forest

One of the road quality control methods is the management and planning system based on the use of UAV, which, in addition to being comprehensive, highly accurate, very low-cost, and of course fast, compared to the old methods where the road surface is measured by workers and experts technical and is done in the form of on-site and field visit, it is much more economical (Zhang et al., 2015:38). (Jafari et al., 1401:2) evaluated the accuracy of the longitudinal profile of the road using the UAV system and mapping cameras. The results of the research showed that the digital model of the surface obtained by overlapping the UAV images is capable of evaluating the accuracy of the longitudinal profile of the road and the quality of the images taken by the UAV is very high and provides better and more details and saves time. Forlani et al., 2022:13 evaluated the influence of ground and aerial control points and their quality on the accuracy of the 3D model obtained from the UAV in the southern part of the University of Parma campus. The results showed that by increasing the quality of the coordinates of the lens centers, the accuracy of the 3D point increases, and the height accuracy of the 3D model of the surface increases twice if a ground control point is added. Due to the great importance of forest roads for optimal management and exploitation of forests, new methods should be sought using remote sensing capabilities. Due to being expensive and time-consuming, traditional methods increase the measurement error and decrease the accuracy in the preparation of information and data obtained at the network and research levels. The use of remote sensing data and drone images with high spatial resolution reduces the cost and facilitates the monitoring of the condition of forest roads. The purpose of this research is to use the images received by Phantom 3 UAV and ground control points with different numbers and distribution as well as without ground control points to check and measure the technical and geometric characteristics of roads and also compare the effect of DSM production quality processing method on The improvement of the quality of the digital model of the earth is the result of UAV images.

UAV images in suitable weather conditions with a flight height of 100 meters from the ground, overlap length of 85% and width of 75%, and a speed of 5 meters per second by the Quadcopter Phantom 3 Pro UAV in the winter season and the condition of forest trees without leaves in January 2023 in a part of The area of Darabkola forests, about 2 km long and 200 meters wide around the road, was received in three separate flight projects during different days. In this research, first, the detailed field measurements of the depth and width of some technical specifications and geometry of forest roads (side channels, gabions, and ditches), surface defects of roads (potholes), and waterways leading to the roads were measured with precise meters and the location of the measurement points was done with DGPS. In addition, several ground control points were made for accurate georeferencing of images and preparation of accurate and integrated orthophoto mosaics of the area using differential GPS and processed using the PPK method. Digital surface models of the region in several modes in the form of processed images in two processing methods with high and medium quality, without accurate GCPs and using accurate GCPs and separate and integrated flight projects were prepared, and technical specifications were extracted from the obtained models and compared with ground observations.

The results of the whole area with quality control points (high and medium) compared to the whole area without quality control points (high and medium) showed that the square root of the average error is lower and has the best height accuracy. Ground control points should be evenly distributed throughout the study area (ideally in the form of a triangulated grid). In this case, the maximum distance of each control point to other control points will be as small as possible. For a certain number of control points, the accuracy obtained by using an optimal distribution was twice better than when the control points had an inappropriate distribution. The best results for accuracy were obtained by considering the control points in the present study. These results are with the studies of Heydari Mozafar et al. (1401:3), Ghafari Thabit et al. (2018: 6), Abbaspour et al. (2017: 4), Zhang et al. (2015: 38) and Rock et al. (2022: 34) are consistent. Also, flight plan areas 1, 2, and 3 with quality control points (high and medium) have a lower mean square root of error than flight plan areas 1, 2, and 3 without quality control points (high and medium). The dispersion of ground control points is more effective than the number of ground control points on the accuracy of the 3D surface model. These findings are in agreement with the results of some researchers, including Ruzgienė et al. (2015: 33), and Gindraux et al. (2017:16) who concluded in their studies that proper distribution of control points has a significant effect on the accuracy of the 3D model up to a certain range Is Consistent. The addition of control points of the flight plan area 1, 2, and 3 in the present study increased the accuracy of the 3D model In this regard Forlaniet al (2022:13) Adding a ground control point roughly doubles the elevation accuracy of the 3D surface model, noted.

The results showed that the DSM produced from UAV images could extract some technical and geometrical characteristics of forest roads. Overall, the results of the surveys showed that the DSM generated from drone imagery is capable of extracting some technical and geometrical specifications of forest roads and forest land micro topography, but requires the use of precise ground control points and high-quality image processing.
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Today, it is widely accepted that participatory methods are the most efficient means of achieving sustainable management of natural resources. Engaging local communities in decision-making regarding natural resource management is a way to protect these resources and improve villagers' livelihoods. However, there needs to be more participation in natural resource management among local communities. A significant part of Dena County's natural resource areas is designated as protected areas, making their optimal management of great importance. Therefore, this research aims to analyze and evaluate collaborative natural resource management in the rural areas of Dena County. This research is practical and uses a descriptive-analytical analysis method. The statistical population includes all the villages of Dena County, with 30 villages classified probabilistically based on criteria such as the number of households, the village's natural location, and its spatial distribution within the county. The sample size was determined using Cochran's formula, resulting in 485 rural operators. Data were collected from both library and field sources. A questionnaire was used in the field section, validated by the opinions of 37 experts, and its reliability was confirmed by examining Cronbach's alpha coefficient for each dimension of participatory management. Data analysis employed a one-sample t-test, one-way analysis of variance, Duncan's test, and the Kriging interpolation method. The research results show that overall, people's participation in natural resource management is in an unfavorable situation. Additionally, the spatial distribution of cooperative natural resource management indicates a more favorable situation in the southern areas of Dena compared to the northern areas.

