حسن فرامرزی

Forest fire in many ecosystems is a natural phenomenon, but also a serious and dangerous threat with environmental, ecological, and physical effects. Therefore, this research investigated the risk areas of fire in Zagros forests identification to evaluate the changes in the time series of deals with a potential fire hazard. To achieve this goal fuzzy layers of analysis network process and order weighted average method were used regularly. For this purpose, fire Zagros forests using satellite images Landsat and MODIS Lordegan city in the period between 2000, 2007, and 2014 and the factors affecting fire are examined. The high-risk areas based on classification utility area and the number of zones were identified as fire-prone areas. In the analytical network process procedure, the largest weighs were assigned to the distance from residential areas and roads, GVMI index, and maximum daily air temperature factors which were 0.209, 0.198, 0.09, and 0.0716, respectively. Time series analysis map showing the extent of critical areas from 2000 to 2014 decreased by investigating the factors affecting fire occurrence in critical areas, distance for roads and residential areas, slope, aspect, GVMI index, and NDVI and maximum temperatures have the greatest impact were on fire. The low-risk scenario and a small amount of compensation with the ROC higher than 0.7 as the best model was the estimated risk of forest fires. The preparation of a map of areas susceptible to fire, as well as analyzing and analyzing the time series of factors affecting the fire in different years, is an effective step in helping forest managers to plan and implement preventive operations in high-risk areas.

Biosphere Reserves are international natural-biological protected areas that, besides offering protection, showcase achievements such as providing rare study habitats to scientists and demonstrating human skills in support of sustainable development. This study aims to evaluate the participatory management in the protection of Golestan National Park, one of the first biosphere reserves in the country.

This descriptive field research prepared the required data by having the target community, including non-governmental organizations, nature partners, local communities, government forces, and other members of society, complete internet questionnaires. The results highlight the cooperation of nature partners in their desire to participate in community education and in dealing with wood smuggling. Local communities showed prominence in fire prevention, and non-governmental organizations stood out in community education, fire prevention, and combating wood smuggling.

The results indicate a significant difference in participation in community education, firefighting, fire prevention, desire to participate in firefighting, dealing with forest destruction and conversion, dealing with illegal hunting, preventing livestock entry to the forest, and combating wood smuggling among groups.

Therefore, given the significant difference between the groups, it is possible to plan in the field of their interest and participation. Lastly, since society members frequently use social networks like WhatsApp and Instagram, and the target groups have strong membership in environmental groups, this capacity can be utilized in education and participation in the management of biosphere reserves.

Global forest area has decreased by nearly 180 million ha in three decades. So, many ecosystem services provided by forests have been threatened. Reforestation and afforestation are the most effective strategies for mitigating deforestation. Therefore, in a variety of countries worldwide, including Iran, several afforestation projects have been implemented; however, the quantity and quality of many afforested lands have decreased over time under the influence of catastrophic factors, environmental stress, and different management methods. Awareness and continuous monitoring of forest programs are some of the most fundamental forestry policies. Therefore, the monitoring of annual afforestation in the eastern Golestan province using Google Earth software was put on the agenda to prepare an afforestation map and identify the reasons for the success and failure of the implemented plans. According to the findings, 19,377.39 ha of afforestation have been planted in Golestan province. Of these, Maraveh Tappeh city has the highest amount of afforestation with more than 9,256 ha with C. arizonica L, C. sempervirens L. var. horizontalis (Mill.) Gord. and P. brutia Ten, mostly. The presence of suitable climatic and edaphic conditions in the Golidagh of Maraveh Tappeh City and the ArabDagh area of Kalaleh City played a prominent role in the success of artificial forests in these areas. It should be noted that wood smuggling, the presence of livestock, the occurrence of fires, the presence of natural and human obstacles, and continuous monitoring have been other factors affecting the success or failure of afforestation programs in the eastern Golestan province.

