نشریه تحلیل فضایی مخاطرات محیطی
سال هشتم شماره 4 (زمستان 1400)

Clean air is a necessity for human well-being and health. Air pollution is a major threat to humans and other organisms and is considered as one of the environmental challenges. Today, with the increase in air pollution, the need to know more about the causes of its occurrence has been raised. The various consequences of air pollution have made air quality monitoring and control inevitable in all societies at the forefront of environmental issues. In recent years, air pollutants have caused serious risks to human health and the environment. One of these pollutants Tropospheric ozone is the cause of health and environmental problems, especially respiratory problems and lung dysfunction and asthma attacks. Other effects of tropospheric ozone can be reduced lung capacity, cough, chest pain, sore throat, condition Nausea, damage to plants (growth disorders and the effect on germination) and reduced tire life, hence, it is necessary to know and study the tropospheric ozone in large and industrial cities. Tropospheric ozone is a pollutant because it plays an effective role in converting primary pollutants into secondary pollutants. Therefore, the aim of this study was to investigate the trend of changes in tropospheric ozone concentration with meteorological parameters, ozone precursors (nitrogen dioxide and nitrogen oxides). In this study, data from Kermanshah synoptic station and air quality station of Kermanshah General Department of Environmental Protection (Ziba Park station) in a long-term period of 10 years (2007-2016) have been used. Also, in this study using sensor images The OMI satellite Aura was surveyed in February and July 2016. Tropospheric ozone is known as a pollutant in Kermanshah. Therefore, no systematic studies have been conducted on the recognition of tropospheric ozone and the relationship between tropospheric ozone and meteorological parameters in Kermanshah over a long period of time. Tropospheric ozone and its relationship with changes in nitrogen oxides, nitrogen dioxide and synoptic parameters in Kermanshah were studied and the correlation between tropospheric ozone concentration and meteorological parameters was studied by Pearson test and the relationship between them was studied by linear regression. Based on the results. The maximum concentration of ozone occurs in the afternoon between 14:00 and 17:00 and the maximum amounts of nitrogen oxides occur at night and in the early morning of the year. Also, the study of seasonal changes in ozone concentration showed that in warm seasons due to the conditions of tropospheric ozone formation, including the intensity of sunlight, temperature and time of radiation and the presence of pollutants including nitrogen oxides, the concentration of tropospheric ozone was much higher. Ozone concentrations are highest in June, July, August, and spring and summer. The results also showed that there is a direct relationship between solar radiation and ozone concentration. Simultaneously with increasing solar radiation, it increases the air temperature, which increases the photochemical activity and thus increases the ozone concentration. This can be seen in the warm months of the year (June, July and August). Wind speed is also directly related to the concentration of tropospheric ozone. As the wind speed increases, the reactants mix faster and the tropospheric ozone concentration increases. However, precipitation is inversely related to the concentration of tropospheric ozone, which decreases with the occurrence of precipitation in the months associated with the onset of precipitation, and in the dry months of the year, the concentration is increasing. Therefore, meteorological factors and parameters play an important role in tropospheric ozone changes. Which can be seen by linear regression and Pearson test. The results of the study of nitrogen dioxide and nitrogen oxides showed that the highest concentration of nitrogen dioxide and nitrogen oxides during the day is the opposite of the concentration of tropospheric ozone and the lowest concentration of ozone occurs in summer due to increased solar radiation, increased oxidation of di Nitric oxide and nitrogen oxides, and as a result increase the concentration of tropospheric ozone, in autumn and winter, this amount has an increasing trend. Therefore, the trend of changes in tropospheric ozone concentration is the opposite of the concentration of nitrogen dioxide and nitrogen oxides, which can be seen in the daily, monthly and seasonal sections, which linear regression and Pearson test show this important and OMI sensor images confirm this fact. In conclusion of this study, all parameters related to the concentration of pollutants along with meteorological parameters have been effective factors in the concentration of tropospheric ozone.

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.

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.

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.

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.

River bank erosion is a complex natural process and plays an important role in the dynamic equilibrium of the river. The amount of river bank erosion affects the river plan, cross section and dimensions of the river and is the main factor controlling channel migration and the evolution of the river planform. This research was conducted with two main objectives, which are: 1. River bank erosion susceptibility analysis in incised rivers in mountainous areas, 2. Comparison of river bank erodibility with two methods original BEHI and modified BEHI.