The continuation and stability of the river catchments depends on the passage of water and the transfer of sediment. Just as river flow information is vital for many practical applications such as water allocation, long-term planning, catchment management operations, flood forecasting, design of hydraulic structures, etc., amount of sediment yield in rivers is important from a variety of aspects such as river morphology, engineering designs to river water resource, reservoir dams, river organization to Inhibition of erosion and floods, irrigation networks, etc. are important. Proper and sustainable use of water and soil resources within the river catchments requires awareness of the spatial variations of hydrogeomorphic elements (water discharge, sediment discharge) and the determinants of these variations. Various studies refer to the key role of forests in the water cycle, soil protection and habitat protection, and show that increasing or decreasing forest cover has had an effective role in the hydrogeomorphic regime of the rivers. Due to the importance of interdisciplinary studies and understanding of interactions between different biological and non-biological components of river catchments in regards to sustainability and continuity of natural and human environment, the present study intends to be aware of the quality and quantity of relationships between forest cover and discharge/sediment yield in the Talesh catchments, NW. Iran.

This study was based on correlation and regression analysis of the ecohydrological relationships. The research statistical population included the Talesh region and the research sample population included 12 important catchments in this region. The data used included monthly water discharge and sediment yield data of hydrometric stations on the one hand and the digital satellite images included the Aster digital elevation model (DEM) and Landsat 8 image on the other hand. Data analysis tools include geographical information system (GIS), Google Earth, SPSS and Excel. The steps of conducting the research were such that: firstly, the hydrogeomorphic variables including the mean, maximum and minimum rates of water discharge and sediment yield (S.Y), were calculated for 2020yr. Then, the 12 watersheds were extracted based on the position of the hydrometric stations from the DEM with a spatial resolution of 30 meters. The next step was to extract the forest cover from the Landsat 8 image, which was obtained on June 3, 2022. In this regard, the satellite image classification in the form of two class of forest and non- forest was through the maximum likelihood algorithm. Satellite images were classified using 300 training points. Finally, the correlation test between the forest cover and water discharge and sediment yield was performed in the SPSS software. The significant level of correlation relationships was ≤0.05.

The results of the correlation test showed that there was a significant relationship between the percentage of forest cover and the water discharge in the catchments. The correlation coefficients (R) were -0.58, 0.58, -0.46, respectively for mean, maximum and minimum discharges, indicating that definite and positive role of the forest in preventing rapid and erosive runoff. In contrast, the relationship between the percentage of forest cover and S.Y in the studied catchments was not significant and the correlation coefficients for mean, maximum and minimum S.Y are at -0.07, -0.05, -0.06 respectively, which is indicative of the weak correlational relationship between the two variables. However, the separation of catchments as large catchments and small led to improvement of correlation relationship between forest cover and S.Y, despite being insignificant, so that correlation coefficients in small basins for mean, maximum and minimal S.Y, respectively of -0.656, -0.60, 0.339, respectively. Given the significant relationships, it was possible to provide regression prediction equations for monthly mean and maximum discharge based on the percentage forest cover in the catchments. The insignificant relationships between forest cover and the sediment load can be explained by complex nature of the sediment load transfer, especially storage and re-movement of sediment load, making it difficult to establish significant relationships between the sediment yield (S.Y) and the environmental variables affecting it. On the other hand, the relationship between vegetation and the S.Y in catchments is usually complex and nonlinear, and therefore the use of nonlinear relationships may make the relationship more complete and obvious. Finally, the multiplication of the factors involved in the production and transferring of sediment load makes it difficult to model and predict the spatial variations of sediment load.

The present study attempted to provide a quantitative analysis of the spatial relationship between the forest cover and the rates of water discharge and sediment yield (S.Y) in the Talesh catchments by adopting an interdisciplinary approach. The results of correlation analysis show that the presence of significant and inverse relationships between the percentage of forest cover and water discharge of the catchments reflects the distinct role of the forest in reducing runoff and the incidence of dangerous floods in the Talesh catchments. In contrast, the relationships between forest cover and S.Y in the studied catchments are not significant. This conclusion shows that we are not able to provide a prediction model of S.Y variations based on the percentage of forest cover in the catchments, but the reverse relationship between the percentage of forest cover and the S.Y of the catchments implies the protective role of the forest in adjusting the process of precipitation, runoff- erosion and enhancing of the environmental quality in catchment systems. First of all, it should be noted that the forest cover variable is considered as a modulator variable or interface between the inlets and outputs of the catchments system, so it is likely that the direct role of the forest on runoff and sedimentation couldn’t be easily grasped by statistics analysis. In this context, there are various natural and human factors that may play a more effective role in the S.Y variation of the catchments than the factor of forest cover. Increasing of correlation coefficients (R) between the percentage of forest cover and S.Y in small catchments indicate that these catchments are an ideal scale for identifying controlling factors of sediment yield.

