Journal of Spatial Analysis

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Global temperatures have increased in the past 100 years by an average of 0.74°C (IPCC, 2013), with minimum temperatures increasing faster than maximum temperatures and winter temperatures increasing faster than summer temperatures (IPCC, 2013). Total annual rainfall tends to increase at the higher latitudes and near the equator, while rainfall in the sub-tropics is likely to decline and become more variable (Asseng et al., 2016). Considering probability of occurrence climate change and its hazardous impacts, it seems essential to clarify future climate. General Circulation Models is widely used to assess future climate and its probable changes. Although the outputs of these models are not appropriate for small-scale regions because of its coarse resolution. Thus, statistical or dynamical techniques are used to downscaling the outputs of these models using observed data in weather stations. Despite the fact that frequent researches has done in relation with climate and climate change, but it is unclear yet future climate, especially climate change, in Iran. The goal of this study was to present the results of climate change predictions which has been done so far in Iran, in order to help prospective studies in this field. This step can be important to consider new questions and challenges. In this study, we assessed future climate change in Iran using results of statistical downscaling studies of atmospheric-oceanic General Circulation Model’s outputs. To do this, studies on prediction of precipitation and temperature parameters in Iran by different emission scenarios, atmospheric-oceanic General Circulation Model’s outputs and statistical downscaling techniques were gathered. Then a comprehensive view about Iran's future climate and specifically the climate changes presented by descriptive-content based analysis and comparison of their results. Used downscaling techniques in these researches were included: LARS-WG, SDSM, ASD, Clim-Gen and used General Circulation Models were: HADCM3, BCM2, IPCM4, MIHR, CGCM3, CCSM4 and finally used emission scenarios were A1B, A1, A2, B1, B2, RCP4.5. Based on climatically geographical differences in Iran, the results discussed separately in six different regions across Iran. The results of various regions are different because of usage of different models and different climatological and geographical conditions. These models simulate temperature more accurate than precipitation, because of more variability and temporal discontinuity of the precipitation relative to temperature. Assessment of results in 30-year periods from 2011 to 2099 showed that in North West of Iran (Ardebil, Azarbayejan- Sharqi and Azarbayejan- Qarbi provinces), precipitation will be decreasing, decreasing- oscillating, decreasing- transitional and temperature will be increasing. Decreasing- transitional trend, in other words decrease precipitation in cold seasons and increase of it in warm seasons, lead to a decrease in the snow occurrence and an increase in the rainfall occurrence. Thus, it can affect the frequency of floods occurrence. In west and southwest region of Iran precipitation has been predicted to have different changes in various sections of it. It will be decreasing-oscillating in Kermanshah and Kordestan provinces and oscillating in Hamedan province. Precipitation will increase in Lorestan and finally it expected to decrease in Khoozestan, Chaharmahal-va-Bakhtiari, and Ilam. However Temperature will rise across this region. In south and south east region of Iran (Fars, Hormozgan, Kerman and sistan-va-Baloochestan provinces), precipitation will be decreasing, decreasing-oscillating, oscillating and increasing-oscillating. Also in this region, temperature expected to increase similar to other regions. In east and north‌ east of Iran (Khorasan Shomali, Khorasan Razavi and Khorasan Jonobi provinces), temperature predicted to be increasing-oscillating, that it is different with other regions. Changes in precipitation will be oscillating and decreasing-oscillating. In the northern coasts of Iran (Gilan, Mazandaran and Golestan provinces), precipitation changes will be decreasing and increasing-oscillating and temperature changes expected to be increasing and increasing-oscillating. Thus, it expected to increase heat wave, drought, and aridness condition as the results of these changes. Precipitation changes in south of Alborz region and center of Iran (Semnan, Tehran, Qazvin, Markazi, Esfahan and Yazd provinces), will be decreasing, oscillating, increasing-oscillating. Also temperature will be increasing in this region. Considering the decreasing trend of precipitation and the increasing trend of temperature in the most of Iran, it is probable to increase the occurrence of climatic and environmental hazards such as flood, drought and heat waves in the future. These events can have serious effects on water resources, agriculture and tourism, especially in regions such as Iran where have sensitive environment.

