فهرست مطالب منوچهر نمیرانیان

Accurate digital elevation models (DEMs) are crucial for effective forest planning and management. Various methods exist for generating DEM data, with handheld mobile laser scanners being the most efficient and precise approach. The raw point clouds obtained from these scanners require several preprocessing steps, one of which involves separating ground and non-ground points. Errors in this part of the process can lead to the generation of an inaccurate digital model with high uncertainty and errors. Various algorithms, such as voxel-based segmentation, simulation filters, and deep learning-based approaches, have been developed for this purpose. This study evaluates the performance of the OBS algorithm in automatically separating ground points from non-ground points in handheld laser scanner data. The study area comprised five different sections within the Karaj Botanical Garden, covering a total area of 7.2 hectares. These areas contained forest stands characterized by heterogeneous structures and multi-story tree layers. Data were acquired using a handheld GeoSLAM laser scanner. To generate a reliable reference for evaluating the algorithm's results, ground points were manually separated. The performance of the algorithm was evaluated by comparing it with the manually separated ground truth using statistical metrics, including Matthew's correlation coefficient, Kappa coefficient, and Intersection over Union (IoU). The statistical metrics across the five study areas demonstrated the effectiveness of the OBS algorithm in separating ground points from non-ground points, with Matthew's correlation coefficient, Kappa coefficient, and IoU values of 0.895, 0.891, and 0.902, respectively. Additionally, the optimal voxel size for the algorithm was determined to be within the range of 15 to 22 centimeters.We conclude that the OBS algorithm, when configured with optimal input parameters, provides high performance in automatically separating ground points from non-ground points, especially in heterogeneous forested environments. The importance of configuring the optimal input parameters is also highlighted.

Knowing the forest canopy height is essential for evaluating the health and dynamics of forest ecosystems, as well as for monitoring and modeling the carbon cycle and biodiversity. However, measuring canopy height through ground surveys is costly and time-consuming. Since 2018, the ICESat-2 satellite, equipped with the ATLAS laser sensor, has enabled the direct measurement of tree height. Although ICESat-2 is specifically designed to estimate ice height, it also provides significant data on vegetation height on the Earth's surface. This study aims to investigate the ability of the ATLAS sensor to accurately estimate forest canopy height in northern Iran. For this purpose, the vegetation height data from the ATLAS sensor (ATL08) was evaluated in the Kheyroud experimental forest. To validate the accuracy of the estimated forest canopy height by ATLAS, the forest height data obtained from the satellite were compared with the maximum tree height measured in 121 plots collocated with LiDAR footprints. The estimated forest canopy height by ATLAS and the maximum measured height of trees were compared using a t-test. The RMSE, rRMSE, and R2 values were 0.87 m, 2.7%, and 0.98, respectively, indicating the high accuracy of the ATLAS sensor in forest canopy height estimation. The results of the t-test showed that the mean difference between the measured maximum height of trees in the plots and the corresponding values extracted from ICESat-2 satellite data is not statistically significant (P > 0.05). This study demonstrates that the satellite estimates forest canopy height with very good accuracy in the forests of northern Iran, with a slight overestimation in areas with low-height trees.

The beech tree has the ability to produce shoots and form a coppice stands under specific natural climatic and environmental conditions or under unusual circumstances caused by human interference. The current research aims to compare the structural characteristics of coppice and standard stands of beech in the Hyrcanian forests in the Chetan area in Nowshahr. The diameter at breast height of all trees was measured using the full calipering method to determine the stocking volume. Half-hectare sample plots were established using the distance-azimuth method to study the spatial structure. The standing and log stocking volumes were also determined. According to the results, the number of live and dead trees in the coppice stand was 174 and 9.7 per hectare, respectively, and their volume was 146.2 and 3.6 m³/ha, respectively. In the standard stand, the number of live and dead beech individuals was 145 and 11 per hectare, respectively, while their volume was 147.5 and 12.1 m³/ha, respectively. About 55% of the standing dead trees in the coppice stand and 35% of the standing dead trees and 42% of the fallen dead trees in the standard stand were primarily in the first decay degree. The highest number of individuals in a beech coppice group included four, which is 17%. Groups of five individuals and two individuals also accounted for 16.9% and 16.5%, respectively. Spatial structure indices of beech coppice, including the Pielou segregation, Clark and Evans, Mingling, DBH differentiation, DBH dominance, and uniform angle, indicate species continuity, clustering, severe dominance of beech species, moderate differences, small size dominance, and clump distribution, respectively. Traditional uses of forests have influenced the structural characteristics of beech stands. Therefore, it is suggested that these and other similar stands be protected as a forest reserve to ensure the development of these habitats towards a more favorable state and the stability of the landscape in these areas.