Since dead trees contain significant amounts of organic matter, they play an essential role in forest dynamics. In the present study, the changes in soil carbon stock were studied in relation to the dead tree features and its soil beneath in mixed broadleaf stands of Loveh forest in Golestan province, Iran using the Principal Component Analysis (PCA) and random forest model. For this purpose, the characteristics of 15 dead trees consisting of hornbeam, oak, Cappadocian maple, and ironwood were recorded in three decay classes 3 to 5, and the soil beneath them was collected from a depth of 0 to 15. The random forest model was implemented based on the relationship between the dependent variable (carbon stock) and the independent variables (effective factors) using the randomForest package in R software. The results showed that using the studied parameters, the random forest model justifies about 54% of the changes in soil carbon stock. According to the final model, the carbon stock of the soil beneath of dead tree is most affected by the three parameters of C/N ratio, nitrogen (%), and soil pH, so in a general trend with the increase of C/N ratio and nitrogen (%) and the decrease of pH, the amount of soil carbon stock around the dead tree has been increased. The present study's findings indicate that dead trees provide great potential for soil carbon storage, especially when faced with an old-growth forest ecosystem.

Golestan National Park is the oldest registered national park in Iran and a unique sanctuary for wildlife. This area was registered as one of Iran's Biosphere Reserves by UNESCO in 1957. Different non-governmental sectors play a role in the protection of this park, and the purpose of this study is to prioritize the importance of their role in its protection. For this purpose, participatory indicators of preventing forest destruction, educating local communities, extinguishing fire, dealing with predators, preventing the entry of livestock, preventing fire, cleaning the environment and performance scores for non-governmental groups, non-governmental organizations, nature partners and local communities with The use of the questionnaire was investigated, and the weight of each index was calculated using Shannon's entropy, and finally, the importance of each influential community in park management was prioritized using the TOPSIS model. In this study, the high importance of participatory indicators of forest destruction prevention, cooperation with environmental department, dealing with illegal hunters and environmental cleaning in park management were obtained with weights of 0.337, 0.187, 0.145 and 0.112, respectively. The results also show the high importance of non-governmental organizations with a weight of 0.87 in the participatory management of the park, so that local communities and nature partners were placed in the next priorities with weights of 0.36 and 0.06. Since the park, with its large area and special regional conditions, is affected by environmental and human tensions, according to the results obtained from this study, it can be said that non-governmental organizations and communities

The growth and development of technology and its expansion have caused criminals to use these technologies as required by their criminal acts, so that today identifying criminals has become one of the most important concerns related to the security of countries, the evolution in the nature of committing crimes Especially, the organization, transnationalization and technicalization of crimes requires a change in the approach of the police and the criminal investigation procedure, which should be upgraded and transformed in line with the change in the type of crimes committed. According to the advances in genetic science, the achievements of this knowledge can be used in the identification and prosecution of dangerous and international criminals.

The current research is practical and descriptive-survey in terms of type and purpose, the statistical population of this research includes 217 specialized police officers in Faraja in the year 1400, the data collection tool is a researcher's questionnaire based on the Likert scale. The obtained information was analyzed in a descriptive-inferential manner.

The findings of statistical data analysis show the significance of tests and the effectiveness of biological evidence in tracking and identifying criminals in transnational crimes. According to the results of the research and the role of biological evidence in the detection of transnational crimes, in order to discover transnational crimes and deal with criminals in a targeted way, the use of genetic knowledge by international police investigation officers is inevitable.