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Land cover changes as a basic factor in environmental change act and has become a global threat. In this research, changes in land cover in rural tourism areas by neural networks, Markov chains in software ArcGIS, ENVI, Terrset using the TM and OLI satellite imagery, Landsat Satellite was surveyed for a period of 30 years for three periods of 1985, 2000, and 2015. The findings of the first stage show that land cover changes at the period 1985-2015, were classified in five class residential spaces, Commercial, Green, Empty and mountainous spaces and communication networks. In this study, the area of mountainous and empty spaces (13.25%) has decreased and in contrast, has decreased the amount of green spaces (6.221%), Residential (5.258%), commercial (1.264%) and communication networks (0.529%). Changing land cover as one of the most important environmental risks has been directly influenced by the Commodification phenomenon. Also, the findings of the prediction using the Markov-CA chain showed that with the continuation of the current and excessive loading on the ground, on the horizon of 2030, green cover (Agriculture, gardens and grassland, garden and residential)  and  wild land  and mountain cover have been reduced and to cover residential and commercial villas will be added. Based on research findings concluded that land cover changes in rural tourism areas in order to achieve more profits has become incompatible applications. This change in land cover, in addition to the economic, social impacts, has led to the formation of environmental hazards in the Bharang area. Developing tourism in the study area by removing agricultural land from the production cycle has led to an increase in urban activities and the formation of new activities (service, Residential Garden, residential villa) instead of traditional activities(agriculture and livestock) that are economical. And by loading too much ecological power tolerable land, while posing environmental hazards, causing incompatible activities next to each other, they do not match. Therefore, tourism, which gradually formed over the years and now it has become a part of rural texture, Spatial Conflict and heterogeneity two strains has created for them. Spatial Conflict created, due to changes in land cover and acceptance of incompatible activities that derive from human-nature relationships. This means that the rapid and unpredictable trend of tourism development, the rural landscape has encountered a problem and with changes in land cover, has led to inconsistencies between different activities and eventually has shaped the Spatial Conflict.
 

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Analysis and Measurement of Environmental Resilience of Villages in Gorganrud Watershed against Flood (Golestan province, Iran)
 
Abstract
Environmental hazards are inevitable phenomena that always place serious risks on the development of human societies, especially rural development. In the recent years, however, significant changes have been made in crisis management approaches, and the prevailing view has shifted from the "reduction of vulnerability" approach to "resilience improvement". Resilience is a new concept often used in the face of unknowns and uncertainties. Therefore, along with this change of attitude, it is important to examine and analyze natural hazards in terms of resilience. According to global statistics, floods, as one of the most devastating natural disasters, have caused the greatest losses and casualties to human settlements, which is true both in our country and in Golestan province. Investigations show that only in the statistical period of 1991-2014, 106 rainfall cases have led to the occurrence of floods in this province. These floods have damaged natural resources, the environment and the prevalence of environmental pollution; In addition, other natural and human factors have contributed to the heightened risk of flood damage. But if it was planned for the restoration of villages, then the damage could be reduced. Therefore, this research was conducted with the general purpose of determining the relationships between environmental factors and factors of rural communities of Gorganrud watershed on their resilience and numerical values. Finally, the residual spatial analysis of rural limited settlements was studied. Accordingly, the research questions are as follows: a) What is the relationship between environmental factors and factors in the villages of Gorganrud watershed in Golestan province with the resilience of the communities living in them in the face of flood? b) What are the resiliency values ​​of these communities in the environmental dimension and which zones? This is an applied research with descriptive-analytical method. A library of researcher-made questionnaires was used for collecting data using library resources. The statistical population consisted of 106 villages with 22,942 households. First, 31 villages were selected by cluster sampling. Then, using Cochran formula, 318 families were selected as sample size and selected by simple random sampling method. Also, for assessing the validity of the questionnaire, using Delphi collective wisdom methods, it was determined by using historical studies and opinions of experts in rural areas. The reliability of the questionnaires was also determined by using the Cronbach's alpha coefficient in the pre-test method. The value for the household questionnaire was r_a1=0.841 and r_a2=0.862, respectively. All steps for statistical analyzes have been performed by Excel and SPSS software. Additionally, the development of mapping, risk-taking, risk and resilience was also done with the help of ArcGIS software and the weight of each criterion was determined by the Super Decision tool; Then, using the weighted and linear overlapping methods, each of the sub-criteria of the main indexes was multiplied in its weights. The study area is divided into two distinct sections in terms of geological and geomorphological structure. The southern and eastern parts of it are the ripples of the eastern Alborz mountains, which are taller in the southern part and extend along the east-west direction. Also, the northern part of the studied basin is the Gorgan plain, in which the main branch of Gorganrud flows from east to west and all branches of the south and east are drained. Following the general slope of the main branch and its long-standing walls in the mid-east, it is usually not flooded; but as far as the west is concerned, its slope is very low and one of the flood plains is considered as the basin. The results of the research show that there is a significant relationship between the environmental factors of the studied basin villages and the resilience of the communities inhabited by them in the face of floods. Also, the average environmental resilience of the whole region was lower than the average (2.76 average), rural households in the sub-basins of TilAbad and ChehelChai with an average of 3.24 and 3 had relatively good environmental resilience, But most of the rural households in the sub-basins of Ghurechai and Lower of Gorganrud, Mohammad Abad-Zaringol, Madarsoo and Sarisoo, with an average of 2.89 to 1.85, had a poor environmental resilience. In addition, According to the flood risk resilience map, it can be said that of the total 31 sample villages studied, about 29 percent of sample villages have "medium upward" resilience in facing flood risks; conversely, most of these villages (71%) also have relatively low degree of resilience. Also, comparing the findings of this study with the results of most other researches, such as the studies of Olshansky and Kartes (1998) regarding the necessity of considering the environmental factors of settlements, observing the necessary environmental standards and the necessity of using proper land use management tools to reduce risk hazards and improve resilience, Center of Emergency Management Australia (2001) on the need to consider the state of the infrastructure, including the level of communications and accesses, biological conditions, including the status of pollution, as well as geographical characteristics, such as distances and proximity, climate, topography, as well as the general results of studies by Rafiean et al. (2012) in special selection of the most suitable model of resilience based on the combination of carter and socioeconomic model due to the simultaneous attention of this model to its geographical features and its comprehensiveness, as well as attention to the local communities' participation, Rezaei (2010), Shokri Firoozjah (2017) and Anabestani et al. (2017) Regarding the low value of the calculated population, the resiliency number of the society is consistent and consistent with the lack of attention to infrastructure issues, locations, etc., which is below the baseline (3). As a result, all of the aforementioned components of the resilience of inhabitants of sample societies have been affected by its environmental dimension, which is often due to insufficient attention and insufficient handling of them, which reduces resilience of rural residents to flood risks.
 
