نشریه تحلیل فضایی مخاطرات محیطی
سال چهارم شماره 3 (پاییز 1396)

The simplest definition of urbanization is that urbanization is the process of becoming urban. Urban climate is defined by specific climate conditions which differ from surrounding rural areas. Urban areas, for example, have higher temperatures than surrounding rural areas and weaker winds. Land Surface Temperature is an important phenomenon in global climate change. As the green house gases in the atmosphere increases, the LST will also increase. Energy and water exchanges at the biosphere–atmosphere interface have major influences on the Earth's weather and climate. Numerical models ranging from local to global scales must represent and predict effects of surface fluxes. The urban thermal environment is influenced by the physical characteristics of the land surface and by human socioeconomic activities. The thermal environment can be considered to be the most important indicator for representing the urban environment. Vegetation is another important component of the urban ecosystem that has been the subject of much basic and applied research. Urban vegetation influences the physical environment of cities through selective absorption and reflection of incident radiation and regulation of latent and sensible heat exchange Satellite-borne instruments can provide quantitative physical data at high spatial or temporal resolutions. Visible and near-infrared remote sensing systems have been used extensively to classify phenomena such as city growth, land use /cover changes, vegetation index and population statistics. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted Normalized Difference Vegetation Index and Heat Island Intensity.
I conducted all spatial analysis in the UTM Zone 39 Northern Hemisphere projection. The fundamental procedure I used for evaluating change in land surface temperature was to relative temperature for both images, so that the values are temperature difference between the coldest and hottest areas in Tehran metropolitan. subtracting these images from each other results in relative temperature change from 2003 to 2015. Landsat satellite data were used to extract land use/land cover information and their changes for the abovementioned cities. Land surface temperature was retrieved from Landsat thermal images. The relationship between land surface temperature and landuse /land-cover classes, as well as the normalized vegetation index (NDVI) was analyzed.
In this study, LST for Tehran metropolitan was derived using SW algorithm with the use of Landsat 8 Optical Land Imager (OLI) of 30 m resolution and Thermal Infrared Sensor (TIR) data of 100 m resolution. SW algorithm needs spectral radiance and emissivity of two TIR bands as input for deriving LST. The spectral radiance was estimated using TIR bands 10 and 11. Emissivity was derived with the help of land cover threshold technique for which OLI bands 2, 3, 4 and 5 were used. The output revealed that LST was high in the barren regions whereas it was low in the hilly regions because of vegetative cover. As the SW algorithm uses both the TIR bands (10 and 11) and OLI bands 2, 3, 4 and 5, the LST generated using them were more reliable and accurate. NDVI negatively affected LST and Urban Heat Island in vegetation areas in 2003 and 2015 in Tehran metropolitan. This analysis provides an effective tool in evaluating the environmental influences of zoning in urban ecosystems with remote sensing and geographical information systems. This method exhibits a promising performance in UHI forecast. The predicted LST confirms that urban growth has severely influenced UHI pattern through expanding the hot area. Our study confirmed that LST prediction performance is strongly depended on the resolution.
The results reveal that the urban LST is affected mainly by the land surface characteristics and has a close relation to the abundance of vegetation greenness. The spatial distance from the UHI centre is another important factor influencing the LST in some areas. The methodology presented in this paper can be broadly applied in other metropolitans which exhibit a similar dynamic growth. Our findings can represent a useful tool for policy makers and the community awareness of environmental assessment by providing a scientific basis for sustainable urban planning and management. This provides an effective tool in evaluating the vegetation greenness of different zoning in urban ecosystems with remote sensing and geographical information systems. From the perspective of land use planning and urban management, it is recommend that planners and policy makers should pay serious attention to future land use policies that maintain a relevant proportion of public space, green areas, and land surface physical characteristics.

