions in Helle basin were located in extreme vulnerability zone with a loss of annual rainfall for drinking and agricultural production and poor nutrition underground aquifers.