Keywords: Environmental hazards, Flood, Vulnerability, Resilience, Spatial analysis, Golestan Gorganrud basin.
 

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Identifying spatial patterns in vulnerability involves a comprehensive look at vulnerable points. And provides analytical power to the authorities. Therefore, it is necessary to recognize patterns of vulnerability so as to minimize the amount of damage to them in the event of a crisis. The city of Tehran, as the political and administrative center of the country, is faced with a variety of risks due to demographic burden and physical development. In this research, we tried to analyze the spatial distribution pattern of urban vulnerability to natural hazards in social and physical dimensions in Tehran's 7th region. The method of this descriptive-analytic study and the model used for trigonometric fuzzy logic. The results indicate that: According to the z score, the positive values are 1.96 up, which form the clusters of hot spots in the southeastern region of the arena; It is a sign of more vulnerability in these areas. Also, negative values of 1.96 and less, which are statistically significant and blue, have formed cold spots, And it is interpreted that low vulnerability zones are clustered in space and are mainly located in the northwest. Therefore, the lower the color range in the red and blue areas was less statistically significant  to the point where this positive net worth is 1.65 that in this situation, the spatial behavior of the vulnerability is considered to be non-significant in terms of hot or cold clusters with high and low values and spatial autocorrelation that the map is also displayed in yellow.
 

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Abstract

Urban heat island (UHI) is one of the environmental phenomenon which has made difficult environmental conditions for citizen. This study aims to evaluate the spatial and locational variability of Esfahan urban heat island according to the role of land use. Thus an area about 190.2 square kilometers (km2) in Esfahan, as the microclimate, was studied. In order to analyze the relationship between land use and land cover changes on Esfahan urban heat island, the images of Landsat 7 (TM and ETM +) and Landsat 8 (OLI / TIRS) on 20 July 1989, 17 August 2005, 18 August 2014 have been used. The results show that the urban areas has experienced 31% changes in positive direction; while the agricultural sector and green space havehad a reduction of 25% in their area. The analysis of the intensity of heat island show that heated cores are related topoor and barren lands with about 37/33 and 36/5. Although the most area of thermal classwere related to warm thermal class in 1989 and 2005, the average thermal classes were about 63/8%in 2014. Moreover, the locational variation distribution of Esfahan heat island shows that the locationof the heat island has gradually changed. For example in 2014 it included small parts in the south of the city, military zones and barren lands in the south, some parts in the north west and north east areas and small areas in the east of Esfahan. This means that urban development isn’t the main factor of the surface temperature increase and urban heat development, but rather the type of land use has influenced the decreasing or increasing of air temperature.