The aim of the present study is to analyze land use changes in Namin County, with a particular focus on assessing forest cover changes over a 30-year period. In this study, to examine the trend of forest changes, satellite images from the years 1991, 2000, 2010, and 2022 were classified, using the object-oriented nearest neighbor algorithm, into five categories: agriculture, forest, residential, rangeland, and water. Following the analysis, the land use changes from 1991 to 2022 were quantified, using the change detection method. Additionally, the future land use map for the year 2035 was modeled using the Markov and CA-Markov methods. The evaluation of land use maps indicates that in 1991, the areas of rangeland, agricultural, residential, and forest land use were 777, 122, 6, and 50 square kilometers, respectively. By 2022, rangeland use had decreased to 752 square kilometers, forest land use had decreased by 34 square kilometers, and residential land use had increased by 44 square kilometers. The results of the Markov and CA-Markov model predictions suggest that by 2035, the areas of rangeland cover will be 650 square kilometers, agricultural land use will be 250 square kilometers, forest land use will be 28 square kilometers, and residential areas will be 50 square kilometers. Overall, the findings indicate that, given the increasing population and uncontrolled construction, rangeland and forest cover areas will decrease, while agricultural and residential land use will increase over the next 13 years.

Forest fires worldwide cause severe damage to vegetation, soil and natural habitats, resulting in direct and indirect negative environmental impacts such as deforestation, climate change and drought. Therefore, identifying and determining the hazards of vegetation that suffer from fire is crucial for their management and development. The proliferation of remote sensing images such as the active fire products of the Terra and Aqua satellites over the past two decades has been one of the most essential methods in detecting these fires. However, the active fire product of the MODIS sensor in previous studies has shown that they alone do not provide good results in fire-affected areas. Therefore, it is necessary to evaluate vegetation with basic maps. The aim of this study was to investigate two types of plant products and to discover the active fire of MODIS sensor and FNF-JAXA forest and non-forest cover maps for better separation of burnt areas of vegetation in Iran between July 1 and 160 2020. The results show the highest area of fire on Julius 144 with more than 49 thousand hectares and Julius 128 with more than 45 thousand hectares. However, the largest area of the fire, forest cover is estimated at 120 to 160 in 2020 with more than 14 thousand hectares. Khuzestan province had the highest area of fires in the period under study that most of these areas in agricultural lands and the three provinces of Fars, Kohgiluyeh and Boyer-Ahmad and Bushehr had the highest area of fires in forest cover. The highest frequency of fires was observed in agricultural lands, the main reason for which could be human intervention. The evaluation of the results showed that the use of the FNF-JAXA product (accuracy of 87.4% and a Kappa coefficient of 0.85) compared to MODIS products (accuracy of 80.3% and a Kappa coefficient of 0.78) in the separation of forest areas has better capabilities. However, the ability of MODIS products to distinguish between pasture and agricultural vegetation is an important advantage, which the FNF-JAXA product does not have. In general, the findings of the research show that the MODIS product and FNF-JAXA maps can be used as reference maps to distinguish different types of vegetation that are subject to fire, in damage assessment and management.

Despite the great emphasis on the importance and protection of forests and the significant contribution these resources play in achieving sustainable development, the problems related to forest fires have become more critical. In this regard, the general goal of the current research was to present a paradigm model of the fire phenomenon in the forests of Chavar Township in Ilam Province by using the grounded theory method. The study population included experts and key informants in the field of forest management and protection, including experts from the Department of Natural Resources and Watershed Management in Ilam and Chavar Township, trained forces of the protection unit of the Department of Natural Resources and Watershed Management of Ilam province and Ilam and Chavar Township, the local communities of Bankhshak and Ganjvan villages were part of Chavar Township and non-governmental organizations (NGO) were active in the field of forest management and protection at the level of this Township. The participants in the research were selected using purposive and maximum variation sampling. Data were collected through depth interviews. The result of the application of grounded theory in this study was a conceptual model that showed human, participative, managerial, motivational and natural factors as causative conditions, cultural-social and economic factors as contextual conditions, and legal-policy-making, educational-informational factors, supervisory and infrastructural conditions as intervening conditions have caused the fire phenomenon in the forests of Chavar Township. The findings showed that extensional and educational, appropriate legislation and supervision, and managerial and economic strategies were the most important strategies to deal with the fire phenomenon in the forests of the study area.