In this study, Bank Erosion Hazard Index (BEHI) and the modified BEHI method along a part of Sajadrood Stream in Mazandaran province have been investigated. The original BEHI (Rosgen, 1996, 2001) evaluates the river bank erosion field measurements. In this method, several parameters are measured, including bank height, Bankfull height, bank angle, root depth, root density, surface protection, bank material structure and stratification. From this parameters, the bank angle and height, root depth can be measured, but indicators such as plant root density and surface protection are visually estimated as a percentage. The score of each index varies from 1 to 10. The total scores of all indicators are classified into 6 groups: very low, low, medium, high, very high and extreme. Newton and Drenten (2015) Based on the modified BEHI proposed a protocol for estimating the river bank erosion. In this protocol, the lengths of similar riverbanks are first defined as a uniform section of bank. These uniform sections can be identified due to differences in bank slope, differences in bank material and a break in vegetation. The characteristics of uniform sections are then evaluated in a pre-screening questionnaire consisting of six questions. If the answer to two or more questions is "yes", there is a high probability of erosion and the BEHI evaluation will be performed. Otherwise, the measurement will not be taken because the erosion is low or very low.

The study area was divided into four reaches and 36 sites were surveyed. These river reaches have a deep bed (incised), high slope, low sinuosity, low width to depth ratio and predominant cobble sediments in the bed. They are in type A3 according to the Rosgen River classification. The height of the banks of the stream is high and its average is 2.6 meters with a minimum and a maximum of 0.4 to 9.7 meters. The average height of bankfull was 0.44 meters and varied from 0.15 to 0.85 meters. Hence, the ratio of bank height to bankfull height has been high. The root depth of plants was low and their average was 0.34 meters. Root density of plants was also low and averaged 5.7% The stream bank angle is measured from 31 to 90 degrees and an average of 51degree. The percentage of surface protection varied between 25 and 65% and averaged 42%. From a total of 36 sites, 8% are in the medium group, 39% in the high erosion category, 45% in the very high erosion group and 8% in the extreme erosion category.
Among the various variables, the β coefficients of the surface protection index and the ratio of bank height to bankfull height were -0.62 and 0.51, respectively. To evaluate the modified BEHI method, all reaches were first examined according to the pre-screening table and more than two "yes" answers were confirmed for each reach. In the modified BEHI method, 26 out of 36 sites were in the erosion group. But in the original BEHI method, 16 sites are in a very high class. The total score of the studied sites was evaluated by two BEHI methods with Pearson correlation coefficients, which obtained a coefficient of 0.21 and shows a relatively low correlation.

Sajadrood stream has high and steep banks due to the incision created in the channel bed. The deposition of large boulders at the toe of the streambank has caused its protection and the flood currents of bankfull are not able to carry this piece of rock. Under these conditions, calculating the ratio of bank height to bankfull height cannot indicate the erodibility of the streambank in the bankfull stage. Nevertheless, the erodible potential of the bank for larger flood currents is confirmed. Comparison of the original BEHI with the modified BEHI showed that the modified method has an overestimate than the original BEHI.

The advent of Web 2.0 enables the users to interact and prepare free unlimited real time data. This advantage leads us to exploit Volunteer Geographic Information (VGI) for real time crisis management. Traditional estimation methods for earthquake damages are expensive and time consuming. In contrast, volunteer and web-based service are near real time with almost no cost services. the lack of accessible real time data collection services causes delayed-emergency responses for disasters like an earthquake. This drawback is critical when we encounter a problem like buried people with valuable seconds for emergency rescue operation. The current research aims to design and implement a web-based volunteer data collection service for rapid estimation of earthquake damages and number of buried people.

To investigate the capacity of VGI in rapid estimation of earthquake, a technical frame work based on the web technologies has been programmed and implemented. The designed service is comprised of server and client sides.The client side is a two-side browser-based service includes volunteers (users) and managers pages. On the user page, volunteers have a web page to enter and fill in the blank forms and taking a photograph of the target building and compare it with pictures. They watch the sample pictures in different level of damages and compare their building with the samples and give a grade of the most similar picture with their building. This grading process leads the server to analysis and classify the incoming data and create the heatmaps for managers. On the managers page two online discrete heatmaps for the both earthquake damages and buried people are displayed. In fact, the heatmaps present the online and real time quantitative situation of the building damages and buried persons as hot spots. These hotspots have the first priority for giving emergency services. The manager page also exploits query tools to request different level of details and classes from the server side. The server side is responsible for receiving, saving, spatial analysis and transmission of the requested result to the client side. This task is carried out by the exchange side. As the citizens are entered to the browser-based service and fill in the blank forms for building damages based on the mentioned guideline and report the buried people, These forms are transmitted to the server side and a geo-server performs spatial analysis including Heatmap, distance and clustering analysis. Then, a real time damage and buried people map are prepared and delivered to the client side. The server updates the created maps whenever a new data is submitted. By this, a real time damage and buried people maps are accessible for official managers to conduct a goal-oriented emergency operation and a preliminary earth quake damages on city building blocks. After the technical frame work has been designed, it was tested in Oshanvieh city by 132 volunteers on the scene for an earthquake.