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Simulation of floodplain zones in Tehran's metropolitan watershed (case study: Kaan basin)
Ezaatollah Ghanavati, Associate prof. Geographical science faculty, Kharzmi University
Ali Ahmmadabadi. Assistance prof. Geographical science faculty, Kharzmi University
Negar Gholami, MA in Geomorphology, Geographical science faculty, Kharzmi University
Extended abstract
Floodplains and adjacent rivers are always at risk from flood events due to their specific circumstances. Flood prone area identification in the watersheds is one of the basic solutions for destructive flood control and mitigation. Flood mapping is one of the best methods for flood prone area planning and identifying. Considering the importance of flood hazard, it is important to understand the role of uncertainty and incorporate that information in flood hazard maps. The hydrodynamic modeling approach is suitable for accounting various uncertainties, and thus lends itself to creating probabilistic floodplain maps. For  this purpose,  flow  boundary  conditions,  peak  instantaneous  discharge with  different  return  periods,  cross  sections and their distance and roughness coefficients for each cross section were entered to HEC-RAS hydraulic model in Kaan watershed  located  in  the Tehran  province,  Iran,  and  this model was  then  run  and  flood water surface profile at different return periods were estimated. In the Kaan Basin, most residential and agricultural lands are located in a very small distance from the river bed. The rapid growth of construction, human activities and land use change in the downstream of the basin have caused a change in the hydrological cycle and runoff production. Floodplain mapping using hydrodynamic models is difficult in data scarce regions. Additionally, using hydrodynamic models to map floodplain over large stream network can be computationally challenging. Some of these limitations of floodplain mapping using hydrodynamic modeling can be overcome by developing computationally efficient statistical methods to identify floodplains in large and ungauged watersheds using publicly.
The aim of this study is to determine flood areas within 20 kilometers of the Kaan River by using the HEC-RAS model and Arc GIS software to identify flood lands in different return periods.
The Kaan basin is located in the central Alborz Mountains. This basin is limited to south, north, east and the west respectively to Tehran, Jajrood Basin, Darakeh Basin and Karaj River Basin. The most important River in the area is the Kaan River and originated from high mountains.
Most commonly, the hydrodynamic modeling approach is used to create flood hazard maps corresponding to a rare high flood magnitude of 100-year return period or higher. Although this approach can provide very accurate floodplain maps, it is computationally demanding. As a result, the modeling approach to flood hazard mapping works well for individual streams, but its efficiency drops significantly when used to map floodplains over a large stream network. In this research, floodplain areas in the Kaan basin in return periods of 2 to 20 years are determined using the HEC-RAS model and the HEC-geoRAS extension. For this purpose, digital maps 1: 25000, DEM (10m), discharge values of Sulaghan Station, morphological characteristics of the river bed and cross sections have been used. Digital Elevation Models (DEMs) play a critical role in flood inundation mapping by providing floodplain topography as input to hydrodynamic models, and then enabling the mapping of the floodplain by using the resulting water surface elevations. Finally, the data is entered into the HEC-RAS software and analyzed. After determining the flood ranges in the various return periods at each cross-section, enter the results to the Arc GIS software and the flood zoning maps were obtained.
In this research roughness coefficients (Maning^,s coefficients) for each cross section were obtain be the
n= (nb+n1+n2+n3+n4) m                                                             (Eq.1)
Geological map and field observations have shown that the main difference between the widths of the valley in the study area is related to the type of rock. The results of the hydrodynamic model show that in the river upstream, the increase in discharge had led to the water level increase and expansion in the floodplain surfaces. But in the middle and low slopes in the downstream of the river, due to the reduced discharge, the river has a larger lateral extension and the flood areas are larger than the upstream of the river. Also, for a longer period of return, the discharge rate and the water level increase and the flood plain was more extensive. The results show that in the downstream of the basin due to instability the bed, existence of wide and eroded chanels, high ability in sedimentation, erosion of the channel bed, and low impact of vegetation, this section They can be restored and regenerated and constantly changing. Due to the location the Tehran-North high way from the Kaan basin, had the construction of roads and structures, the flood plain areas of the river should be fully observed or retrofitted.
 
Key words: Environmental hazards, Flood, Flood areas, Kaan River, HEC-RAS
 
 
 