In order to manage the forests and optimal and sustainable utilization of the forest, it seems necessary to know the information on the volume of the residual stand. In this study, a systematic randomized inventory was carried out in 186 circular 10-acre plots in the educational and research forest of Darabkola, Sari, Golestan, Iran and the volume of each plot was obtained. In the next step, the physiographic layers of the area were prepared using the topographic map and the vegetation characteristics were prepared using the LISS-III image of the IRS-P6 satellite with a resolution of 23.5. After preparing physiographic layers and vegetation characteristics, their value was calculated for all plots. Then, regarding these variables and using two methods of multilayer perceptron neural network and multiple regression model, modeling was done. The results showed that the multiple linear model could model the volume changes in the region with higher accuracy (R2=0.75 and RMSE=0.3). The results of this research can be used in management planning and as one of the effective factors in the design of logging routes and forest roads so that areas with larger volumes are covered more.

The present study was designed and implemented in terms of type and method of descriptive-analytical and in terms of purpose and practical nature and in terms of data collection, documentary-survey and using qualitative and quantitative approaches.For a quantitative approach, the questionnaire includes 217 people, The validity of the questionnaire was confirmed by experts and its reliability was obtained by calculating the Cronbach's alpha coefficient of 70%. Descriptive statistics and inferential statistics were used to analyze the data. Findings from t-test showed that the value of t-statistic in all four dimensions was greater than 1.96, which indicates the significance of the test and the effectiveness of each dimension. All dimensions and components based on K-S test had an alpha value of more than 70% and the data distribution was normal. To confirm the predicted structures after the first-order factor analysis and to model the equations, confirmatory factor analysis, etc, which, the results indicate that the indicators are desirable and the items are in line with the theoretical structure.Based on the results, the respondents had the most effective dimension in identifying criminals, the technical dimension with an average of 4.53 out of 5 and the least effective dimension of the management dimension with an average of 4.26 out of 5. mean 4.4 and standard deviation 0.6. According to the findings, the effect of the set of dimensions was 4.41 out of 5 with a median of 4.5 and a standard deviation of 0.4.

In recent years, the addition of the various nanoparticles in dielectric of EDM process has been considered in order to improve the material removal rate (MRR) and surface roughness. In this regard, the effects of the addition of metal oxide nanoparticles including Cu, Al, Al2O3, C, Si, SiC, Gr and W, in different dielectric such as deionized water, kerosene, mineral oil and silicon oil, are surveyed. The results illustrate that the parameters such as the density, particle size, particle concentration and electrical and thermal conductivity of the nanoparticles can be affected on the process performance. ZnO is one of metal oxides which has high thermal and electrical conductivity so that it can improve the performance of EDM process. In this paper, the effects of the mass concentration of ZnO particle (1 to 4 gr)in dielectric of EDM process and the variation of peak current (between 6A to 24 A) on MRR and surface roughness in AISI 1045، AISI 4140, AISI D3 steels are investigated. The studies are done in two classifications that are including the rough and the finish machining. In rough machining, the results illustrate that the mass concentration 4 gram of ZnO nanoparticle mass increase the MRR values up to %10, %50 and %40, in AISI1045, AISI4140 and AISID3, respectively. Although, In finish machining (with the peak current 6A), the results are shown that the surface roughness in finishing in the AISI 4140 and AISI D3 was significantly improved, but the improvement of AISI 1045 is just %10.

Forest fire has many side effects on forest and land function. Among them are loss of biodiversity, reduction of economicvalue of forests and climate change in large scale. The aim of this study was to evaluate the changes in forest firespotentials. To achieve this goal, the required digital layers and data were obtained from the relevant websites and organizationsas well s through field surveys in the area of the study. After preparing the data by assuming the occurred fire, thelayers were entered in a fuzzy process using Analytical Network Process (ANP) and Ordered Weighted Average (OWA)method. For this purpose, Zagros fire forests (Lordegan city) were examined using Landsat and MODIS images and consideringthe factors affecting fire (topographical factors, human, climate and vegetation). In ANP procedure, the largestweighs were assigned to the distance of residential areas from roads, GVMI index and maximum daily air temperaturefactors in their magnitude order. OWA method was also used to create the hazard prediction model. Based on the results,the fire hazard map was prepared in four classifications: very low, low, medium, and high. An accuracy assessment wasalso performed using the relative operating characteristics. Of the six scenarios applied, the low-risk scenario and a smallcompensation amount of ROC = 0.702 were evaluated as the best model to predict the risk of forest fires. Due the highaccuracy and precision of the model obtained, it can be used to contain the fires that will occur in the future.

