Journal of Spatial Analysis

Ultra violet radiation has some useful effects and some harmful effects on human health an d create many diseases. Nowadays not only declined but the usefulness of the therapeutic effects of the Sun in the treatment of diseases such as rickets, psoriasis and eczema have been proved. But prolonged exposure to radiation of the Sun is not always beneficial and may cause acute and chronic effects on the health of the skin, eyes and immune system. Ultraviolet radiation of the Sun is one of the most destructive waves for life on Earth. So Ultraviolet radiation index and predict its rate (1 to +11) as well as the analysis of this indicator will help people to protect themselves against the Sun

    Ozone station , global ozone measurement stations and only stratosphere in Isfahan, Iran, which is in the South and in the Northern geographical position latitude 32' 31 and 70 ' 51 is located over the East. The altitude of this station from sea is 1550 m. Also atmospheric parameters in this station which are measured daily include temperature, pressure, humidity, wind speed and direction and in the upper levels of the atmosphere at 12 GMT with the help of Joe's high temp radio instrument.

    The first step to do this research was gathering of climatic data and the statistical and quantitative analysis in order to study on the subject. Ultraviolet radiation data on the same basis of assessment, ozone station during the period January 2001-December 2010 has been collected. The second batch of data information gathered from meteorological station of Isfahan climatic elements from 2001 to 2010. This data is based on monthly averages for analysis of solar UV radiations from meteorological solidarity with the country.

Adjust the time series at the first step in the study and analysis of the data was done in order to equal intervals in these regular categories and methods of statistical analysis was carried out on them and the overall process of UV changes in the form of daily, monthly, quarterly and annually. Also part of the analysis that was carried out on the data, check how the sequence or they had over time; this way specify whether data periodically changes or trends have been or not. Once the data is based on the time of occurrence, sort and arrange the time series on them.

Annually analysis of UV index showed the general variation is a common feature of studied years but in the spring season have high variation in compared with other season. The main reason of this variation may be related to sunlight angle that can be showed atmosphere effect on received radiation. Descriptive statistic result indicated that the highest mean of UV index is 6.52 and minimum were 4.8 that have very high variations and may be it has different harmful effects. Also seasonal analysis showed highest UV index created in hot summer related to highest temperature in this season. The computational modeling of UV index against years in different season indicates there do not exist a linear relation between two factors. The correlation analysis of UV index and some climatic factors showed there are a significant relation between temperature  with 0.8570 coefficient that  can be said in relation to increase of temperature, UV rate increased and vice versa and with cloud cover correlation coefficient is  -0.393 that have significant negative relation.

    Results showed that the peak time period are output in the first half and the second half of the year, landing in the specified time series. As well as through a linear fit to all charts, increase or decrease of the radiation, changes the trend in recent years, showed that based on the ultraviolet radiation changes the average increase in the spring and summer and fall and winter shows a decline. Also according to the ultraviolet radiation in daily statistics review ozone assessment station in the studied period (2001-2011) maximum amounts of ultraviolet radiation index, (11.5) observed in the middle of the summer and the minimum amounts of radiation index (0.5) observed in mid-winter.