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Zoning and Spatial Analysis of Potential Environmental Hazards
Case study: Silvana District
Abstract
Natural hazards can be considered as one of the most important threats to humankind and nature that can occur anywhere in the world. Natural hazards are one of the main obstacles to sustainable development in different countries and one of the important indicators of the development of world countries is their readiness to deal with natural hazards. Therefore, it is important to pay attention to it and appropriate measures should be taken to reduce the vulnerability of human settlements. Nowadays with increasing population growth, population dynamics and the large number of people exposed to various types of disasters, the need to identify environmental potential hazards and identification of hazardous areas are felt more and more. Meantime, some people may not be aware of potential hazards of their place of residence. So by identifying and evaluating potential hazards and their Risks before the occurrence, we can significantly reduce the severity of the damages and contribute to sustainable regional development. The negative effects of natural disasters can be minimized by the availability of comprehensive and useful information from different areas and Multihazard mapping is one of the most effective tools in this regard.
According to the above mentioned, in this study, the spatial analysis of potential hazards in Silvana district in Urmia County has been studied. This study area due to specific geographic conditions such as position, complexity of topographic and ecological structures, in general, the existence of environmental factors for hazards has been selected as the study area. There have been a number of hazards in the past and assessing of this area is necessary, because of the lack of previous studies. For this purpose, by reviewing various reports and doing field observations, three hazards including Flood, Landslide, and Earthquake are identified as potential hazards of the study area.
For assessing hazards, 12 factors in 6 clusters such as Slope, Aspect (Topographic factors), Lithology, Soil type, Distance to Faults (Geological factors) Precipitation (Climatological factors), River Network Density, Groundwater Resources (Hydrological factors), Land use, Distance to Roads (Human factors), Observed Landslide Density and Seismicity (Historical factors) as the research factors has been selected. For weighting factors, Analytic Network Process (ANP) Method in Super Decisions 2.6.0 software environment has been used. The results of the analysis show that Slope (0.201), Precipitation (0.161), Lithology (0.112), Distance to Faults (0.106), Land use (0.096), Rivers (0.078), Seismicity (0.06), Soil Type (0.055), Landslide Density (0.047), Aspect (0.033), Groundwater (0.03) and Distance to Roads (0.016), Respectively have maximum to minimum relative weight. Then, weighted maps are standardized with using FUZZY functions. For this purpose, Fuzzy membership functions such as Linear, Large and Small has been selected based on each factor. For some factors such as Slope, Aspect, Lithology, Soil type, Rivers density, Land use, Seismicity and Landslide density, Fuzzy linear function has been used. For some others such as Groundwater and Precipitation, Fuzzy large function has been used and for distance to Faults and distance to Roads, Fuzzy small function has been used. Finally, weighted maps were overlay in ArcGIS 10.4.1 environment with Fuzzy Gamma 0.9 operator and potential hazards zoning maps is obtained.
Final results indicate that major parts in the Northwest, West and South of the study area located in high risk zones and 59 percent of the total area exposed to high risk. Based on hazard zoning maps, 44 percent of the area exposed to Flooding, 48 percent exposed to Landslide and 44 percent exposed to Earthquake. Also, 61 percent of the population or 37394 people exposed to one hazard, 7 percent or 3817 people exposed to two hazard and 8 percent or 4914 people exposed to three hazard. According to surveys, only 21 percent of the study area is considered as a low risk area but that does not mean that environmental hazards will never happen in these areas. In general, and based on results, it is concluded that Silvana district has a high potential for environmental hazards. Final results of the research show that potential hazards identifying and preparation of hazard zoning maps can be very useful in reducing damages and achieving sustainable regional development. Therefore, considering the ability of hazard zoning maps to identify areas exposed to risk and assess the type of potential hazards, These analyzes should be considered as one of the most appropriate and useful tools in different stages of crisis management that can be the solution to many problems in preventing and responding to natural disasters and therefore, it is recommended that they be used in the crisis management process.
Keywords: Spatial Analysis, Environmental Hazards, Silvana, ANP Method, Risk
 

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The Spatio-Temporal Variations of Aerosol Concentration Using Remote Sensing in Sistan and Baluchestan Province (2018 - 2000)
 
 
 
Abstract
Atmospheric particles play an important role in balancing the energy budget of the Earth's surface. The Sistan and Baluchestan province because of the specific geographical conditions during the year is witnessing the spread of dust particles caused by dust storms. This paper investigates the spatial changes of this phenomenon in the region to identify the association of dust accumulation and the reasons for these concentrations. In this study, the AOD Index data of the Aqua and Terra Modis Satellite Sensor (MODAL2_M_AER_OD) with 10 × 10 km spatial resolution were used. Then, by using statistical methods, a spatial analysis was done and the temporal and spatial changes trends at 95% and 99% significance level were performed using the nonparametric Mann-Kendall method. The results showed that the maximum concentration of aerosol in areas such as Zabol, Zahak, Hirmand, Hamoun, Iranshahr, Bampour, Jazmurian basin, Chabahar, and Konarak. On average, the highest variations in aerosol concentration were in the southern regions of the province include Dashtiari, Polan, and Chabahar, and the least in the northern part of Polan, Chabahar, Konark, and Bampour areas. The trend of changes was evaluated at two significant levels of 95 and 99%. The results of this section showed that the AOD had a positive and increasing trend in June, July, and August in the areas of Dalgan, Iranshahr, Bampour, Bazman, Mirjaveh, Nokabad, Zahedan, Nosratabad, Zaboli, Qasrqand, Irandegan, and Sib-va-Soran Plain and areas such as Korin, Zabol, Zahak, Sirkan (Bamposht), Hamoun have a negative and decreasing trend. The average changes in aerosol concentration in June, July, and August show a significant increase in the aerosol concentration from 2015 to 2018 up to 0.8.
 
Keywords: Environmental Changes, Dust, Environmental Hazards, Climate.

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One of the causes of environmental hazards is the change in the pattern of surface water flow in floodplains following the construction of flood Spreading networks. The purpose of this study is to prepare a zoning map of vulnerable areas of the flood Spreading station of Musian plain  in Ilam province after the implementation of the aquifer project in this plain. To prepare this map, five factors influencing the change in flow pattern including elevation, slope, flow direction, geological formations, and landuse change were examined. Then, in the GIS environment, each class of the mentioned factors was given a score of zero to 10 based on the range and the corresponding weight layers were created. Then, by combining the created weight layers, the vulnerability zoning map of the area was created based on 5 classes: very low, low, medium, high and very high. The results showed that the most important threat and danger factor is the concentration of waterways behind erosion-sensitive embankments. Also, the study area in terms of vulnerability includes three classes with medium risk, high and very high and covers 16, 62 and 22% of the area, respectively. Flood and upland Spreading areas, risk areas and lowland lands are the most vulnerable parts of the basin in terms of floods and sedimentary deposits.