Thunderstorms are one of the most important, abundant and severe atmospheric hazards. In addition to destroying a large amount of agricultural products and construction projects, cause many human casualties are annually in different parts of the world (Iran Pour and et al, 2015). This phenomenon is associated with severe storms, showery precipitation, hail (Puranik and Karekar, 2004), and thunder and lightning (Nath et al, 2009). These storms occur 50,000 times on a daily Basis. They account for 18,000,000 yearly (Ahrens, 2009). Extensive studies have been conducted in Iran and the world in this regard. For example, Wallace (1995) examined the abundance of lightning in the United States using 100 stations. He concluded that the greatest frequency of convectional showers occurs early in the night and at least at midnight. Sterling (2003) described the thunderstorms as a major dilemma for the United States in the twentieth century. The environmental and economic consequences of thunderstorms and their associated phenomena such as floods, hail and heavy precipitation are believed to be very ruinous on the US economy. Sistan and Baluchistan Province, Iran has annually been witnessing a variety of thunderstorms systems and associated precipitation. The province has suffered lots of damage resulted from the phenomena caused by thunderstorms. Therefore, this article aimed for a spatial analysis and the frequency of thunderstorm occurrences at different time scales. The article also examines the temporal variations and trends. The secondary questions outlined here are as follows: At what time of day do thunderstorms occur? How are thunderstorms recorded as various codes? Which one of these codes is the most commonly reported one? In terms of location, what are the stations with the greatest and least number of thunderstorms?
The area under study is Sistan and Baluchistan Province, Iran. With an area of almost 187,502 km2, the province is located in the southeastern part of Iran, on the Oman Sea coast and in the vicinity of Pakistan and Afghanistan. The province has 300 km water border with the Oman Sea in south, 1100 km land border with Pakistan and Afghanistan to the East, Khorasan Province to the North, and Kerman and Hormozgan to the West (Ebrahim Zadeh, 2009).
In this study, the frequency of thunderstorms was extracted based on 7 synoptic stations and the used of Presence Weather Codes. Temporal variations were then studied using the Man-Kendal and Sen's non-parametric tests. Finally, the relationship between the thunderstorms and ENSO was investigated. Meanwhile, spatial dispersion was also taken into account.
The results showed that thunderstorms have a peak region in southeast part with the center of the Saravan and Iranshahr stations and a minimum area in the Oman Sea coasts (Konarak and Chabahar). More precisely, Saravan Station scored the top with 567 thunders and lightning, while Konarak Station hit the lowest point with 96 in this 30-year period. In the maximum thunderstorm region, Saravan and Iranshahr are the main centers during different seasons so that the number of thunderstorms is higher in summer and fall in Iranshahr compared to Saravan. In winter and fall, such thunderstorms, caused by extra-tropical origin, are more in Saravan than Iranshahr Station.
The results of hourly investigations of thunderstorms showed that most of thunderstorms occur at noon and 3:00 p.m. Codes 13 and 17 were the most frequently reported codes with 605 and 571 occurrences, respectively, Codes 99 and 5 were the least. Monthly investigations showed that May and March had the highest number of thunderstorms (322 and 317, respectively), while September accounted for the least number (55). Quarterly investigations showed that spring had the highest number of thunderstorms (756) followed by winter (559). These thunderstorms are seen in spring more than other seasons because of the passage of extra-tropical air masses, which is abundant in the region under study. Summer, which is the Sub-tropical High pressure (STHP) season, had the least number of thunderstorms (340 occurrences of thunder and lightning). These thunderstorms mainly occur in Iranshahr and Saravan Stations, which was proven in the spatial analysis. The summer incidence increase of the thunderstorms is rooted in the Monsoon systems, preparing the ground for the phenomenon. The temporal variations at different monthly, quarterly, and yearly scales showed that no significant differences are found in thunderstorm trends. The phenomenon has experienced enormous fluctuations, likely to be associated with complex changes of macro-climate patterns. El Nino and the Lanino are likely to be the main factors affecting the ENSO's warm and cold phases. According to the results, almost 70% of thunderstorms are associated with the El Nino. In other words, more thunderstorms are expected during ENSO's warm phase.

Agricultural development depends on increasing production and productivity and reducing risks threatening the agricultural sector and in the shadow of extension risk management that can be prevented of wasting and damage to agricultural crops and the provision of necessary domestic agricultural production, also providing export and currency-made to advance the country's development goals. Pay attention to the strategic location of Mazandaran in citrus products, natural hazards that threaten citrus production each year in the economic development, production and exports and providing sustainable livelihoods to farmers affected negatively. Agriculture and in particular the subdivision gardening, due to dependence on weather conditions, the brunt of climate change is undergoing, horticulture stable on long-term behavior growers to ensure the stability and productivity of the land in the future is created and the expectations and concerns of the community intended to provide a food healthy and security to protect the environment and natural hazards reduction is concerned.