The tourism industry, as a clean and job-creating industry, has been one of the most profitable industries in the world in recent years and is always the focus of development policies and programs. In order to develop and survive in the tourism sector, governments and private sectors at macro to micro levels need to forecast the demand in this sector. Today, a forest fire is one of the leading natural disasters and has worried all countries about its effects. Widespread fire in forests is one example of a natural crisis and dealing with it is crisis management. In this research, the factors of tourism management and fire prevention, fighting in forests and pastures are discussed. In order to protect forests and pastures against the risk of fire, one of the first strategies that are considered is to determine the areas prone to fire, and other strategies for this purpose include the preparation and implementation of forestry plans, rapid fire detection, and comprehensive response with all protective measures, regular planning and proper culture in order to preserve natural resources, use of indigenous knowledge of people in forest management, creation of a fire crisis center in forests to serve forest areas at risk, coordination of firefighting forces with public relief forces in order to deal with by fighting fires, training human forces and using effective and up-to-date equipment, the experience of the countries can be used. As a result, tourists and residents should not set fires in forests and pastures and burn the remains of agricultural products in fields.

The forest as one of the renewable resources plays an important role and a suitable platform for social and economic activities. In this context, identifying the effective factors in the sustainable development of the forest and knowing the indicators and management criteria of this natural area and paying attention to the shortcomings and strengthening the abilities is one of the current needs, therefore this research tries to measure the extent and measure of the management of the sustainable development of the forest based on FMU model with 6 indicators and 48 criteria and in the form of sfm paradigm in the forests of Ilam province, to determine the management level of sustainable forest development. The statistical populations in this research are the experts and specialists of the Natural Resources Department, especially in the forestry department in Ilam Province, and the sample size was determined through the snowball method of 15 elite experts in the field of forestry in the Department of Natural Resources and Watershed Management of the cities of Ilam Province. The results show that out of the 6 main indicators measured, water and soil management indicators with 71.5% and laws and organizations indicators with 60.37% are at a relatively favorable level. Biodiversity indicators with 47.38 are at the average level and economic-social index with 39.33%, ecosystem index with 38.92% and stakeholder participation index with 30.6% are at a weak level based on the sfm measurement and sustainability chart which is done with human and natural considerations, the management performance in the discussion of the natural index is 49.7% and the performance of the human index in the management of the forests of the region is 43.5%, which indicates the level of achieving the management goals of sustainable development in an average level.

Degradation of the country's forest resources and natural pastures has various factors and has adverse ecological, economic, social and political consequences. The main purpose of this article is to explain the degradation of Iran's forest resources from the perspective of the concept of resources in a relational approach by relying on documentary information and local studies and to answer the question that from the perspective of the concept of resources in the relational approach. What are the factors affecting the destruction of the country's natural forest resources? From the set of research findings, it is inferred that in the social context under discussion, the combination of resources has had interactions that have led the use of material resources towards the use of resources in the traditional system. In the context of the study population, the interactions of natural resources, knowledge, power and social capital have been in a way that can be acknowledged. Sophisticated complex, creative and innovative interactions have no place.

Rapid detection and investigation of volume and scale fires, is a critical element to control such natural disasters. Therefore in current research synoptic pattern of forests fires of Golestan province was investigated. For this purpose were collected the information related to the distribution of temporal and spatial level fires from the Department of Natural Resources of Golestan province in the period (1390-1384) and the days in which the fire was mentioned by natural causes were identified. Then the synoptic patterns of the region at the time of occurrence of fire to extract and track their movements were tracked using Lagrangian algorithm. In the next step by using principal component analysis, were identified prevailing types in mentioned level in the event of pervasive fires. The results showed that at the time of occurrence of fires in the study area are 4 pattern of rule. The first pattern is omega-shaped blocking in longitude between 40 and 70 degrees east and latitude 30 and 70 degrees north, the second pattern is very deep trough on the West side of Russia and the Middle East, The third pattern formed relatively deep trough in the West Black Sea and dragged it to lower latitudes And the fourth pattern is a barrier with height of the center 5800 geo potential meters on Iran.

Sustainable development, which, in the broadest sense, is a provider of the needs of the present generation and future generations or tomorrow, is always considering the conservation of land and, consequently, forest protection. The purpose of this study was to investigate the role of socioeconomic issues affecting forest management in one of the regions of Iran and Turanian, Shadi Garden in Khatam city, and further understanding of these issues and its relation with protection and exploitation of forests. Sustainable environments, which in the broadest sense represent the needs of present generations and future generations or tomorrow, are always considering the issue of protecting the land and, consequently, protecting forests. The purpose of this study was to investigate the role of socioeconomic issues affecting forest management in one of the regions of Iran and Turanian, Shadi Garden in Khatam city, and further understanding of these issues and its relation with protection and exploitation of forests. The present study was a survey-descriptive-correlational study conducted in a field study using a questionnaire.