To investigate the capability of volunteer geographic information for earth quake afterwards, the designed service mentioned in the methodology was utilized on Oshnavieh city. It was assumed that an earthquake has occurred. 132 volunteers participated for the data collection process. According to the crisis management organization experts, 102 reports of the total 132 reports are correct that shows the accuracy of 76.52 percent. Besides the building damage level based on the defined guideline, the citizens also select their vital needs after the earthquake. the most requested vital needs are warm stuffs, medicine, water and foods respectively. Unfortunately, the participation rate is ranged from some seconds after the earthquake to three days. This means that some citizens have filled and transmitted their data three days after the earthquake. In the following, a comparison between the designed service and traditional earthquake damage estimation methods (in situ) was carried out. The result shows that field-based methods for a city like Oshnavieh need about 20 days. However, the designed volunteer-based service what is programmed and implemented in the current research does this job by 3 days.

As the results show, the proposed service designed in this research implements the damage estimation process 6.5 times faster than the governmental procedures. This proves the efficiency of the research achievements. Besides the velocity, traditional damage estimation methods are expensive compare to volunteer-based data collection and processing which are almost free, scalable and pervasive.

Climate change is the greatest price society is paying for decades of environmental neglect. The impact of global warming is most visible in the rising threat of climate-related natural disasters. Globally, meteorological disasters more than doubled, from an average of forty-five events a year to almost 120 events a year (Vinod, 2017). Climate change refers to changes in the distributional properties of climate characteristics like temperature and precipitation that persist across decades (Field et al., 2014). Because precipitation is related to temperature, scientists often focus on changes in global temperature as an indicator of climate change. Valipour et al. (2021) reported the mean of monthly the global mean surface temperature (GMST) anomalies in 2000–2019 is 0.54 C higher than that in 1961–1990. Many studies have been done on climate change in Iran. These studies have mostly studied the mean and extreme temperature trends (Alijani et al., 2011; Masoudian and Darand, 2012). In general, the results of previous studies showed that the statistics of mean, maximum and minimum air temperature in most parts of the Iranian plateau have increased in recent decades. Also, the increase of minimum temperature is greater than maximum temperature. A review of the research background shows that we need to understand more about regional climate change in Iran. Therefore, present study performs the climate change of 14 extreme temperature indices using multivariate statistical methods at the regional scale.

Historical climate observations including daily maximum and minimum temperature were obtained from the Iranian Meteorology Organization for the period 1968 to 2017 at 39 stations. In this paper, 14 extreme temperature indices defined by ETCCDI were analyzed. The indices are as follows: (1) Annual maxima of daily maximum temperature (TXx); (2) Annual maxima of daily minimum temperature (TNx); (3) Annual minima of daily maximum temperature (TXn); (4) Annual minima of daily minimum temperature (TNn); (5) Cold nights (TN10p); (6) Cold days (TX10p); (7) Warm night (TN90p); (8) Warm day (TX90p); (9) Frost days (FD); (10) Icing days (ID); (11) Summer day (SU); (12) Tropical nights (TR); (13) The warm spell duration index (WSDI) and (14) the cold spell duration index (CSDI). The extreme temperature indices were extracted using R software environment, RclimDex extension. The Mann–Kendall Test and Sen’s Slope Method was employed to assess the trends in 14 extreme temperature indices. To identify homogeneous groups of stations with similar annual thermal regimes, Principal Component analysis (PCA) and Clustering (CL) was applied. Pearson correlation coefficient was used to investigate the relationship between height and trend slope.

All the extreme temperature intensity indices (TXx, TNx, TXn, and TNn) showed increasing trends during 1968 to 2017. The increasing trends of TXx, TNx, TXn, and TNn were 0.2, 0.3, 0.44, and 0.5 ° C per decade, respectively. These results indicated that the extreme warm events increased and the extreme cold events decreased. The average of the extreme temperature frequency indices over Iran showed that the frequency of warm night (TN90p) and warm day (TX90p) significantly increased with a rate of 6.9 and 4.2 day per decade, respectively. Also, the frequency of cold night (TN10p) and cold day (TX10p) significantly fell with a decrease rate of 3.8 and 3.8 day per decade, respectively. The frequency of warm nights (TN90p) was higher than that of warm days (TX90p). The result indicated that the trend of nighttime extremes were stronger than those for daytime extremes. The average of frost days (FD) and icing days (ID) indices over Iran showed decreasing trends during 1968 to 2017 with rates of 3 and 1.1 d per decade, respectively. While, the averaged of summer days (SU) and tropical days (TR) indices over Iran showed increasing trends with rates of 4.4 and 6.4 day per decade, respectively. The warm spell duration index (WSDI) indices showed a clear increase, with a rate of 2.1 per decade. In contrast the cold spell duration index (CSDI) showed a significant decrease, with a rate of 1.7 per decade. In general, the cold indices displayed decreasing trends, whereas the warm indices displayed increasing trends over most of Iran. Pearson correlation coefficient between height and Sen’s Slope was estimated to be equal to -0.62 (p < 0.01). In general, the results of this study showed that there is a negative correlation between the elevation factor and the Sen’s Slope of warm extreme indices. That is, as the altitude decreases, the Sen’s Slope increases. Therefore, the stations located in low altitude have experienced stronger increasing trends than in high altitude. The area of ​​Iran was classified into four clusters using PCA and CL methods. Cluster 1 has experienced the strongest increasing trends. The average height of cluster 1 is 535 meters. Approximately 38% of the studied stations were located in cluster 1. Cluster 2 showed a moderate heating trends. 33% of the stations were located in cluster 2. Most of the stations of cluster 2 are located in the northwest and west of Iran. Cluster 3 showed a weak increasing trends compared to clusters 1 and 2. The stations of cluster 3 did not show a special geographical concentration and were scattered in all parts of Iran. 18% of the studied stations are located in cluster 3. The stations of Cluster 4, have experienced weak decreasing trends, which was different from the other three clusters