The main purpose of this study was to investigate Mechanisms of Reducing Natural Disasters and Risk Management to Sustainable of Citrus Gardens in Mazandaran Province. The Population consists of all citrus farmers in the villages of 12 counties of Mazandaran province, a sample of 290 farmers was selected by using proportional random sampling method among 122361 citrus Orchard men. Data were collected by means of a questionnaire. The Validity of questionnaire was determined through sustainable agriculture experts of Mazandaran County and some faculty members at the University of Tehran, Department of Agricultural Extension and Education, Agricultural Management and Development. The reliability was found to be acceptable. Diagnostic validity by using an average variance extracted (AVE) and reliability by using Cronbach's alpha and composite reliability (CR) were confirmed. To explain the mechanisms Confirmatory Factor Analysis (CFA) was used to modeling the structural equations using LISREL software, version 8.80.
According to the results of the ranking factors related to the mechanism in dimensions, "supportive - credit", "environmental - spatial", "socio-participation", "knowledge-awareness", "infrastructure-institutional "," educational –informational" and "economic factors" respectively were mostly mechanisms and strategies based on factor coefficient. Among the credit-supportive, "insurance" has had the most important role in the structure of credit-supportive factor, thus, according to the regional agricultural insurance and damages in the event that the actual performance of the target area is less than the guaranteed performance is a good solution. One of the major goals of sustainable agricultural systems is decreasing vulnerability and improving sustainable livelihoods in rural people. Therefore adoption of GAP technologies has emphasized to increase elimination of pest with minimum impact on the environment, human health and access to sustainable agricultural development, (achieve to environmental, economic and social sustainability) as well as attention to the sustainability of on-farm activities to certain safety and quality of food and non-food agricultural crops. According to the study, understanding and awareness of farmers to improve skills and farming and horticulture management techniques to reducing natural disasters and risk management and expand the participation of farmers in risk management, to develop processing and packaging industries, convenient and refrigeration practices for storage and preservation of agricultural and horticultural crops, in addition to communication channels network through demonstration farms, farmer field schools, workshops, field days, meeting, SMS, and information and communication channels carried by ICT as necessary solutions recommended. This Provides Information and knowledge share among orchardist and strengthening local associations and with each other. This process helps them to increase their awareness about mechanisms of reducing natural disasters and risk management to sustainable of citrus gardens and find positive attitude toward it. This output complete sustainability goals of agriculture through improving social sustainability. In order to access growers to timely sales service products, the establishment of a new extension system based on an available market with up to date and secure information as Marketing Information Services (MIS) could be a suitable strategy for orchardists in order to access sustainable development.

As a result of climate change and reduction in rainfall during the last decade, drought has become big problem in the world, especially in arid and semi-arid areas such as Iran. Therefore drought monitoring and management is great of important. In contrast with the traditional methods which are based on the ground stations measurements and meteorological drought monitoring, using the remote sensing techniques and satellite imagery have become a useful tool for spatio-temporal monitoring of agricultural drought. But using of this technique and its results still need to be evaluated and calibrated for different areas.
The aim of this survey is to study the spatial and temporal patterns of drought using remote sensing and the regional meteorological data in the Markazi province. For this purpose, the MODIS satellite data between the years of 2000-2013 have been used to monitor and derived vegetation indices. Drought indices based on satellite data including the Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Temperature Vegetation Dryness Index (TVDI), and Soil Water Index (SWI) were obtained from the MODIS satellite data for the period of study for different temporal scales (seasonal, biannual and annul).Then, correlation between obtained results from satellite data and standardized precipitation index (SPI) have been analyzed in all time periods.
Results show that study area has a low to medium vegetation cover. According to the results, the climate situation of the study area is more compatible with the seasonal results of the VCI, and VCI was selected as the best indicator for agricultural drought monitoring in the study are. The obtained results from the applying of VCI over the area show the drought condition in 2000 and 2008 and the wetness in 2009 and 2010 during the study period.