Wildfires cause substantial losses of property and human lives in ecosystems in Iran and all around the world. Every year, about 6000 ha of forests are affected by fires in Iran (Jahdi, Salis, Darvishsefat, Mostafavi, Alcasena, Etemad, Lozano, & Spano, 2015).These fires can occur naturally due to climate change or abnormally caused by human activities in the forests. In fact, fire is one of the most important factors in disrupting the structure and dynamics of forest in natural conditions that produces a large amount of dead wood caused by the destruction of trees (Coban & Mehmet, 2010). As a result, there are significant costs to prevent fire every year in countries it takes place, and managing ecosystems is a way to reduce the effects of fire on war and maintain perspectives. To manage fire in forests, understanding the behavior of the fire and the factors causing it in a prone environment and factors affecting its behavior are essential (Artes, Cencerrado, Cortes, & Margalef, 2013). One way to manage fire is FARSITE model. This model has become popular due to its steady structure and simplicity of popularity in the modeling of fire spreading. This model is considered as one of the main fire simulation systems used to describe the behavior and release of horrific fires and is a semi-experimental model (Shen, Prince, Gallacher, Fletcher, & Fletcher, 2017).

For the FARSITE Fire Extender simulator, we need 5 layers of GIS height, slope, direction, fuel type, and canopy. All of these spatial data describe the landscape of the area. Topographic data (elevation, slope and tilt direction) were extracted from 1: 25000 maps of the country's mapping organization, which were converted to ASCII (Kanga & Singh, 2017) format using ArcGIS10 to prepare for entering the FARSITE model. Meteorological data is another input similar to the FARSITE firewall, which includes the degree of heat, relative humidity, and wind speed. To obtain climatic data, synoptic stations in Ilam province were recorded at 3-hour intervals. The appropriate burning model of the research area was selected based on the description of 53 standard burning model developed on the basis of the fire extension model. This selection was made using vegetation maps, map coverage of the area and observations and field studies based on similarity of the existing vegetation characteristics and description of this model. In the last step, in order to simulate the GIS layers (slope, direction, height, combustion and canopy), the FARSITE model was entered in an appropriate format. Then, the area was classified according to the extent of the fire.

The results showed that fire in four areas where it occurred had different behaviors, which is also due to different natural conditions in these areas. Also, fire hazard zoning, in the province of Ilam shows that, 1.5% of the area has a high risk of fire. Therefore, it can be stated that the study of different factors (topography, vegetation, burning and climatic conditions) in the studied areas shows the complexity of fire behavior in these areas. It is under the control of various factors. To identify the behavior of the fire, all the parameters and influential factors must be considered together and in conjunction with each other.

Also, according to the results of FARSITE simulation and its accuracy evaluation in the region, using kappa coefficient, all points are in agreement with real values, which indicates the performance of the model in this region, and in none of the regions the coefficient value Kappa has not been negative. Therefore, the implementation of this model is a useful guide for forest fire management, and based on it, a fire prevention crisis management program can be implemented in the three phases of initial operations or pre-occurrence measures (prevention plan), action plans (coping plan), and post-operation operations (recovery plan).

Identifying tourism development capacities is an undeniable priority in any country, especially in developing countries. There are various methods for determining such zones. Given the sensitivity of forest ecosystems to human interference, the purpose of this study is to evaluate the ecological potential of Tonekabon forests.

To evaluate the ecological potential of the study area, we used the combination of Makhdoom and FAO model in GIS environment using Layer Overlay (IO) technique and weighting by AHP method. In this study, the importance of the criteria and sub-criteria involved in the evaluation process was determined using experts' hierarchy and the weight of each layer was determined using Expert Choice software.

Results indicated that 118.73 hectares of the area is suitable for centralized recreation and 487.72 hectares for extensive recreation and the rest is of conservation value.

The results of this study showed that the combination of IO with AHP in GIS could well compare and evaluate different layers according to the criteria and be used as a suitable tool by decision makers to determine forest ecological potential for tourism development. The issue can be effective in achieving sustainable tourism development.

Forests located in the Zagros Mountains, as part of natural resources have different services. Soil retention is one of the most important services of forests. Population growth in recent decades has led to intensifying the exploitation of forests and uncontrolled destruction of them. Knowledge of ecosystem services as a new approach can help to prevent the destruction of forests. Current study was done by purpose of considering the role of forest ecosystems in soil retention as an ecosystem service and identification of areas with high supply of this service. InVEST software was used to model soil retention (SR), as the capacity of ecosystems to retain soil, by their equations. The results of the study showed that because of increasing the LS and R factors toward the south part of Lorestan province, the maximum potential of soil erosion was seen in the this region (1000 t/ha). The role of forests in soil retention was highlighted because spatial overlay of forest cover with maximum soil erosion areas was seen in the south part of Lorestan province. According to results the maximum of soil retention was allocated to forest cover compared to other land uses.