In this study we analyzed the climate change of extreme temperature indices in Iran. The result showed that the frequency of warm nights, warm days, summer days and tropical days increased. Also, the frequency of cold nights, cold days, Frost days and icing days decreased. The warm spell duration index showed a clear increase. In contrast the cold spell duration index showed a significant decrease. In general, the extreme warm events increased and the extreme cold events decreased over most of Iran. There is a negative correlation between the elevation factor and the Sen’s Slope of extreme warm indices (R = -0.62). Therefore, the stations located in low altitude have experienced stronger increasing trends than in high altitude. The area of ​​Iran was classified into four clusters using PCA and CL methods. Cluster 1 has experienced the strongest increasing trends. The average height of cluster 1 is 535 meters. Therefore, the most heating have occurred in Low-lying areas of Iran. Cluster 2 and Cluster 3 showed a moderate and weak heating trends, respectively. The stations of Cluster 4, have not experienced clear trends.

Drought is one of the environmental disasters that is very frequent in arid and semi-arid regions of the country. Rainfall defects have different effects on groundwater, soil moisture, and river flow. Meteorological drought indices are calculated directly from meteorological data such as rainfall and will not be useful in monitoring drought if the data are missing. Therefore remote sensing technique can be a useful tool in drought measurement. Drought is a recognized environmental disaster and has social, economic, and environmental impacts. Shortage of rainfall in a region for long periods of time is known as drought. Drought and rainfall are affecting water and agricultural resources in each region.

The present study is a descriptive-analytic one with emphasis on quantitative methods due to the nature of the problem and the subject under study. In this study, the Tera Sensor Modis satellite images from 2000 and 2017 were used to verify the existence of wet and drought phenomena. In the next step, by examining the rain gauge and synoptic data of the existing stations and using a standardized precipitation index model of three months (May, June and April), the sample was selected. Next, we compared the temperature status indices (TCIs) and vegetation health indices (VHIs) in these three months to determine the differences in these indices over the three months. Modi satellite Tera satellite was used to find out the vegetation status in the study area. Subsequently, using the condition set for the NDVI layer, the vegetation-free areas were separated from the vegetated areas. Experimental method was used to determine the threshold value of this index. For this purpose, different thresholds were tested, with the optimum value of 1 being positive. NDVI is less than 1 plant-free positive and more than vegetation-free. MODIS spectral sensing images for ground surface temperature variables, with a spatial resolution of 1 km, including bands 31 (bandwidth 1080/1180 central bandwidth / 11.017 spatial resolution 1000 m) and 32 bands- 770/11 Central Wavelength Band 032/12 Spatial Resolution Power (1000 m) Selected for months that are almost cloudless. All images have been downloaded from the SearchEarthData site and have been edited. The total rainfall of June, April, and May for the 20-year period was provided by the Meteorological Organization of Iran. ARC GIS software and geostatistical methods were used to process the Excel data. Also, to estimate the correlation between the data Pearson's correlation coefficient was used.

The standardized precipitation index is a powerful tool in analyzing rainfall data. The purpose of this study was to compare the relationship between remote sensing indices and meteorological drought indices and determine the efficiency of remote sensing indices in drought monitoring. Correlation between variables with SPI index was evaluated and calculated. The results of the indicators are different, so a criterion should be used to evaluate the performance of these indicators. SPI index on quarterly time scale (correlated with vegetation) as the preferred criterion Selected. According to the results of correlations, the TCI index with the SPI index had a strong correlation with other indices. In the short run, this index has the highest correlation with thermal indices at 1% level. The correlation between meteorological drought index and plant water content and thermal indices increases with increasing time interval. Positive correlation between vegetation indices and plant water content with meteorological drought indices indicates that trend of changes is in line. Therefore, the TCI index makes drought more accurate and is a better method for estimating drought.