The field of natural hazards research has a rich history in geography, appropriately so because it involves conflicts between physical processes and human systems. Natural events occur without direct human effect and endanger his social life. Events that enforce average annual up to 150000 human damages and more than 140 milliard dollars financial damages on counties and especially developing countries. Among all the natural disasters, the earthquake is one of the most serious ones. It brings tremendous economic losses and deaths of people, as well as the enormous effects on the harmonious and continuous development of society. Iran is an event ism country in the world. In this field look at the recent decades earthquakes statistics that reveal average once in every five years.
Gilan province is located in south western of Caspian Sea in mountainous area of Talesh and central Alborz range that endure many earthquakes up today. The most ancient earthquake ever occurred in this area refers to Marlik civilization which is located near Rudbar – Rostam Abad. One of the recent earthquake in the 20th century in this area is Rudbar earthquake in 21 Jun 1990 with magnitude Ms = 7.7 Richter that caused many destruction. In one hand according to complex tectonic of central Alborz and in the other hand locating Gilan in the south west of Caspian sea that demonstrate many seismic activities, it illustrates as a result that this area is one of the active high potential seismic area of Iran.
The current study is aimed at investigating the earthquake vulnerability of rural and urban settlements of Gilan province. To this end, Euclidean distant analysis and raster overlay have been conducted in GIS. To run the procedure, the first step is to calculate distance (pixels in 86 m dimension) between province and active and inactive fault line based on Euclidean analysis distance in Arc Map. The next step is aimed at standardizing the calculated distances using Raster Calculator Command. The, zoning of earthquake vulnerability of Gilan into five zones (based on active/inactive faults) is the primary goal. As a matter of fact, standardization leads to fuzzy maps. Standard score (distance) is calculated by dividing each score by sum of the scores. The next step tries to categorize zoning map and to translate Raster map into vector one in order to calculate the area of each risk category. Finally, overlay of urban and rural layers base on zoning map may help us analyze seismic hazard urban and rural regions of Gilan province.
Results have shown that 40.72 % of total area of Gilan province are in 15 km distance from active fault. Also, 21.51 % of total area of Gilan province are in 15 to 30 km distance from active fault. Additionally, 64.45 % of total area of Gilan province are in less than 8 km distance from inactive fault (Table 1).
According to seismic hazards due to active faults, 18 cities out of 51 urban regions are severely vulnerable to earthquake. Accordingly, 67.20 % of Gilan urban population are located at high-risk zone. Seismic hazard zoning map based on active faults have indicated that 20 cities are highly vulnerable to earthquake. (Table 2)
Seismic studies on rural settlement of Gilan province have indicated that 1350 rural out of 2925 rural residences are severely vulnerable to earthquake because they are near to active faults. These regions are the habitat of 24.9 % of the total rural population. Zoning map based on inactive faults have shown that 1679 rural regions are vulnerable to earthquake (Table 3).
Studies have claimed that the majority of rural and urban regions of Gilan province are severely earthquake-prone. It is due to geographic and natural features of the mentioned province. To this end, some recommendations are given:1.Meticulous supervision on safety of building from the stage of plan-making to administration which have to be based on engineering principles for earthquake-prone cities including Baresar, Ataqur, Asalem, Haviq, and Roodbar which are next to active faults
2.Prevention of formation of suburbs and towns on southern and northern parts of Gilan because these parts are really vulnerable to earthquake
3.Prediction of temporary accommodation in central Gilan because this part is less vulnerable to earthquake
4.To equip buildings, hospitals, schools, and other buildings located in big cities including Rasht, Bandar-E Anzali, Fuman, and Lahijan with facilities required in case of earthquake
5.To hold training courses in rural and urban parts of the mentioned province to make residents prepared for earthquake and for emergency evacuation
6.To prioritize reformation of old and historical buildings in Rasht because Rasht is mostly laden with old buildings which are really vulnerable to earthquake.