Forest conversion to agriculture, Forest Understory cultivation and grazing in the forest are considered as the most important factors in the destruction of Zagros forests and in this regard, local and governmental stakeholders have different and contradictory views together. The purpose of this study was to gain a perspective of stakeholders regarding agricultural and livestock activities in Almaneh allotment forests in Sarvabad city. In the Almaneh`s forest village, agricultural activities whether farming or horticultural are carried out either inside the forest (in the form of understory farming, or deforestation and conversion to agriculture and orchard) or at the edge of the forest which in any case affects the forest. In this village livestock also has a direct impact on the forest and it can always be described as an integral part of the forest.

The statistical society of this study includes the people of Almaneh village and some experts of the Natural Resources and Agricultural offices of Kurdistan province. The main instrument of the study is a questionnaire and In total, 115 local and state stakeholders views using a Likert scale on Forest conversion to agriculture, Forest Understory cultivation and grazing in the forest were investigated. Kruskal-Wallis and Mann-Whitney tests were used for data analysis using SPSS software.

According to the results, local stakeholders are not aware of their activities in deforestation and agricultural experts agree with them. But natural resources experts have opposite view. In other words, local and state practitioners have a different perspective on many aspects of the activity and the conflict between local practitioners and government experts, especially natural resource experts, is clearly visible.

So, from a stakeholders perspective, a common item is selected as the selected stakeholders item in all three activities, which shows that these activities are due to economic problems and the lack of local people's income.

Understanding the structure of a forest is crucial for detecting forest dynamics, describing ecosystem stability, and designing effective management plans and protection and restoration measures. This study primarily aims to investigate the spatial pattern and structural characteristics of beech forests in the optimal developmental stage using variable area sample plots. In compartment 327 of the Grozban district of Kheyrood forest, eleven variable area sample plots with geometric shapes, exhibiting characteristics of the optimal developmental stage, were selected. The location, diameter, and height of all trees larger than 7.5 cm were measured in each sample plot. The results revealed that the largest contribution of trees among the investigated sample plots was related to mid-diameter and low-diameter classes. The Clark and Evans index and uniform angle results indicated a regular distribution of trees in all studied sample plots. The mingling index averaged 0.19 across all sample plots, suggesting low mixing and a minimal tendency of beech trees to blend with other species. The average diameter and height differentiation index were calculated as 0.31 and 0.30, respectively, indicating an average difference between neighboring trees. Overall, the use of indices based on the nearest neighbor with variable area sample plots and geometric shapes demonstrated that these indices effectively quantify the structural characteristics of forest stands in the optimal developmental stage. Consequently, it is recommended to conduct similar research in other developmental stages.

The aim of this research was to identify the optimal habitat areas of ash species (Fraxinus excelsior L.) in Kheyrud Nowshahr forest, which covers an area of approximately 8,224 hectares. We recorded the geographical coordinates of 1004 ash individuals using a GPS device, along with environmental variables such as climate variables and primary and secondary topographic predictors extracted from DEM. We used the predictors with the least degree of correlation as input in the Generalized Linear Model, Generalized Additive Model, Random Forest, and maxent models. We prepared and analyzed the variables in ArcGIS, SAGA, and R software. To compare the performance of the four models, we considered the input variables in all models to be the same. We evaluated the models using kappa coefficient (K), Area Under Curve (AUC), and True Skill Statistic (TSS) measures. The RF model had the highest K (0.973), AUC (0.997), and TSS (0.973), indicating the best performance among the models. According to the RF model, the most important variables were valley depth, profile curvature, slope, and topographic position index. These variables indicate the areas with rich soil, sufficient moisture, proper drainage (non-stagnant water), slope less than 45%, and sufficient light (suitable for the vegetative stage). We identified the most suitable areas in the Baharbon, Chelir, and Menia-Sang districts due to optimal conditions for these effective variables.