The results showed that among the surveyed fishes, the highest drought trend was observed in the eastern part of these provinces and covered more than 50% of the area. The trend of changes in this slope was statistically significant. According to the results of correlations, the TCI index with the SPI index had a strong correlation with other indices. It can also be concluded that the Modis images and the processed indices along with the climate indices have the potential for drought monitoring. Using maps derived from drought indices can help improve drought management programs and play a significant role in mitigating drought effects.

Problem StatementCarbon management and its production resources are important not only for the preservation of non-renewable resources but also for the prevention of global warming and its adverse consequences. Direct consumption of fuel and energy by households plays a major role in CO2 production and it’s spatial distribution. Therefore, in order to plan and manage carbon emissions, it is very important to identify the factors influencing household energy consumption. This paper aimed to investigate the relationship between household characteristics such as age, income, family size, household head age, house area, etc. and energy consumption which ordinally results in more emissions. The study area is Ardabil city. It has an area of 6289 ha and a population of about 530000 people.

Consumption of natural gas, electricity and car fuel has been the criteria for determining the amount of household energy consumption. The data of the first two cases obtained from the bills of household’s consumption and the data of car fuel consumption and the other other required data, were collected through a survey as well. Based on the Cochran's formula, statistical samples including 383 households were selected as a sample of the households residing in Ardabil. A questionnaire was also used to collect the data. Data on energy consumption variables were first converted to Mj and then converted to CO2 emissions.  The data was then entered into Arc GIS to draw spatial distribution maps using Kriging interpolation Tool. Finally, using TerrSet Geospatial Monitoring and Modeling System software, the spatial relationship maps were produced and the adjusted R values were calculated.

Findings demonstrate that in Ardabil, household fuel consumption cause to an emission of more than  226,515 grams of CO2 per household every month which is three times more than the mean value for all the Iranian households. In the study area, the average amount of energy consumption and carbon emission of households residing in municipality districts 2 and 3 are higher than same figure for all the households residing in the city. In contrast, in the municipality districts of 1 and 5, energy consumption and CO2 emission are lower than the mean value for the whole Ardabil households. In district 4, the figure is very close to the mean value for all the households. More than 80 percent of household CO2 emission emitted from fuel consumption in homes and this ratio is almost the same throughout the city and in all municipality districts. After that, the ratio of transportation CO2 emission is about 15%, and electricity consumption has a ratio of less than 5% as well. In four lots located in the southwest, north, northeast and the center of the city, every year, households emit less than 172640 g/m of CO2. In contrast, in 4.8% of the city surface area, the lots located in southwestern and southeastern, households’ emission of CO2 is the most (more than 308923 g/m). The adjusted R, which represents the spatial relationship between the variables with CO2 emission, for all the 11 variables, were 0.67, 0.66, 0.72, 0.80, 0.87 and 0.88 for the city, district 1, district 2, district 3, district 4 and district 5 respectively and these values indicate that there is a high correlation between these variables. The highest adjusted R values (0.8 and more) belong to the strip-shaped lots locate in the central and eastern fringes of the city and they cover almost half of the surface area of district 2 and a small part of district 1. Areas where R value is less than 0.2 cover almost the whole surface of district 5 in the northeast of the city. Also, variables of “number of people who have a driving license in any household”, “household head age”, “household size and “house surface area”, represent a high correlation between these variables and CO2 emissions. Also, the correlation between the variables level of “education of household head”, “household head income” and “having electrical appliances” indicate that there is the lowest correlation between the variables and with CO2 emissions.

Geographical situation of Iran is a place for interacting many physical and human processes which lead to specific precipitation climatology in the country. The month to month variation of precipitation is one of  the features which the precipitation climatology may reflect due to tempo - spatial characteristics. In fact, monthly distribution of precipitation is one of precipitation normal features building up the climate structure. In order to recognize this fundamental characteristic three following questions have been raised:1) Have the month to month distribution of precipitation changed over recent four decades? 2) How is the pattern of relationship of month to month distribution of precipitation and spatio - topographical variables? 3) Is it possible to find a spatial pattern for decadal changes of precipitation of month to month distribution?

In order to find a responses for the abovementioned questions the distribution of month to month precipitation and its decadal changes was considered by adopting coefficients of variations (CV) for 46 years (1970-2016)  and using the third version of Asfazari dataset. The relationship of precipitation data and spatio-topographical variables calculated based on regression techniques. Moreover, the spatial pattern considered by using cluster analysis.  The CV calculated as follow: here ،،  are ith raw's and jth column's CV, standard deviation, and monthly mean, respectively. CV and its relationships with spatio-topographical variables were calculated in two temporal scale, for whole the under investigation period (1970-2016) and in decadal period for four decades (1977-1986, 1987-1996, 1997-2006, 2007-2016).