Fire in natural resources is one of the crises that causes irreparable damage to ecosystems and the environment every year. The purpose of this research is to attempt to study areas of risk aversion and to prepare a map of forest fire hazard area by integrating topographic data and other additional information from a GIS system for Golestan province. In order to carry out this research, firstly, with the removal of the recorded data related to the situation of fires occurred in 2009 and 2010, the domain of all natural resources of Golestan province was carried out. In order to identify areas with high fire potential, static parameters were used to control the burning of forest forests (elevation, slope, slope direction, land use / land cover, evaporation rate). Each of the static parameters is divided into different classes And to each class, using bachelor's knowledge and review of research, ground data and the results of the above studies are weighted from one to ten. In the following, by using overlap of these layers with different weights, areas with high fire potential were identified for the forests of Golestan province. Finally, all weights were summed up, the final weight was obtained and a fire hazard map was prepared. The Arctic GIS9.2 software has been used to generate a fire hazard map. Also, The fire risk index (FRSI), the Normalized Difference Vegetation Index(NDVI), and the zoning map, have a fire hazard in the risk category (very low to high) ). The results showed that most of the fires occurred in hardy and covered with forested areas, as well as in the forested areas with a crown and an intermediate cover, and in the next stage, in the woods and shrubland areas. In calculating the calculation of fire density in altitudes, the results showed that approximately 90 percent of fires occurred in average altitudes between 700 and 1500 meters. Overall, the findings showed that 90 percent of burns occurred continuously in areas With fire hazard, 30% in hazardous areas and 60% in extreme areas, so that its Galikesh, Minoodasht, , Azadshahr has high risk of high fire.

Forest fires and its spread are one of the natural phenomena across the globe. Natural phenomena are always complex and there are many factors affecting them, the phenomenon of fire in forests and its extension is not an exception and occurs annually in different parts of the country. Considering the ecological importance of forest ecosystems and the increasing development of remote sensing technology and geographic information systems, we can identify areas that are most at risk of this phenomenon. This research is a descriptive-analytical method, the collection of information with Use of library resources. The area under study is Kermanshah forests. In this study, topographic parameters (slope, direction and altitude), accessibility (distance from roads, distance from settlements and distance from rivers (tribes and tribes), tribal passage, accident points Growth at the nomadic crossing site, land use, pasture distribution and forest distribution are considered as effective parameters in the fire zoning and using the ahp model, different weight layers have been given. Finally, by applying the weights to the layers, the layers were phased out and the gamma 0.9 was prepared from the layers. According to the weights, criteria and sub-models, the map of areas with a fire hazard in three areas, low Risk, medium risk and high risk areas.