Using Technology not only has found vast application in crime prevention, but it has also established its foothold in the suppression and punishment of criminals. At present, in many developed countries of the world such activities as individuals’ identity control in border input and output, pursuing and monitoring criminals to detect criminal acts, facilitating city traffic, smart theft alarm systems notifying police centers, and many other police activities are all conducted using electronic equipment. Therefore; this research is intended to investigate the role of information-centric police in detecting runaway criminals via information-based systems (software and network). The present research is of applied from type and objective viewpoint and with descriptive nature is of survey type. The target audience of this research includes experts, detectives and NAJA executive police specialists (CID, Cyber Police, Intelligence Police and Prevention Police) in 1397. Using Koucran Formula, the sample volume was determined 82, and the data collection tool is questionnaire type based on Likrat Spectrum whose fluency and sustainability were proved with (a=0.908). To analyze data, we used Binominal Test or Relevance Test (In order to detect the effects or lack of effects of each variable in another variable) with Spss20 Software. The findings of this research show that using information-based systems (knowledge management, software systems, telecommunication systems and information banks) in detecting runaway criminals is effective. In regards to the results of this research and the role of information-based systems in detecting criminals and extracting the effective factors in this regard, removing legal obstacles along with security courses of actions for police access to all future information banks is an inevitable issue.

Faba bean is one of the main winter crops in Golestan province (northeast Iran), with an estimated production of about 106,284 tons of green pods and 7256 tons of dry grain while the harvesting land area  is about 1838 ha. Topographic characteristics, climatic conditions and the soil quality of an area are the most important parameters to evaluate land suitability. To develop successful cropping systems, it is necessary to understand how a crop such as faba bean responds to biological, chemical, physical, and climatic variables, and how this response can be influenced by management. Accordingly, farmers can improve their production in this district, and at the end of the study, the distribution and areas of land suitable for faba bean cultivation in Aq Qala were determined. In addition, this research provides information at a local level that could be used by farmers to select cropping patterns in accordance with suitability results.

The study areas of the research include agricultural lands and rangelands of Golestan province  Using 1: 50,000 maps of the national cartographic center of Iran, we created a 20 m digital elevation model (DEM) with a topo-to-raster function. In this study, the first agro-ecological requirements of faba bean were determined according to scientific resources. Several parameters were considered in this study, including the annual average, minimum and maximum temperatures, annual precipitation, slope, elevation, and some soil properties such as organic matter, pH, EC, texture, phosphorus, potassium and calcium. The last 12-year climatic data were gathered from 4 meteorological stations and 21 rain gauge stations in the Golestan province. The mean temperatures were calculated from daily mean minimum and maximum temperature data. The rainfall and temperature data of the whole province were used to interpolate and draw map of annual rainfall, and annual average, maximum and minimum temperature by geostatistical and interpolation methods. The slope and elevation information was obtained from the Digital Elevation Model (DEM) using GIS software. The standardization of data was used from fuzzy method and Analytic Hierarchy Process (AHP) was used for weighting the criteria. Finally, using ordered weighted average (OWA) in the  IDRISI software, faba bean cultivation potential map was prepared.