International studies show that the damages caused by natural hazards is essential that special attention to natural hazards in urban societies of the world, especially in urban areas of developing countries. In many of these communities needed new ways to deal with these challenges. This method should provide sufficient knowledge to identify the nature of problems and the identification of individual characteristics, socio-economic, physical, environmental and management, would in effect do the "Back to Balance" against natural hazards. This feature Back to Balance the same resiliency. The term resilience has a very long history and its use goes back at least a century BC. According to the different interpretations of the concept of resilience, this term is rooted in the traditions of various disciplines such as law, engineering, ecological and social sciences. Today, the concept of resilience has entered the field of planning with different orientations (social, economic, physical, and administrative, etc.).Although it still focuses more attention on environmental issues and a large part of its exploration dedicated to managing the environmental hazards such as earthquakes, floods, hurricanes and global warming. Tehran, as a result of political and economic influence, special conditions to deal with the crisis in terms of the influence of natural disasters and crisis management in terms of organizational structure and legal. In this respect, residential and urban areas of 12 with characteristic their history can be acute against the imbalances caused by natural hazards and create a crisis in urban life. Therefore, the present study has been prepared for the purpose of stability analysis flexibility in District 12 of Tehran metropolitan city.
This is of cognitive research that has been done for analytical and descriptive. All data is obtained in the manner of library and field. The library of available resources and work conducted the form of a questionnaire survey. Questionnaires have been used of type Likert spectrum (numerous, high, high, somewhat, relatively low, low and very low), and its completion is done by fieldwork. Statistical population has problems of urban planning experts, among them 80 people were interviewed for targeted samples. Resiliency that includes four dimensions (economic, social, ecological, environmental and institutional). Was approved the validity of the index by 7 experts manage urban planning problems. For measuring reliability coefficient is calculated Cronbach's alpha equal to 0/79. For data analysis, the use of statistical analysis such as frequency, maximum and minimum, average and standard deviations, T-Test one sample test and Friedman nonparametric test
The results of the indicators of urban resiliency against natural hazards suggests that economic indicators 73/24 Average been determined and relatively low level, ie below the average level. Results of the test showed one sample T-Test is an indicator of economic status of urban resilience against natural hazards of poor utility. As well as the social, ecological, environmental and institutional (organizational) urban resilience against natural hazards associated with poor utility. Finally the 12 metropolitan Tehran metropolitan areautility resilience against natural hazards with respect to all dimensions were too weak. Friedman test results on the scoreboard indicators showed that the index of environmental sustainability (20/33) related to the ecology and environment in the first rank the importance of urban resilience and adaptability Index System (10/11) related to next institutional (organizational) is set as the least significant indicator. Also, significant chi-square statistic is calculated at a rate of 09/67 in three degrees of freedom at the level of 0.000. So, with a probability of 99% can be said that there is a significant difference between the performance rating of 80 specialist urban resilience dimensions (economic, social, ecological, environmental and organizational) against natural hazards, and not the distribution of the same rank.
This research been prepared with the aim of assessing the scale of urban resilience against natural hazards in District 12 of Tehran Metropolis. Results showed that social, environmental and institutional ecology and urban resilience against natural hazards associated with poor desirability. According to this result, it is concluded that the region as a whole is resilient against natural hazards. In this direction, the resilience approach guidance to managers and practitioners use of flexible decisions and concerted policy for urban management. Build resilience in this area to support programmes should invest in organizing access to both external and existing resources in a fair manner, with a coordinated governance structure, and to facilitate social solidarity and support as part of disaster response. The findings also stress the importance of taking an ecological approach to studying resilience to disasters. Many factors from individual, community, and societal levels seem to be important in shaping resilience perceptions of natural hazards survivors. Understanding this evidence will help to validate and further develop indicators of resilience. Our findings point out that, despite existing pre-disaster vulnerabilities, resilience can be fostered following disasters if community members perceive availability of aid and support and mobilize resources Hence, psychosocial support programmes should invest in organizing access to both external and existing resources in a fair manner, with a coordinated governance structure, and to facilitate social solidarity and support as part of disaster response. The findings also stress the importance of taking an ecological approach to studying resilience to disasters. Many factors from individual, community, and societal levels seem to be important in shaping resilience perceptions of natural hazards survivors. Future research should conduct multiple levels of analysis with an all-hazards perspective to reveal how they can be integrated to increase adaptive capacities. Future research should focus on the process of capacity building through informing action to better prepare for disasters. Finally, this research tells us that due to the resiliency of the city will be able to have knowledge of all relevant indicators in the resiliency and reduce the adverse effects of these risks in urban communities.