The results of current study proved that the month to month different in precipitation amounts have had spatial variations, whilst the temporal trends is not statistically significant. In addition, the minimum, maximum, and consequently, the range of values also the averages have not experienced significantly changes. However, the region experiencing the same values of precipitation illustrated oscillatory behavior. Accordingly, the decadal variations have happened in different areas. Although the there have been statistically significant relationships between monthly CV and spatio - topographical factors, the correlations were low. Based on cluster analysis, we found 5 regions according to CV and its anomalies in compares with normal CV for all under investigation period. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.

Precipitation is known a chiastic and complicated climate element. One of chiastic behaviors which precipitation shows in its different time - scale behavior is its month to month distribution among a given year. In current research the decadal variation of  above-mentioned behavior among recent four decades and the variation of its relationships and the spatio - topographical features , as parts of climate structure of the country, have investigated in details.  Our finding illustrated that the month to month different in precipitation amounts have had tempo - spatial variations, whilst the temporal long - term trends is not statistically significant. Moreover, the values of minimum, maximum, and consequently, the range of month to month CV also the decadal averages have not experienced significantly changes over four under study decades. However, the region experiencing the same values of precipitation depicted oscillatory behavior. consequently, the decadal variations have happened in different areas. Although there have been statistically significant relationships between monthly CV and spatio - topographical variables, the correlations were not considerably high. Based on cluster analysis technique, we found 5 regions according to CV and its anomalies in compares to normal CV for all under study decades. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns. 

Models, satellites and terrestrial datasets have been used to detect and characterize aerosol. Nontheless, micoscale classification using remote sensing parameters considers as a deficiency. Thus, regionalizion and modeling aerosol without regard to political boundaries or a specific stations over Iran  demonstrates the spatial distribution of simple AOD structures.

 Present study attempted to simulate and detect homogeneous areaes of aerosol in Iran using AOD (areosol optical depth) datast at 550 nm across Iran. Among the eigen techniques, principal component analysis (PCA) is the most applicable and controversial classification applied as multivariate analysis approach. In the line of the target, PCA, S-Mode separate the AOD subgroups with similar correlations. In the mode, m time series apply to each n station or grid points as a variable in the analysis, which is the territory of the region or geographical area. Mathematically, if the input data column in the Z matrix is applied as mathematical variables and the Z matrix has n points in the time series and m is the time step, then in the Zs decomposition has 3654×9985. In addition, the scree test and North's rule were used to cut-off the principal components and to select the number of appropriate special vectors to be kept.

For the study purpose, 85 percentaile of loadings were used to determine AOD areas over Iran. Using the method, the spatial patterns of Iran's aerosolshave been divided into six subregions, which are the major centers affected by the AOD. These major AOD hotspots affect by AOD extermes that are originated from aerosol surrounding sources. So that, the geographical location of sources areas have caused the northeastern atmosphere of Iran to be influenced by severe storms originating from the Karakum Desert. The same is correct concerning the East and Southeast regions. While, the intensification and transfer of aerosol from the Sistan plain to the south is increased AOD load over southeast Iran. Moreover, this study revealed a set points associated with distinguishing spatial differences between the west-northwest and southwest regions as well as central region that have not addressed in previous studies because of focus on ground-based observations. Also, the method illustrated that formation of the identified regions are a function of the volume, growth, and spread of aerosol particles resulting from the source regions in the Middle East. Finally, the classification techniques converting dynamic phenomenon such as aerosol into simpler structures presented a interpretable understanding of the geographical distribution of the phenomenon.

The present study identified the spatial patterns of AOD hotspots into six distinct regions including northeast, west-northwest, southeast, southwest, central and eastern Iran affected by the aerosol as well as major centers or high gradient areas. In addition, the present study not only supported by previous studies, but also it  make sense a regionalization that was neglected by former studies, whileseperated  the boundaries of the AOD areas without considering  provincial boundaries. Overall, the classification techniques, PCA, simplified a dynamic phenomenon such as aerosol into a simpler and illustrated geographical and interpretable understanding of the spatial distribution of the phenomenon.