The results indicated that the most important variables, according to their specific weighting, were annual precipitation during the growing season (0.2876), slope (0.5396) and EC (0.3913). The digital environmental layers overlaid and integration in GIS media, then zoning of lands were carried out in 4 classes (highly suitable, suitable, less suitable and non-suitable). The study area includes different classes with diverse capacities for faba been cultivation comprising: a highly suitable potential, which constitutes 55.78% of the total area; a suitable class, 27.82%; a less suitable, 12.23%; and non-suitable, 4.17%. The final maps showed that more than 80% of agricultural lands of township are suitable for faba bean production. This research provides information at a local level that could be used by farmers and decision makers to select cropping patterns in accordance with their suitability. The topography, soil characteristics and climatic conditions were the most important determinant parameters of this evaluation. Our results revealed that 86.60% of the land area is suitable for faba bean cultivation. From the land suitability analysis, it was concluded that, in general, some nutrient contents of the soil are low or high for the study region. In addition, the research results indicated that the main limiting factors are high EC and low rainfall.

In conclusion, a combination of GIS, AHP and OWA is a practical and applicable method for determining land suitability for faba bean crops. In this study, the time-saving during the development of the land suitability map for faba bean was considerable. This method is almost a new application in Iran for land suitability analysis. However, decision makers should consider the side effects of applying these methods in the determination of suitable areas for crop growing. The result in of this study indicated that the OWA is a valuable approach in land suitability assessment, therefore, we suggest that the OWA should be used with AHP in future land suitability evaluation. We recommend that similar studies should use other parameters such as relative humidity, wind speed, solar radiation and heavy soil metals.

Identifying the flood susceptible areas is a vital and substantial element of disaster management to control and mitigate injuries of the natural hazards. The purpose of this study was to identify the important variables in creating flood areas and to present the potential hazard of flood in Golestan National Park (GNP) using machine learning techniques including random forest (RF), boosted regression tree (BRT) and maximum entropy (ME) models. In order to achieve these purposes, firstly, factors were determined by reviewing the relevant sources, and the databases were created by sorting out these factors. Finally, Flood risk modeling was done using machine learning techniques and the accuracy assessment were determined using the ROC method and real data recorded in nature. The results of the models showed the importance of elevation, distance from the river and transit road, moisture and maximum temperature variables in the event of flood hazard. So that the results of the BRT showed role elevation variable to 38.9%, mean temperature 19/2 %, Rainfall 13/6 % and distance from the rivers 13% and the results of ME showed role elevation, mean temperature and distance of road variables respectively 35.7, 22/4 and 13.8%. The results of the accuracy assessment models using 30% of the data that were not included in the modeling the ROC value showed BRT and RF model with 0.99 values, and the proper accuracy ME was with value of 0.89. Therefore, the maps obtained can be used to manage the flood crisis in the area

The rapidly growing world population places considerable pressure on increasingly scarce natural resources, spurring the need to develop more efficient and sustainable agricultural production systems to feed these growing populations. this study to evaluate the agricultural lands in Golestan province for soybeans, using Geographic Information System (GIS) and weighted linear method (WLC) was performed. For this purpose, the needs of the crop and environmental variable factors were determined and graded and according to current elements prepared required map. Studied Physiographic variables were consisted of slope, aspect, elevation and the soil texture. Data were standardized by fuzzy method, and Analytic Hierarchy Process (AHP) was used for weighting the criteria. Finally, soybean cultivation potential map were prepared with using weighted linear combination (WLC) in the software IDRISI The results showed the highest amount weighty criteria by the Analytic Hierarchy Process in the soybean soil texture (0.5228) and elevation whit (0.0765) had the lowest coefficient in the rankings. Then zoning of lands carried out in 4 classes (high suitable, suitable, less suitable and non-suitable Generally results of the weighted linear combination of Physiographic showed that 11.08 and 37.60 percent of the lands for soybean production areas were located in high suitable and suitable zones. In addition, limiting factor of the soybean cultivation in the Golestan province can be cited soil texture.