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Risk modeling of plant species diversity and extinction in Sorkheh_hesar National Park
 
Zahra Mosaffaei¹, Ali Jahani^2*, ³MohammadAli ZareChahouki, ⁴Hamid GoshtasbMeygoni, ⁵Vahid Etemad
 
¹ Masters of Natural Resources Engineering, Environmental Sciences, College of Environment, Karaj
^*2Associate Professor, Department of Natural Environment and Biodiversity, College of Environment, Karaj.
³ Professor, Department of Restoration of arid and mountainous regions, University of Tehran, Karaj
⁴ Associate Professor, Department of Natural Environment and Biodiversity, College of Environment, Karaj
⁵ Associate Professor, Department of Forestry and Forest Economics, University of Tehran, Karaj
 
 
Abstract
Full identification of hazards and prioritizing them for non-harm to nature is one of the first steps in natural resource management. Therefore, introducing a comprehensive system of evaluation, understanding, and evaluation is essential for controlling hazards. This study aimed to model and predict environmental hazards following increased degradation in natural environments by ANN. Thus, 600 soil and vegetation samples were collected from inhomogeneous ecological units. Soil samples were prepared by strip transect method according to soil depth in four profiles (5, 10, 15, 20 cm). Vegetation samples were also collected using a minimum level method using 2 2 square plots according to the type, density, and distribution of vegetation. Sampling was done in two safe zones and other uses were modeled using ANN in MATLAB environment. The optimal model of multilayer perceptron with two hidden layers, sigmoid tangent function and 19 neurons per layer and coefficient of determination of 0.90. The results of sensitivity analysis showed that soil moisture content would be effective in decreasing biodiversity and flood risk as well as increasing the risk of extinction of endemic species in the region, and then the apparent and true gravity and soil porosity and distance from the road play a key role in the degradation of cover. Vegetation has increased flooding and extinction risk. Therefore, it is recommended that measures related to soil and vegetation restoration in this park be taken to reduce future damages as soon as possible.
 
Keywords: Modeling, Artificial Neural Network, Environmental Hazards, National Park, Vegetation
 

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Abastract
Introduction
Road accidents is the outcome of driver behavior, road condition, vehicle status, and environmental factors. Therefore, identification and assessment of effective parameters on road accidents can be considered as an appropriate way to reduce the accident events, driving violations and increase the road safety. Determining the effects of meteorological factors on the road accident events has gained more attention in recent years.
  The The main objective of this study was to investigate the relationship between the number of road accidents and the meteorological variables in the intercity road of Grmi-Ardabil in the Barzand route.
Methodology:
In this regard, the effects of climatic factors (including rainfall amount, the minimum absolute temperature, and the number of frost days) on the frequency of perilous events were analyzed. The data of accident events (in recent 4 years) were obtained from the trooper department of Ardabil Province along with the meteorological parameters of Germi station through a 11-year period. The statistical tests were performed using R programming software through statistical analysis.
Findings and Discussion:
The results showed that the majority of accidents were occurred in winter season which is in consistent with the frequency of frost days and also corresponded to the absolute minimum temperature. According to the results, the highest significant positive correlation at (R²= 0.43) was observed between the number of injured people and frost days. In addition, the relationship between the absolute minimum temperature and the number of were identified as significant negative correlation.
Conclusion:
As a concluding remark, the poor road conditions caused by climate element can be considered increasing the frequency of accident events. Accordingly, the proper strategies related to behavior change could be
considered in setting the rules and regulations to reduce the accidents and the number of injuries.

Keywords: Climatic hazards, Correlation analysis, Frost days, Minimum absolute temperature, Germi-Ardabil road


 

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Considering the increase in housing construction in developing societies such as Iran, it is necessary to address the issue of reducing construction accidents, especially in metropolises, and related safety measures with the help of emerging technologies. Therefore, the main goal of the current research is to investigate the use of Internet of Things to monitor and control high-risk points in order to reduce accidents and improve safety in the spaces of construction site in Tehran.
In this applied research, first, a library study was conducted regarding the concept and application of Internet of Things in the safety field of the construction industry. Then, high risk points and activities were identified. After that, in the field study phase, this list was corrected and completed by 52 competent building safety consultants. After that, ten semi-structured interviews were conducted with safety experts and knowledgebale in the field of IoT. Therefore, effective solutions based on Internet of Things were extracted to control and monitor high risk points. Also, in this regard, the current situation and required platforms were explained from the aspects of technology, organization, cost and outsourcing.
In fact, the main findings of this research, in the form of a conceptual model, show that paying attention to the stages of choosing the incident, choosing the desired point and activity, determining the appropriate solution for the determined situation (monitoring the amount of movement and health of the structure, monitoring the proximity of flammable materials with other materials, monitoring the proximity of people and machines and preventing the continuation of movement and determining the limits around the openings) and checking the required platforms (infrastructure, support, accreditation, culture, budget, employers and law), respectively, in order to design and implement IoT-based safety systems in the spaces of construction sites is vital.