Rural areas are more vulnerable to earthquake hazards than urban areas but the vulnerability of rural areas has always been neglected and few studies are worrying about it. Given the importance of villages and played the crucial role in socio-economic development and national security, providing adequate housing for villagers and addressing the problems in this area, in particular, providing them with security and relieving their vulnerability are of particular importance. One of the policies of Iran to reduce the risk of damage; improvement and rehabilitation of rural housing by the Housing Foundation of the Islamic Revolution Which has become one of the most important strategies in Iran due to the extent of natural disasters and their financial and financial losses and their expectations beyond ensuring security against accidents are also a continuation of rural life. neyriz Township is subjected to major and minor faults that the existence of these faults and the probability of earthquake causes vulnerability of the villages of the region. The housing estate of the Islamic Revolution of the Islamic Republic of Iran, from 2004 to 2013, has provided 5255 villagers of more than 20 households with facilities for the renovation and renovation of houses. The number of facilities was paid to 66 villages of more than 20 households in the city and supervision of the construction process was carried out. So what seems to be important is the activity that the Housing Foundation has had in its housing estate, its impact on the rural areas, and how much it has been able to achieve resistance and stability in rural housing; in addition to what degree, they have been able to influence their satisfaction. Therefore, the present study addresses the vulnerability of rural dwellings. In this regard, vulnerability is initially studied then the satisfaction of the villagers is examined finally, the share of each vulnerability level criterion is measured on the satisfaction of the villagers and appropriate solutions.

 The research methodology is based on its descriptive-analytical nature. Data gathering was conducted through surveying, library and field method. A small portion of the sample includes 230 households from 18 rural in the Neyriz Township. Reliability of the questionnaire was calculated using Cronbach Alpha (alpha = 0.79). In the qualitative section for the implementation of grounded theory, an interview was conducted with 40 villagers.

By studying the vulnerability of rural nursing homes in the Township of Neyriz, the villages of the studied villages are in an unfavorable position in terms of economic and social dimensions. Objective satisfaction indicators show that 51.8% of the villagers' homes were constructed responsive to concrete. 80.4% of the walls of the houses are made with bricks. The roofs of the houses are covered with 75% block and block. Of the studied rural households, 94.6% have personal housing and only 5.4% of the tenants. In the area of providing services in residential units, all the studied villages have water, electricity, telephone and 2.05 villagers are satisfied with the crop of agricultural products, parking lots, agricultural machinery and heating and cooling equipment for their housing.

 Findings showed that the vulnerability of rural housing is not only physical and environmental in nature, but also in social, economic and institutional-organizational dimensions. Meanwhile, vulnerability in physical and environmental dimensions in the study area is lower than other dimensions. Therefore, the existence of unstable housing in rural areas has led to a decline in their quality of life. This situation is strongly influenced by internal and external factors and forces. The lack of financial support, the traditional housing structure, poor design, poor monitoring and enforcement, social constraints, lack of building facilities, weaknesses in government support and regulatory policies, and government institutions are among the main problems of rural dwellings. According to interviews with villagers, the following solutions can be made to reduce rural housing problems: - The costs of facilities and infrastructure are not at the expense of villagers. Therefore, the creation of continuous financial resources for councils and departments can be open.  - Reducing the problems and obstacles facing applicants for loan use (through increasing credit, decreasing profits and raising the age), providing welfare services and reducing the total poverty of the rural community, granting loans or with benefits and installments Low for women-headed households; increasing the number of borrowers and creating rural people's interest and motivation for living in the countryside.
- Preserving indigenous architecture, using indigenous materials, avoiding blind imitation of urban housing, etc., are unfortunately much neglected, and new rural houses have become homogeneous and adapted to the natural and physical environment of the countryside. - In anti-poverty programs, the problems of villagers have been underestimated, which has led to their vulnerability. Therefore, investing in villages, creating complementary agricultural businesses, increasing production and, consequently, increasing rural incomes, can accelerate the growth and development of this sector.Energy saving is considered to be a problem with rural housing problems in terms of access to fossil fuels and mechanical equipment for heating and cooling buildings.

Land use reflects the interactive characteristics of humans and the environment and describes how human exploitation works for one or more targets on the ground. Land use is usually defined on the basis of human use of the land, with an emphasis on the functional role of land in economic activities. Land use, which is associated with human activity, is undergoing change over time. Land use information and land cover are important for activities such as mapping and land management. Over time, land cover patterns and, consequently, land use change, and the human factor can play a major role in this process. Today, satellite-based measurements with geographic information systems are increasingly being used to identify and analyze land-use change and land cover. With regard to the problems of changes and transformations in the studied area, remote sensing can allow managers to categorize images and evaluate land use changes, in addition to saving time and costs, which allows planners to make plans based on changes, more resources are lost. To be prevented.