  The presence of roads plays an important role in the occurrence and prevention of forest fires, which causes damage to the ecosystem of the soil and seriously endanger the ecosystem's performance and service, and threat the stability of forest eco-environment. The rising incidence of this event has increased the need to develop appropriate management plans for areas that are susceptible to fire. Therefore, the present study investigates the role of the transit road known as the Asian Shahrah, which passes through the Golestan National Park and has direct and indirect effects on the park fires. In this study, first the human factors (distance of transit road, side roads, villages, tourist areas and the presence hunters and farmers) affecting the fire in this area were determined. After that, according to the way of influencing, these layers were fuzzy and weight factors were obtained in two cases of transit road and transit road transport using the Analytic Hierarchy Process. After determining the weight and prepare invoices using the weighted average method arranged in six scenarios and modeling was performed both with and without transit road and best-case scenario was found with comparison with the real situations fire map and use of the Relative Operating Characteristic statistics. Finally, zoning with regard to the risk of using Run macro modules, and where the zones were fitted. Results showed the role of transit roads in the presence of 0/296 weight and transfer road with 0/077 weight. The Scenario with the average level of risk and decompensation was recognized as the best scenario with ROC = 0/87. The results also showed that if transported, the high risk areas would from 5647 ha would reduce to 2986 ha which is in fact 47% reduction of the whole high potential risk area. Road transit plays a direct role in 46 percent of fires in the area. Considering the high weight of the road presence role in the fires of Golestan National Park, it can be said that Because of the presence of Turkmen Sahra region, and also deserts and plains of Semnan province in the north and south of Golestan National Park, warm winds from these areas blowing to the Golestan National Park, so there are favorable conditions for fire occurrence in the park, which will increase the chance of fire in the park by high traffic on the transit road. Therefore, with due attention to role of the Asian highway in wildlife road accidents and the loss of countless numbers of them and probability of fire occurrence in the region, the need to transfer this road to the outside of the park is felt more and more.

In order to create sustainable development in the tourism industry, the proper understanding of environmental potentials and its sensitivity to human activities is very important. This study has identified and prioritized the potential of ecotourism sites in the Kojur basin of Mazandaran province. Physiographies criteria, including slope, direction, and elevation, as well as criteria of distance from road, river, village, sliding locations and canopy percent, were selected as the appropriate index. The criteria were evaluated and fuzzy by the experts and Analytic hierarchy process (AHP) method. Subsequently, using the Ordered weighted average (OWA) scenarios, the appropriate ecotourism site was selected. To reduce risk and increase managerial power, Boolean logic was used. The results showed that the landslide and the roads had a maximum value of 0.315 and 0.238, respectively. The output maps of the OWA scenarios have shown that the northeastern range of the cougar basin is the most optimal location for the establishment of the ecotourism site, and the northern region was ranked next. In the scenario of the low-risk level and non-compensated, and low-risk level and low compensation scenario, 83 hectares of land were recognized for the appropriate ecotourism site. While, average risk and complete compensation, high risk and low compensation, average risk and non-compensation and high risk and no compensation, were 3179, 1255, 1909, and 2577 hectares respectively for ecotourism sites. The Boolean logic output showed that about 47 hectares of northeastern lands of Kojour basin are an appropriate ecotourism site.

Nowadays، fires are the most common damaging factor of natural ecosystems after urban and agricultural human activities. The aim of this study is to identify the susceptible areas to fires using Discriminant Analysis and Adaptive Network Based Fuzzy Inference System in the Golestan National Park as one of the most important biosphere reserves. The required data and digital layers were prepared from associated sites، organizations and field surveys in the area of the study. After preparing the data by assuming the occurred fire، the most significant effective factors were identified using Discriminate Analysis. These factors were calculated as a weighted average and models were implemented by using K-Fold Algorithm with trapezoidal، Gaussian، triangular and bell membership functions in six stages. The best model was used for simulation. The fire hazard map was prepared with five classifications، very low، low، medium، high and very high. An accuracy assessment was performed using the relative operating characteristic. The results of the Discriminant Analysis showed the important factors، including presence of hunters and shepherds، distance from roads، average temperature، distance from the springs، rainfall during the growing season and slope. Validation trapezoidal membership functions showed best results with value of R2= 0. 534 and RMSE= 0. 283. The results of the accuracy assessment obtained with value of ROC= 0. 875. While the very High-risk area was 972 hectares، and High-risk area was 16879 hectares of 91895 hectares area. According to accuracy of the proposed map، it can be used to control the region fires in Golestan national park.