This study investigates the capability of ALOS-2 full polarimetric radar data for estimating woody aboveground biomass (AGB) in a mixed Hyrcanian forest. For collecting ground data, the low slope areas selected and measured for a total of 127 square sample plots with an area of 900-m2. Tree height and Diameter at Breast Height (DBH) were measured for each tree with DBH of larger than 7.5-cm and the volume of each tree was calculated using these two characteristics. We used volume to biomass equation (multiplying the volume by the wood-critical density) to calculate AGB in each sample plot. The average of observed AGB was 318.04-tons per hectare for the study area. To process ALOS-2 data, the polarization channels were calibrated and multi-looked. We used a Box-Car filter with window size of 5×5 pixels to reduce the noise. Finally, the extracted features were geometrically corrected. They are Backscattering intensity components in the form of gamma naught, Freeman-Durden target decompositions components and variables derived from mathematical relationships betw

Calculating the amount of canopy ecohydrological parameters is the main step in rainfall partitioning modeling, and by calculating the amount of ecohydrological parameters, it is possible to predict the amount of throughfall, stemflow, and rainfall interception per rain storm. Therefore, this study aimed to evaluate the canopy echohydrological parameters of three oriental beech (Fagus orientalis Lipsky) stands and three chestnut-leaved oak (Quercus castaneifolia C. A. Mey.) located in the Hyrcanian vegetation region in the annual-based time scale. The ecohydrological parameters studied included canopy saturation point, canopy water storage capacity, free throughfall coefficient, and the ratio of mean evaporation rate from canopy to the mean rainfall intensity. On average, the canopy saturation point was 5.37 mm in the chestnut-leaved oak and 6.29 mm in the oriental beech. Also, on average, the canopy water storage capacity of the oriental beech (2.08 mm) was higher than that of the chestnut-leaved oak (1.15 mm). The mean rainfall magnitudes in the chestnut-leaved oak and oriental beech stands were 20.0 and 16.2 mm, respectively. The average relative interception in the oriental beech (36.9%) was slightly higher than the chestnut-leaved oak (33.5%). The average free throughfall coefficient and the ratio of mean evaporation rate from canopy to the mean rainfall intensity were calculated to be 0.50 and 0.25 for the oriental beech and 0.71 and 0.36 for the chestnut-leaved oak. By knowing the values of canopy ecohydrological parameters, thinning and pruning silvicultural treatments can be applied in stands with high water storage capacity and low free throughfall coefficient to reduce rainfall interception.

Galazani (pollarding) is a traditional silvopastoral system, which comprises disbranching and defoliation of oak trees to provide livestock fodder. This affects forest stand structure, tree architecture and growth. This study aimed to compare diameter increment between households’ forests (conventional territories) in different diameter classes and analyzing the effect of Galazani on both diameter increment and its trends. To obtain the goals, 16 Lebanon oak (Quercus libani Oliv.) trees in the Armardeh forest in the Kurdistan Province, western Iran, distributed in five family territories (as an indicator of how local owners treat their own forest) from different diameters were cut. The width of annual rings of the cross-sectional discs, which were taken from the trees, were measured via a LINTAB table equipped by a binocular with a precision of 0.01 mm. Results showed that mean annual increment (1.78 mm) was not significantly different amongst various diameters nor amongst different owners. Mean comparisons of diameter increment in the years after Galazani indicated that the increment in the first year after Galazani (1.34 mm) was significantly less than the second (2.11 mm), third (2.76 mm) and fourth (3.19 mm) years. The trend of diameter increment enhances the tree stability and supports forest structure in order to improve the tree growth. Furthermore, it is necessary to both extend Galazani rotation to at least five years and to limit its maximum allowable diameter. Based on our findings, practicing Galazani in large diameter trees (30 to 35 cm) significantly reduces diameter increment.