In order to classify and detect the marginal land of the river, TM and OLI image images were selected for a specific month (August, August) for the years 1987 and 2017. The purpose of this study was to investigate the changes occurring in the studied area with an emphasis on agricultural lands. To do this, the images before processing in the ENVI software took radiometric, atmospheric and geometric corrections on them. After that, the main components of the river route were extracted. Five basic algorithms were used to classify the base pixel, but eCognition software was used to classify the object. Supervised classification identifies homogeneous regions with examples of land use and land cover, in which pixels are assigned in known information classes. Education is a process that determines the criteria for these patterns. Learning output is a set of spectral signatures of proposed classes. The first step in object-oriented classification is the segmentation of the image and the creation of distinct objects, consisting of homogeneous pixels. The main purpose of image segmentation is to combine pixels or small objects to create large image objects based on the spectral and spatial characteristics of the image. In order to evaluate the accuracy and compare the resulting maps, the overall accuracy and Kappa coefficient are used. When the sampling of pixels is done as a spectral or informational class pattern, the evaluation of the spectral reflection of classes and their resolution can also be done. An algorithm with the highest accuracy and accuracy will be the basis for the detection. Detection of changes, which leads to a two-way matrix and shows variations of the main types of land use in the study area, was carried out in this study. Pixel-based cross-tabulation analysis on pixels facilitates the determination of the conversion value from a specific user class to another user category and areas associated with these changes over the given time period.

The results showed that the object-oriented method is more accurate than the base pixel algorithms for providing user-defined maps. The amount of accuracy in the method based on object-oriented classification depends largely on choosing the appropriate parameters for classification, defining the rules, and applying the appropriate algorithm to obtain the degree of membership. The Kappa coefficient for each image is approximately 0.90. So these maps are the basis for the discovery of change. According to the results, the agricultural and residential lands have been increased and this increase has been accompanied by a decrease in rangelands. A general overview of this 30-year period shows that the arable and dry farming, respectively, increased by 2418.79 and 719.61 hectares and the rangelands had a decrease of 2848.86 hectares. However, the residential class and human effects show an increase of 428.88 hectares or a growth of 178.87%, which indicates the importance of agriculture in the studied area.

Identifying and discovering land cover changes can help planners and planners identify effective factors in land use change and land cover, and have a useful planning to control them. For this reason, maps are needed with precision and speed, and object-oriented processing methods make this possible with very high precision. The results of this study, in addition to proving the precision and efficiency of object-oriented processing in land cover estimation, between 1987 and 2017, have witnessed a decrease in the area of rangeland lands and, on the other hand, agricultural and residential lands, which is indicative of the overall trend Destruction in the area through the replacement of pastures by other uses such as rainfed farming.

Old trees are important and key elements of forest sites and are of great value in terms of forest management, reforestation, silviculture and ecology. Although old trees constitute a small percentage of forest trees, they account for a large share of forest carbon reserve and play a vital role in carbon storage. Understanding the how geographical and site distribution of these trees across the forest is essential to obtain information for forest restoration management. Therefore, this study was carried out to investigate the geographical and site characteristics of old trees of Wing nut, Ash, Hackberry, Sycamore, Elm, Olive, Cypress and Fig in Ilam province.

After querying the villagers and local people and conducting numerous forest surveys, the old trees were identified and selected on the basis of the diameter of the breast. Then their geographical characteristics including city, district, village, geographical coordinates and site conditions including slope, aspect, altitude, soil depth, climate and proximity to water source were measured or recorded.

The results showed that in terms of geographically distribution, the identified old trees have located in Ilam, Mehran, Malekshahi, Badreh and Dehloran cities. Topographically, the old trees of Wing nut, Elm, Ash and Fig were located in the 0-10% slope class, Hackberry and sycamore in the 0-10% and 10-30% slope classes, olive in the 10-30% slope class and Cypress in the 40-70% slope class. The old trees of Wing nut, elm, Ash and Hackberry were located in the north aspect, fig, sycamore and Cypress in the south aspect and olive in the west and south aspects. The old trees of Wing nut, elm, Ash, Hackberry, Sycamore and Cypress were dispersed at altitude class of 1100–1250 m and olive and fig old trees were at altitude class of 1250–1400 m above sea level. Climatically, the old trees of Wing nut, elm, Ash and Hackberry were located in the very cold Mediterranean climate, Cypress trees and some sycamore trees in the cold Mediterranean climate, and fig, olive and some plantain trees were in the semiarid cold climate. In terms of access to water resources, old trees of Wing nut, elm, Ash, Sycamore, Hackberry and Fig were located on the bed or margin of river, old Cypress trees had no access to water resources and some olive trees were close to water resources. In terms of soil subsidence, old trees of Wing nut, elm, Hackberry, olive, and fig were mostly in soils with medium depths. Old ash and sycamore trees were present in shallow to medium depths and old cypress trees were present in shallower soils. Although the identified old trees were present in limited sites, their long-term and sustained presence in these sites indicates that sites conditions are favorable for their survival.

Therefore, it can be concluded that the presence of low slopes, suitable soil bed and access to water resources were desirable characteristics for stability and survival of the studied old trees in these sites. Due to the above-mentioned characteristics, ecologically similar sites can be found in the forests of the province and can be restored by seed of old and resistant trees.