Fire plays a major role in shaping the structure of many terrestrial ecosystems and influences their functionality. With East Azerbaijan Province experiencing one of the most severe droughts over the past few years, the average size and extent of burned area had increased intensively in this region, which is significantly posing threats to the wildland, people, property, and destroying environmental infrastructure. In order to accomplish an in time effective and preventive management and also prior to fire occurrences in forest and rangeland, it was essential to identifying and classifying the susceptible areas and factors influencing on fire occurrences. Generally, the lack of knowledge about regional conditions, which has major influence on the expansion of fire occurrence and causing serious damage to environmental area, infrastructure and property, animal life and plants (Jaiswal et al, 2001 1). Therefore, generating of fire susceptibility maps and analyzing its driving factors may have a great impact on reducing and preventing the deforestation and desertification in environmental area (dong et al, 2005: 169), also it will support and assist the activities of managers and planners in forest management for planning and implantation of an early warning system. In this manner, understanding the spatial distribution of fire ignitions and learning about the key drivers behind this distribution is mostly based on the analysis of historical fire locations. Detailed information about the changes of spatial distribution of fire dangers will provides valuable guidance in the direction of forecasting the trends of environmental dangers for the government and protection agencies. Moreover, it would be very useful as a complementary approaches to fire or wildfire management. Various approaches have been applied to modeling wildfire susceptibility, including different techniques, some authors concluded that machine learning algorithms, like maximum entropy (MaxEnt), performed with high accuracy for modeling wildfire susceptibility. In this regard by using an approach based on a machine learning algorithms called the maximum entropy (MaxEnt) with correct and well-organized data in the context of geographic information system (GIS), it is possible to achieve better and more understanding of the changes in the spatial distribution in fire dangers and affecting factors. In the current study, by using of fire event data from a 9-year period, wide variety of environmental variables and MaxEnt approach, an attempt was made for investigation in fire danger and its influencing factors in forest and rangeland of East Azerbaijan province over a 9-year period. The present study area is East Azerbaijan province in Northwestern Iran, which lie between latitudes 36° to 39° N and longitudes 45° to 48° E and extends over 47,000 km2, with a wide variety of vegetation types, topographical and climatic conditions. The East Azerbaijan province environment is highly diverse in terms of climate, geology and topographic characteristics which lead to different levels of susceptibility to fire. The climate in the study area based on the De Martonne aridity index is semi-arid, average annual precipitation and temperature are 315.2 mm and 10.2 °C, respectively, and elevation ranges from 160 to 4811 m above sea level.
Three phase comprising in the methodology of this research; the first phase applies the several methods such as image processing techniques, GIS analysis, and spatial interpolation methods for producing the dependent and independent datasets. The second phase, data of fire occurrences between 2006 and 2015 associated with a range of environmental and anthropogenic independent variables in three period (2006-2008, 2009-2011 & 2012-2015), jackknife test was used to find out the main driving factors in the spatio-temporal distribution of fire and wildfire. The third and last phase includes analysis of changes in fire danger and its driving factors. Data was collected from various sources including satellite imageries, and metrological data. Fire occurrences and locations were derived from MODIS (Moderate-Resolution Imaging Spectero Radiometer) fire product, historical record of environmental protection agency, and field checking. The Collection 5, Level 3, 8-day MODIS Terra and Aqua active fire product (MOD14A1 & MYD14A1) was used during this study. In the data preparation phase, ASTER Global-DEM with 28.5 meter spatial resolution was used to generate maps of elevation, slope and aspect by using ArcGIS software. Climate maps (max and mean temperature, and precipitation) were created through the interpolation of data gathered by several meteorological stations in the region. A detailed land use/land cover map derived from LANDSAT 8 satellite images, using multi-layer perceptron (MLP) neural network method as a wildly used image classification approach. Then, with kernel density and Euclidean distance functions, anthropogenic variables were created. Eventually, map of Normalized Difference Vegetation Index (NDVI) was derived from MODIS satellite imagery. Maximum Entropy (MaxEnt) is a presence-only machine learning algorithm that iteratively contrasts environmental predictor values at occurrence locations with those of a large background sample taken across the study area. The principle of MaxEnt is to estimate the probability distribution of maximum entropy, which is below a collection of constraints (environmental and anthropogenic conditions), the most spread-out or closest to uniform. It is a sophisticated approach to modeling the probability distribution from the n-dimensional environmental space using occurrence locations data and iteratively evaluates the contrasts between the values of those occurrences and those of a background consisting of the mean occurrence over the entire study area, as sampled from a large number of points. By applying this algorithm, the most uniform distribution will be recognized and selected from several possible distributions, moreover it can specify a per-pixel susceptibility to wildfire occurrence which might be used as an essential tool for environmental hazard management in forest and rangeland. It should be noted that the MaxEnt software was used to analysis the fire susceptibility. The main outputs of this model are; prediction of fire danger in study area, Receiver Operating Characteristic curve as an indicator for accuracy assessment and jackknife test to assess the significance or relatively importance of each independent variable in model result in each period. The process of implementation models for three 3-year period have been done by using the fire occurrences data as the dependent variable and 12 anthropogenic and environmental factor as the independent variables. Assessment of the changes at different areas in terms of fire susceptibility represented upward trend in fire danger, increasing the areas in high-risk zones and extensive changes in the factors influencing the fire occurrence. According to the results most extent of changes about decreasing the areas of zones with very low risk and increasing the area of zones with very high risk and medium risk. Based on the result of accuracy assessment by using Area Under Curve (AUC), which was calculated from Receiver Operating Characteristic (ROC), our analysis indicated the maximum entropy as machine learning algorithm were efficient predictor (AUC =0.91, 0.828, 0.839) for wildfire susceptibility assessment in East Azerbaijan province in three different time period. The machine learning algorithm MaxEnt was successfully applied to analyzing forest fire susceptibility assessment in East Azerbaijan province to demonstration areas with higher fire susceptibility and analyzing its driving factors over the times. Due to the high accuracy of the suggested model (MaxEnt) which has been utilized in the study for 3- period (2006-2008, 2009-2011 and 2012-2014) and also the assessment of the previous studies, this model could considered as a proper approach to evaluating and modeling fire danger and its affecting factors. The results of this study will help to determinate and evaluate fire management objectives. Considering limited financial and human resources to suppress fires in the East Azerbaijan province the concentration on very susceptibility areas could be a way to encounter these challenges. The results can be used for preventive actions and additionally for making more scientific and appropriate decisions. Investigate the changes of fire dangers in forest and rangeland of East Azerbaijan and its upward trend, reveals the requirement for more attention to this issue and also for planning the proper strategies and activities. On the other side increasing in the impact of human factors on fire occurrences in recent years, demand the necessity for cultural proceeding, raise of public awareness as well as taking advantage of the general public potential in the field of preventive activities.

Cover vegetation is much related to climatic conditions. Recognition of seasonal variability the vegetation growth is important to determine the ecosystems response to climate change in seasonal and interannual scales. In this research, to produce the predicted model, we used from climatic factors (precipitation, temperature and relative humidity (maximum, mean, minimum) during 20 years (1987-2006), and these data (141 weather stations) interpolated. So, calculate monthly the maximum value composite of NDVI from NOAA-AVHRR images that same during. Then, have computed Multivariate Least Squares regression from climatic factors (independent variables) and NDVI (dependent variable). The result show, most correlation between climatic factors and NDVI is about of 0.82 and occurring in May, that is highest growth. The lowest correlation is occurring in winters, because is not growing. The annual correlation in calculated model is more than 0.93 with inter the accidental errors. Totally, the calculated NDVI for May and Jun in during 2004-2005 years is close to predicted model, but in winters are distances from together. For the severe drought are lower predicted in 2006 at spring (Jun). In winter the role of temperature is more than precipitation and relative humidity in predicted model, but in earlier of May the role of precipitation and relative humidity is positive and temperature is negative, because is increasing temperature and decrease of precipitation and relative humidity. In autumn, is increasing the role of temperature and decrease the role of precipitation in predicted model.