The socioeconomic situation in the Zagros Forests has provided conditions for the overexploitation in this region, which has raised concerns about the intensified decline of ecosystem services in these forests. In this study, soil and water protection services (as the most important regulatory functions of the Zagros Forests) were economically estimated in the Sarvabad basin of Kurdistan province. Then, the trend of change in their values was examined in two scenarios of 1) reaching all the forests of the basin with 30-50% canopy (first scenario) and 2) conversion of forests to sparse forests with 5% canopy (second scenario). The results showed that the average annual value for soil protection, i.e. preventing land loss and sediment control is 27002.82 IRR per ha, while the average annual value for water protection is 790000 IRR per ha. We also estimated the changes in the total annual value of soil protection function by assuming the first scenario, which increased by 34.83%. In case of the second scenario, it decreased by 37.3%. Moreover, the first scenario was able to add 29.96% to the value of the water protection function of these forests, whereas 33.54% of the value of the water protection function decreased for the second scenario. Decrease in the value of ecosystem services due to the tree canopy reduction in this study emphasizes the importance of protection and restoration of the Zagros Forests ecosystem to maintain and provide valuable ecosystem services.

The difficulties in the measurement of rainfall interception in forests confirm the necessity of presenting models. The widely used models for estimating rainfall interception are physical-based models, among which the Sparse Gash is the most commonly used. We evaluated the Sparse Gash model for estimating the rainfall interception of five forest stands (two chestnut-leaved oak stands, two oriental beech stands, and one velvet maple stand) in the Hyrcanian region. In each stand, the gross rainfall and throughfall were measured using 5 and 20 rainfall collectors, respectively, and rainfall interception was calculated by subtracting the throughfall from gross rainfall. To evaluate the performance of the model, we used statistical metrics: Error percentage (Error), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the Model Efficiency coefficient (CE). Based on the Pearson correlation coefficient, the correlation between the values estimated by the model and the observed values was statistically significant at a 95% confidence interval. In all forests, the values of the CE were higher than 0.5, indicating the appropriate efficiency of the model. Based on the Error, the model showed good capability in estimating the rainfall interception of four forest stands (i.e., oriental beech in Lajim, chestnut-leaved oak in Kohmiyan and Sari, and velvet maple in Sari Error metric were found to be -10.3%, +12.7%, +10.8%, and +15.4%, respectively). Studying the performance of physically-based models in forests with different species and different allometric, climatic and rainfall characteristics completes the information gap about the efficiency of models to estimate rainfall interception.

Climate change studies and simulations conducted by GCM models show that patterns of temperature and rainfall will change over the next 50 to 100 years can affect patterns of forest stands increment. Growth and yield models do not have the ability to simulation forest stands under the effect of climate change. Due to lack of efficient models, JABOWA-4 as a hybrid model that can evaluate the population dynamic under climate change scenarios, and can explore the long-term aspects of forest composition, was applied in this study. In order to uncertainty of climate change trend in future, three greenhouse emission scenarios were formulated to explore future global developments with special emphasis on greenhouse gases. After comparison of modeled and real values of diameter growth, R2 and RMSE were calculated to be 0.98 and 1.734 (cm2), respectively, indicating a good correlation between two mentioned values. The response of species to climate change were assessed separately for Beech and Maple with 31 and 25 percent reduction in DBH increment, respectively, wich showed a negative response to climate change. Oak projected to increase slightly and after that decreased by17 percent under climate change and Hornbeam showed positive response to climate change but less than real values. The results of this study indicated that gap models are good at providing forest yield prediction affected by climate change.