Extensive fires in the forests are examples of natural crises (Hosseinali، 2005) and forest fire events are increasing in the conditions of changing climate and global warming; (Azizi and Yousefi، 2005). This phenomenon is considered one of the most destructive factors for forest ecosystems، causing irreparable damages (Marozas et al، 2007). Some of these damages include land use changes، emissions of greenhouse gases، disruption of forest structure and nutrients losses in ecosystems resulting from burning of vegetation and forest floor layers (Vakalis et al،2007; Alexandridis et al، 2008; Bakhshandehsavad rudbari et al، 2011). According to FAO (1995) the annual average of fires in forested areas around the world is estimated to be two million hectares. In many parts of the world، fires in forests and ranges is one of the most important issues and concerns، not only from an environmental perspective، but also from economic، social and security viewpoints (Silvia Merino and Gonzale، 2010). One of the research fields for controlling forest fire is to identify critical points in terms of fire in forested areas، because the lack of knowledge about these areas will cause the occurrence and spreading of forest fire، delay in fire suppression، and damage to forest plant and animal life (Jaiswal et al، 2002). Therefore، preparing the potential map of fire (fire critical areas) plays an important role in reducing the number of fires and preventing the destruction of forests (Dong et al، 2005) and helps the forest managers to prevent fires with special care in critical areas before they occur. According to a study by Atrak Chali (2000) the average area in forest areas that is burned due to fires is 7،000 ha and return intervals of forest fire in Golestan province varies from 5 to 7 years; therefore preparing fire hazard maps with high-precision is necessary for planning and crisis management. When، preparing the maps of fire risk، GIS is used as a basic tool for spatial data management. In many studies، GIS have been used to identify critical points and potential techniques have been applied. Mohammadi et al (2009) attempted to map the fire susceptible areas in Paveh forests fires by conducting field operations and by considering the measures of vegetation، physiography، climate، human and distance from roads and streams as well as by applying the analytic hierarchy process (AHP) and they showed that the resulting map was highly corresponding with the real locations of fire. In a study in Spain، Nieto et al (2012) evaluated the occurrence of fire caused by lightning during a 3-year period from 2004 to 2002 using logistic regression. In this study some parameters such as lightning، topography، vegetation and climatic parameters were considered. The results showed that the lightning was most important factor causing fire in the area fires during mentioned period and a risk model with ROC of 0. 7 obtained، indicating the good performance of the model. Golestan National Park is First Park that was considered as the national park in Iran and one-eighth of plant species، one-third of bird species and more than 50% of the mammal species live in this park (Hassanzade Kiyabi et al، 1993). This park is susceptible to fire due to its characteristics vegetation as well as occurring at a region with winds formed by the clash between wet and dry weather fronts (Shokri et al، 2002). This study models and identifies areas susceptible to fire in Golestan National Park using logistic regression، taking into account parameters influencing on the fire in the region. Study Area: Golestan National Park is located at the Northeastern part of Iran، East of Golestan province، Northwest of Khorasan province، and North of Semnan province between 37º 17´ 43´´ to 37º 31´ 35´´ N، and 55º 43´ 25´´ to 56º 17´ 48´´ E. The park area is 91،895 ha with a perimeter of 198 km. A transit road، known as Asian road that connect the northern and central Iran to the north-eastern Iran passes through the park. There are several villages around the park including Tangeh rah، Terjenli، Ghoch Cheshmeh، Zav، Tomak، Kondosku and Dasht Shad in West of the park، Dasht، CheshmehKhan and Armadlu in South of the park، Robat Ghahrahbil in East of the park and Lohondor، Yelcheshmeh and Behkade in North of the park.