 

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Spatial analysis models provide a single model and solution to solve various problems in the field of study, one of the applications of these models is in measuring urban risks. In recent years, with the occurrence of various crises in urban communities, the urban management system and development plans are seeking access to models of prevention and dealing with these crises. The purpose of this research is to review the literature about the use of spatial analysis models in measuring urban risks in a meta-analytical way, so this research is conducted by reviewing and summarizing foreign articles (research statistical community) in relation to this issue in order to identify, analyze and Analyzing and summarizing the solutions of the investigated backgrounds.
The statistical population is discussed with four standard criteria of spatial analysis, including description and identification of hazard dispersion, hazard dispersion argument, interpolation, and spatial planning. The statistical population is research, studies, and articles indexed in Sciencdirect, Willey, Web of Science databases in the period 2021-2000. Out of 99 articles, 78 articles have been selected and analyzed by screening method according to research objectives and indicators. The analysis was performed in two ways: descriptive statistics in SPSS software and inferential statistics in CMA2 comprehensive meta-analysis software.
The results indicate that in the component of hazard dispersion descriptions, most of the researches in their used models have not been able to provide a tangible and appropriate general description, but in the three components of hazard dispersion, interpolation, and spatial planning of urban hazards based on score The average effect size, the applied models used in the research, have been able to provide a proper justification and tangible results with the applied model of spatial analysis in their studies.
 

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Explaining the spatial patterns of drought intensities in Iran

Abstract
Recognition of spatial patterns of drought plays an important role in monitoring, predicting, confronting, reducing vulnerability, and increasing adaptation to this hazard. This study aims to identify the spatial distribution and analyze the spatial patterns of annual, seasonal, and monthly drought intensities in Iran. For this purpose, the European center Medium-Range Weather Forecast (ECMWF) data for the period 1979-2021 and the ZSI index were used to extract the drought intensities. To achieve the research goal and explain the spatial pattern of the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran’s Index, and hot spots were used. The results of the global Moran’s I showed that with increasing intensity, the spatial distribution of drought events has become clustered. The spatial distribution of the local Moran’s Index and hot spots also confirms this. Very clear contrast was observed in the local clusters of high (low) occurrence as well as hot (cold) spots of severe (Extreme) yearly droughts in the south, southeast, and east. In autumn, weak to Extreme droughts show a southeast-northwest pattern. But in spring and winter, the spatial pattern of drought is very strong as opposed to severe and moderate drought. Despite the relatively high variability of maximum positive spatial Autocorrelation of severe and Extreme monthly droughts, their spatial pattern is almost similar. The spatial clusters of severe and very severe droughts in the northwest, northeast, and especially on the Caspian coast, are a serious warning for the management of water resources, especially for precipitation-based activities, such as agriculture.
Introduction
Drought or lack of precipitation over some time is the most widespread natural hazard on the earth compared to its long-term average. This risk negatively affects various sectors such as hydropower generation, health, industry, tourism, agriculture, livestock, environment, and economy. To reduce these negative or destructive effects, it must be determined how often drought occurs during the period and in which areas it is most severe. Doing so requires determining the characteristics of the drought. These characteristics include area, intensity, duration, and frequency of drought. Discovering the geographical focus, recognizing the pattern governing the frequency of occurrence and temporal-spatial distribution as well as changes in the dynamics of this hazard facilitate an important role in drought monitoring, early warning, forecasting, and dealing with these potential hazards; this information can be used to create a drought plan by providing analysts and decision-makers with ideas about drought, helping to reduce the negative and vulnerable effects and ultimately make it easier to protect or replace for greater adaptation. Many researchers have been led by these approaches to the use of statistical analysis. Numerous studies have been conducted in the study of climatic phenomena such as drought with space statistics techniques in various regions, including China, India, South Korea, and even Iran. Part of the domestic research on spatial patterns of drought is without the use of spatial statistics and a limited number of others who have used these analyzes have only studied the overall intensity of drought and have not studied the spatial patterns of different drought intensities. The main purpose of this study is to identify the distribution and spatial patterns of drought intensities in Iran using spatial analysis functions of spatial statistics based on the frequency of drought intensities (Extreme, severe, moderate, and weak) with yearly, seasonal and monthly multi-scale approach. Therefore, this study will answer the questions: a) What is the spatial distribution of drought intensity data in Iran? And b) What is the variability of spatial patterns of Iranian droughts at different time scales?
Material &Method
ERA5 monthly precipitation data for a period of 43 years from 1979 to 2021 were used for this study. an array of dimensions of 78×59×504 of data were formed in MATLAB software in which 78×59 is the number of nodes with a spatial resolution of 0.25 degrees and 504 represents the month. After creating the database, the ZSI index was used to calculate the severity of drought in annual, seasonal, and monthly comparisons. Finally, to achieve the research goal and explain the spatial pattern governing the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran I and hot spots was used.
Discussion of Results
Due to its ecological conditions, geographical location, and location in an arid and semi-arid region of the world, Iran is among the most vulnerable countries due to natural hazards, including drought. It has experienced many severe droughts in the last century. The occurrence of drought and its effects is one of the major challenges of water resources management in this century. The results of the Global Moran’s Index for all three annual, seasonal, and monthly scales showed a highly clustered pattern of drought events in the country. Spatial clustering of the occurrence of severe and Extreme yearly droughts in the eastern, southeastern, and southern regions is also an interesting result. These conditions are due to low precipitation and high spatial variation coefficient in these areas. This contrast of spatial clusters of drought intensities indicates the relationship between drought and temporal-spatial anomalies of precipitation so that with increasing precipitation, spatial variability of precipitation decreases, and consequently spatial homogeneity of precipitation increases. severe and moderate-intensity spots in the south-southeast in autumn and spring can be affected by fluctuations in the beginning and end of the monsoon season in South Asia due to the high variability of atmospheric circulation at the beginning and end of precipitation in these areas. Some studies have also shown the relationship between precipitation in these areas and the monsoon behavior of South Asia. Extreme drought events in winter and spring have had a positive spatial correlation pattern in the southwest, west, and northwest. However, precipitation at this time of year is concentrated in these areas. Warm clusters or concentrations of very severe drought events in the northern strip of the country, especially in the Caspian region, can be due to the high variability of precipitation at the beginning of the annual precipitation season (late summer and early autumn).  Observations of these conditions in the northern strip indicate that an event with a high frequency of severe droughts, even in rainy areas, should not be unexpected. Spatial clusters of Extreme, severe, moderate, and weak drought every month using both local Moran and hot spots statistics show the fact that in Iran, the most severe droughts have occurred in the western, northwestern, and coastal areas of the Caspian Sea. However, the absence of severe droughts or spatial clusters has been the occurrence of low drought in the southeast and to some extent in the south. On a yearly scale, the south, southeast, and east have played a significant role in the spatial cluster of severe and extreme droughts. So that these areas of the country have had positive spatial solidarity. However, in these areas, negative spatial correlation prevailed in the autumn for severe drought. This may indicate an anomaly and a tendency to concentrate more precipitation in Iran, as well as many changes in seasonal and local precipitation regimes. According to the research results, a high incidence of severe and extreme drought on all three scales (monthly, seasonal and annual) even in the wettest climate of the country (northern Iran, especially the southern shores of the Caspian Sea) shows that High-intensity droughts can occur in all parts of the country, regardless of the weather conditions.
Keywords: Natural hazards, spatial patterns, Moran statistics, spatial autocorrelation, hot spots