Thunderstorm is one of the most severe atmospheric disturbances in the world and also in Iran, which is characterized by rapid upward movements, abundant moisture, and climatic instability. Since this phenomenon is usually accompanied with hail, lightning, heavy rain, flood and severe winds, it can cause irreparable damage to the environment. Investigation of spring thunderstorms has a great significance regarding the irreparable damages can cause by them and also because of the higher frequency of this phenomenon in the spring and the necessity for preparedness and disaster mitigation actions. To identify the locations of the major thunderstorm risk areas, the entire country with an area of 1648195 square kilometers, which is located between the 25°-40° north latitude and 44°-63° east longitude is considered.     Spatial distribution of the occurrence of hazardous spring thunderstorms was analyzed using a series of monthly thunderstorm frequency data obtained from 25 synoptic stations over a 51-year-long period (1960-2010). Ward's hierarchical clustering and Kriging methods were used for statistical analysis. Initially, total number of thunderstorms in April, May and June were considered as the frequency of occurrence of thunderstorm in different stations in the spring. Measure of central tendency and dispersion which consists of the sum, minimum, maximum, range and coefficient of variation, standard deviation, and skewness were used to clarify the changes of thunderstorms and to determine the spatial and temporal climatic distribution of spring thunderstorms. An appropriate probability distribution function was chosen to determine the distributions of the data.  Due to the large volume of data and the uneven distribution of stations, cluster analysis and kriging methods were used to classify different regions into homogeneous groups for zoning and spatial analysis of spring thunderstorms, respectively. The statistical characteristics of spring thunderstorms were reviewed and fitted with a 3-parameter Weibull distribution. Regions considered for this study were classified in four separate clusters according to the simultaneity of thunderstorms in the spring. After zoning, it was found that the highest rates of thunderstorm took place in the northwest and west of country. The northeast of Iran has the second highest number of thunderstorm occurrence. The least number of thunderstorm event had happened in the central and southern half of the country.     According to the descriptive statistics parameters, maximum number of thunderstorms occurred in May.. Based on the results of the cluster analysis, there is a similar trend in the central and eastern regions, the rest of the country was clustered into five distinct homogeneous regions, including the northwestern, western, southern, northern, central northern and northeastern regions. Zoning results indicate that the highest number of the occurrence of this phenomenon in the country is concentrated in the northwestern and western regions. Higher frequency of occurrence of thunderstorms in the northwestern and western regions may be attributed to local topographic conditions like high mountains, orientation of the terrain, solar radiation on slopes and existence instability conditions, hillside convection, the presence of water resources and specific climatic conditions in these areas. In addition, as a result of a continuous surface obtained by the method of interpolation with the least amount of systematic error and also the use of correlation functions for recognizing the spatial structure of the data and estimating the model error when using the Kriging method, the weights are chosen in order to have a more optimized interpolation function. Also the cluster analysis may significantly reduce the volume of operation without affecting the results and will help in finding a real band due to more appropriate classification of different geographic areas with greater spatial homogeneity and minimal variance within the group. Based on the results of the spatial analysis, it is clear that Kriging and Ward cluster analysis methods are appropriate for thunderstorm zoning and classification of different regions according to occurrence of thunderstorm, respectively.

Forest fire is one of the important problems in Iran which is caused by different factors such as human and natural factors. One of these factors is climate conditions that can be created by heat wave and special circulation of atmospheric phenomena. Occurrence of forest fire in north of Iran have different impacts on environment such as destruction of natural. According to the position of Iran in the dry climate zone provides required conditions for this hazard. Unfortunately,every year thousands of hectares of precious green cover is burned. Forest fires have harmful effects on human life directly,or in directly and lead to environmental destruction and pollution, global warming, loss of vegetation, and dry soil erosion. As a result, research on forest fires will become necessary. The study region is Mazandaran province forests located  in north of Iran with area of  23756.4 square Kilometers.The main object of this study is to detect the forest fires using satellite data and associated analysis with synoptic approach based on weather maps.

To detect fire in the study area different satellite data such as  synchronized and geostationary satellite data were used. In this study, MODIS satellite imagery and global algorithm detection of fire to detect fire in the forest and meadows of Mazandaran province were used. The climate data including weather station data and weather map were used. Other data include data of LST and vegetation products of MODIS. In order to downscale the global data an appropriate threshold was defined. In the proposed method,  After geometric correction and radiometric the cloud mask was removed, And then fire potential was identified with different thresholds and tests. Three fire episodes of  Savadkooh 2006, Noor , 2009 , and Behshahr, 2010 were selected for study.

Results showed  a threshold value of 310 ° K for MODIS sensor band 22 is good for a global scale. Cold and small fires are not detected, Therefore Local threshold was used. In addition, surface temperature and vegetation mapping , chlorophyll amount of vegetation were used before and after the fire episode.It became apparent that the amount of chlorophyll was reduced and the temperature was increased after the fire.

   The synoptic maps of the fire day showed a low pressure over the region and mid level systems indicated the advection of warm air over the area. Surface stations showed the increase of temperature and reduction of moisture during the fire days over the long period mean values.

According to the results of the study the ground level data accompanied the upper level images and pressure patterns.

Universal high performance of fire detection algorithm was used  to identify areas of forest fires Using MODIS satellite images and global algorithm modified to suit the characteristics of the study area fire detection. Then three of the fires were identified with this method. The algorithms with MODIS images and weather data together indicated the validity of the study and performance of this algorithm to identify the location of fire in the study region. Therefore the method of this study can be used in other areas to detect forest fires.