Land use change and its effect on soils is one of the important factors in decreasing soil quality. Nowadays because of rapid growth of the population، vast areas of the forest lands are changed into agricultural lands but chemical properties of the soils are commonly affected by changing in land usage. Converting the forest lands into agricultural lands is one of the prevalent issues in Iran، especially in north of Iran، nevertheless، relevant studies considering the effects of land use change is very limited and lack of enough and suitable studies due to quantifying of these effects is so significant. Because of that، this study was carried out in order to investigate the impact of changing in usage of forest lands in to the dry farming lands (canola) and paddy lands on some chemical properties of soil such as: pH، organic carbon، total nitrogen، available phosphorous and potassium، electrical conductivity and cation exchanging capacity in Zarin Abad area of Sari، in north of Iran. In order to study the effect of changing in usage of forest lands (Hyrcanian forest) into the dry farm lands (canola) and paddy lands on some chemical properties of soil in Zarin Abad area of Sari، Iran، this research was conducted as factorial design in complete randomize block. samples of soil from each land use were collected in four replications from 2 depths of 0-20 and 20-50 centimeter. Samples were dried and passed from the 2mm sieve، then amount of the organic carbon was determined by the method of wet oxidation. Total nitrogen of the soil was measured by Kejeldal method. To calculate the soil available phosphorous، samples were extracted in two ways: Olson (for measuring available phosphorous in soil samples with pH=7) and Bray-Kortz (for measuring available phosphorous in soil samples with pH=7). then the amount of phosphorous in each extraction was determined with Expectrophotometer device. Available potassium was measured by extraction with Ammonium acetate with pH=7 and Flame photometer device. Cation Exchanging Capacity was also determined by Bawer method. To measure the reaction and the electrical conductivity of the soil’samples، after making saturation mud، the amount of reaction (pH) was measured by pH meter in each sample. The amount of electrical conductivity after extracting from saturation mud was determined in extractions from each sample by Ec meter. Then the analysis of data was done after doing normalization test with Colomogrof-Smirnof test in SPSS program. Comparison of the averages of data was done with Duncan test. Results showed that land use change from forest lands (Hyrcanian forest) into paddy lands، increased soil reaction from 6. 43 to 7. 52 but change to dry farming lands (canola) had no significant effect on soil reaction. Land use change from forest lands into dry farm lands caused decrease in the amount of organic carbon about 46. 5 percent which was about 38 percent in paddy lands. Amount of total nitrogen was decreased in land use change from forest usage into dry farm usage but this decrease was not significant in forest lands change into paddy lands. While land use change caused increase about 4 times in amount of available phosphorus in dry farming lands and increased about 2 times in lands that converted to paddy lands but it had no effect on amount of available potassium and cation exchanging capacity. The lowest amount of electrical conductivity was observed in dry farming lands. Correlation coefficients between parameters showed positive and significant correlations between organic carbon with available potassium and electrical conductivity. There were positive correlations between electrical conductivity with amount of available potassium and soil reaction. Amount of available phosphorus showed a positive relationship with cation exchanging capacity too. Land use change caused changes in some soil chemical properties and each property affected the amount of others so considering the ecological importance of Iran’s northern forests، results of this study showed the necessity of more accuracy and attention to adjust the unfavorable effects of land use change by applying efficient methods of land management in these areas.

Careful assessment of biomass for forest management and understanding the role of forests as carbon sources is very important. Since 50% of forest biomass contains Carbon، estimating the forest biomass in terms of the amount of energy stored in the review of forests and climatic change is highly regarded. The best way for estimating biomass is the developed models which are (based upon) the local collected data. Recently the remote sensing techniques with minimum ground measurements have been played an important role in forest biomass estimation. Lack of the local equations for estimating biomass and ambiguity precision of the global equations، Leads the study toward the development of biomass equations for the forests of Guilan region، in northern Iran. To develop these equations، in a field work، 28 plots (each plot 30*30m) have been selected and the various parameters such as height and diameter of trees have been measured. Non-destructive method is used to estimate the biomass of plots. Then، by using the optical and radar ALOS satellite images، the relationship between remote sensing data and the estimated biomass of plots are determined. The multivariate regression analyses are used to establish the mentioned relationship. The best model based on the highest coefficient (R^2= 0. 731 and the lowest Root Mean Squared Error (RMSE= 13. 88(ton/he)) are determined.