 

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Extended abstract
Landslide risk zoning is one of the basic measures to deal with and reduce the effects of landslides. Vernesara watershed is one of the areas where many landslides have been observed in different parts of it. In this research, in order to zone the risk of landslides using the entropy index, first the ranges of landslides were determined, then the effective factors in the occurrence of range movements were prepared in the ArcGIS software environment, and a landslide susceptibility map of the studied area was prepared. . The prioritization of effective factors using Shannon's entropy index showed that the slope layers, land use, surface curvature, topographic humidity index and topographic position index had the greatest effect on the occurrence of landslides in the region. Also, zoning landslide sensitivity with the mentioned model and evaluating its accuracy using the ROC curve shows the very good accuracy of the model (79.6 percent) with a standard deviation of 0.0228 for the studied area. The zoning map shows that the low-risk areas cover only 13% of the area and more than 56% of the area is in the area with high risk of landslides, which indicates the high potential of the area in the occurrence of landslides. . Construction at a distance from fault lines, waterways and the steep Asmari Formation and safety of communication routes are the most important measures to reduce the amount of damage caused by landslides in Vernesara watershed.
Key words: natural hazards, landslide, entropy, folded Zagros.
 

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In order to plan, manage and exploit water and land resources, awareness of the spatial variability of resources, as well as understanding the response behavior of the watershed in order to model physical processes, has an identical significant role. Due to its location in arid and semi-arid areas, special climatic and geomorphological conditions, Qom-Roud basin is prone to flash floods. Due to the lack of hydrometric and topographical data with high accuracy in the basin, the use of hydraulic models does not lead to accurate results of the hydraulic characteristics of floods. In such a situation, the methods based on the geomorphological features of the basin can be advantageous. In this article, Variable flood stage method (VFS) method is used, which combines the hydraulic characteristics of the river with the geomorphic characteristics of the basin in order to estimate the water depth in the river caused by floods with different return periods. The water depth was investigated for different return periods of two, five, ten, twenty-five, fifty and hundred years. In each period, the highest water depth was in the parts near the outlet and the lowest water depth was in the upstream parts of the river. The research illustrations there is a direct relationship between the depth of water and the area of the sub-basin. The results of this research can be used for basins without hydrometric and topographic statistics with high accuracy in order to estimate the peak speed and flood depth.