In this study we first determined parameters and their influences on fire event، then information related to these parameters was collected from the related organizations as well as by inventory in the study area. Affecting parameters were prepared in the ArcGIS and IDRISI software packages. Based on topographic map، Elevation ranges from 467 to 2342 m above sea level in the study area. slope from 0 to 72 degrees and slope aspect maps with 9 classes were extracted from a Digital Elevation Model (DEM). Normalized Difference Vegetation Index (NDVI) map was extracted from MODIS satellite images of 2011. Humidity and temperature isopleths maps were obtained from interpolation of meteorological data 2001-2011 years of climatology and synoptic stations around the park based on Inverse Distance Weighting (IDW). Considering the effect of the presence of hunters and ranchers on fire events in the park، the distance from arresting positions of offenders in 2007-2012 as was mapped the higher probable presences in the park. Also a buffer zone was established from camps as tourist sites، villages around the park، transit road passing through the park. In the study area، 9 vegetation classes were identified including dense-canopy forest، low-canopy forest، average-canopy forest، very low-canopy forest، good pasture، medium-vegetated pasture، woodlands، bushy vegetation، and agricultural land. The occurred fires during the last 30 years was determined based on records of Central Office of Park، information provided by the guards as well as signs of the fire using GPS، then the Boolean fire maps was drown in Arc GIS software. After selection the parameters، fire hazard map prepared using logistic regression method in the IDRISI software. Logistic regression is run as computational binomial regression in which the dependent variables of nature are entered binary. The uses model accessory was assist with Relative operating Characteristic (ROC) and Pseudo-R2 statistics. Finally، sensitivity of variables was examined by removing them using ROC and Pseudo-R2.

The regression equation resulting from the model was calculated as follows: Logit (fire) = 38. 792 + 0. 05475*Aspect + 0. 79038*Tem - 0. 000666*Camping + 0. 0014*Elevation - 0. 00037*Shepherds + 0. 00036*Hunter + 0. 0081*Landuse -0. 7874*Moisture + 0. 0011*NDVI + 0. 0004*Road - 0. 051747*Slope - 0. 00006*VillageIn this model، variables such as aspect، elevation، mean temperature (tem)، distance from road، and presence of hunter، land use and NDVI are positively correlated with fire risk while parameters of slope، camping، presence of ranchers، moisture and distance from village are negatively correlated with fire risk. The ROC، Pseudo-R2 and Chi-square were calculated 0. 9267، 0. 3133 and 102227. 3 in the model، respectively. The fire risk map was prepared using logistic regression. The results of this study both from the obtained equation and from measuring the sensitivity of variables indicate that temperature and humidity are affecting on the occurrence of regional fire. Since the ROC statistic of 0. 7 indicates low accuracy، 0. 7-0. 9 value indicate the practicability and a value more than 0. 9 represents the high accuracy of model and Pesudo-R2 values greater than 0. 2 can be considered as a relatively good fitness، in this study ROC Pesudo-R2 values were found 0. 9264 and 0. 3133، respectively، indicating the high accuracy and good fitness for the fire risk model. Therefore logistic regression can be introduced as an appropriate method to classify the fire risk. Understanding the behavior of forest fire and factors causing the appropriate environment for fire occurrence and influencing on fire behavior are of high importance for fire forest management، thus this model can be useful for designing of fire management and taking preventive measures in high fire risk areas.

Considering the location of area، high temperatures and low humidity that provides favorable conditions for fires، and also given the high traffic of travelers، tourists، ranchers and hunters allowed in the park، the results showed that fire risk is in this park. Due to the high accuracy obtained from the logistic regression model in this study، one can claim that this method is appropriate for the evaluation and modeling of fire risk thus the resulting model can be used for preventive measures.