Urban climate is strongly influenced by the processes of urban work and life. Expansion of cities and consequently increased human constructions causes to changes in urban climate. The rising temperature of cities rather than the surroundings is one of the effects linked to direct human intervention.
Building heating, air pollution and the use of inappropriate materials in the flooring streets (like asphalt streets due to dark colors in energy-absorption) are effective in phenomenon of urban heat islands that makes unfavorable environment for citizens. Paying attention to the urban surfaces like sidewalk, streets and rooftops has a great role in decreasing effect of this phenomenon. Due to growing urbanization and subsequently cities development, urban heat islands have taken a growing trend in big cities.
In general, the urban heat-island is a result of urbanity features, air pollution, human warmth, presence of impervious surfaces in the city, thermal properties of materials and geometry of urban areas. Heat island phenomenon is a result of many factors that are summarized below: (1) urban Geometry (morphometry) (2) thermal properties of materials which increase the sensible heat storage in the urban texture (3) released human heat as a result of fuel combustion and animal metabolism (4) urban greenhouse gases, leading to an increase in long wave radiation, atmospheric contamination and therefore warmer atmosphere (5) reduction of evaporation levels in cities, which means that energy will be released more as tangible rather than latent heat (6) reduction of turbulence and heat transfer through the streets.
This study aimed to simulate and calculate the maximum amount of heat island (UHI max) according to the conditions of urban geometry in the region of Kucheh bagh in Tabriz that is a pioneer study in Iran.
The study area is located in Kuche bagh region at the intersection of the streets of Ghods and Farvardin in the city of Tabriz.
The Oke’s numerical-theoretical equation was used for this study. First, the geometry of the target area using the radius of 15 meters from the axis of the road was divided into separate blocks. The ratio of street width (W) and height of buildings (H) was calculated in GIS software and at the end, the intensity of UHImax was calculated and simulated using Oke equation.
The urban geometry including building height and street width is calculated using Equation 1.
The theoretical- numerical basis of this equation shows that simulation of H/W ratio is an appropriate ways to describe urban geometry. Increasing the value of this ratio could lead to an increase in urban heat-island through modeling. This model has many advantages compared to other methods used to estimate the urban heat island. So, the selected parameter to calculate urban geometry and the model used to estimate the maximum intensity of heat island is the ratio of H / W and OKE model, respectively. In addition, the average height of buildings located within a radius of 15 meters and an average width of passages were calculated from the equation 2 and 3, respectively.
After calculating the geometry of the study area, the results showed that the blocks E, G and D in terms of height of the buildings have a heterogeneous distribution, but the distribution of blocks C, I and J is illustrative of their standard configuration. Although the blocks E, F and J in terms of street width are less diverse compared to other blocks, but in terms of height of buildings (8.6, 7 and 5 meters) have a different pattern that maximum values of their UHI are 8.3, 7.5 and 6.3 degrees, respectively. Three blocks B, H and I, in addition to their similarity according to street width and height of the buildings, in terms of the ratio of H / W and heat island intensity with the values of 9.6, 9.8 and 10.2 degrees are homogeneous.
It was also found that the greatest difference between the H / W ratio is related to block A (0.54) and block H (1.98); this difference has caused that greatest difference between the maximum intensity of UHI would calculated between the two blocks equal to 5.2 degree.
Misconfiguration causes that energy leaving from city surface deal with the problem due to narrow passages and high buildings. Therefore, consideration appropriate width of passages and streets and height of buildings are necessary to ease heat leaving and reduce intensity of UHI.
These simulations showed that high buildings and narrow streets intensify the heat islands. While in the presence of short buildings and wide streets, the UHI max is lowered. When the ratio H / W in the studied urban area is between 0.54 to 0.81, UHI max remains between 5 to 6.6 C˚, when this ratio increases to 1.01 to 1.98, UHI max will be between 7.5 and 10.2 C˚. The result also revealed that block A and H with 5 and 10.2 C˚ have the minimum and maximum value of UHI intensity, respectively. So can be concluded that block A and H have the most standard and non-standard urban configuration in the region. The estimates from regression model showed that the street width (91.6%) is more effective than the height of the buildings (6.6%) in changing UHI max.