Estimating the biomass values in forests stands through remote sensing is important. It has been reported that the major reasons of uncertainty are the lack of concurrency in satellite data and field information as well as the use of global allometric equations for estimating the weight of biomass of forest trees inside the country. Minimizing the above problems and the investigation of data performance in developing appropriate model for estimating the forest biomass in the Bankoll region of Karazan District of Sirvan County in Ilam province using Sentinel-1 satellite data in 27th of June, 2017 was the main goal of this study. Average size of the trees crown in 53 rectangular plots related to the coppice growth form with dimensions of 30×30 mwhich during 23 may 2017 to 10 June 2017 through applying DGPS by RTK method have been implemented on the ground were entered in the process of estimation the value of biomass. The average harvested field biomass was 10.63 Mg ha-1. After extraction of radar features, those features which had the greatest correlation with the values of biomass were selected using genetic algorithm by two models including K-Nearest Neighbor (K-NN) regression and Support-Vector Regression (SVR), then the most appropriate combination was identified and the biomass values were modelled. Models were validated using 26 test plots. Correlation of features obtained from radar data and the value of biomass indicated that features of VH، Mean VV، Mean VV GLCM (Correlation) and Mean VH GLCM (Dissimilarity) had the greatest sensitivity towards the value of biomass. Using regression models indicated that SVR model (Relative RMSE of 0.08) was more precise compared with K-NN regression (relative RMSE of 0.10). The best combination in the use of K-NN regression model with a relative RMSE of almost 0.99 Mg ha-1 (equal to 10%) and the coefficient of determination (R2) of 0.22 and the best combination when using SVR model was a relative RMSE of 0.87 Mg ha-1 (equal to 8%) and the R2 of 0.14. The results indicated that the final models, obtained from the optimal features extracted from radar data in the wavelength of C band and used parametric and non-parametric regressional methods in this research, were not abled to improve the saturated effect in data for estimation of biomass in the studied forests and it was not resulted in presenting an estimating model with an acceptable accuracy.

Understanding the ecological niche of the different species is essential in many ecological issues.  Ecological niches of species are one of the important factors in the tree species distribution pattern and for all species, it can be detected by examining distribution of species distribution. Ecological nest models often help to understand more ecosystems. These models are applicable in predicting ecosystem stability and sustainability ratios and ecosystems.

In order to determine the selective pressure of different species, the indicators of the equilibrium level of selected nests, the dominant level of selected nests and the crisis level of selected nests were used and 41.5 hectares of Khirud research and educational forest were fully surveyed (100%). Then, characteristics such as diameter equal to the chest of the trees were measured and using selective nesting indices, the selected pressure and nesting levels of beech, oak, hornbeam and alder species were measured.

The values of the selective pressure were measured for the species on the Fagus orientalis 66.419, Quercus persica 3. 313, Carpinus orientalis 261. 28, Alnus 36. 962 and tilia begonifolia 9. 39 respectively. The final results showed that Carpinus orientalis wasat a Dominates niche level, the Fagus orientalis and Alnus was in the balance niche level and the Quercus persica was in intermediate between balance and critical level and also tilia begonifolia was in the critical niche levels.

The Carpinus species were at the dominant level of selective pressure, the Tilla species were at the equilibrium level and the Quercus species were at the equilibrium level of the crisis nest. The results of this study showed that selective strain quantification is an important factor in determining the current status of endangered species.

Local people are always dependent on cutting down and pollarding of Zagros forests trees to provide their livelihoods needs such as house heating, cooking, supply of livestock forage and building materials. The stakeholders also have many conflicts in terms of forest utilization, which is the main cause of many irregularities in the forest management. The present study was conducted to investigate the views of local and governmental forest stakeholders on the cutting down and pollarding of forest trees in the Almaneh village, Sarvabad city of Kurdistan province. The main tool of the research was a questionnaire whose validity was evaluated based on the opinions of specialists and its reliability surveyed through Cronbachchr('39')s coefficient. In total, the views of 115 local and governmental stakeholders were studied using a Likert scale. All data were submitted to SPSS to analyze using Kruskal wallis and Mann whitney tests. According to the results, local stakeholders stated that they currently forest trees are not severely cut down and pollarded as in the past (Average stakeholder views for cutting and pollarding were 2.3 and 4.1, respectively), and their utilization is limited to the collection of dead trees that do not damage the forest (Average stakeholder views were 4.03) and oppose the governmentchr('39')s inhibition. Natural resources specialists, despite the confirmation of the decline in these utilities in recent years (Average stakeholder views for cutting and pollarding were 3.14 and 3.9, respectively), have considered the destruction of forests, and the bilateral participation is necessary in this regard. In total, our results showed explicit signs of conflict between the views of local and governmental stakeholders to each other. In spite of the conflict of views, in general, stakeholders announced the positive impact of entering the gas into the village and changing the source of livestock forage (Average stakeholder views for cutting and pollarding were 3.79 and 4.1, respectively).

In recent years, new methods have been developed for analyzing spatial pattern of trees, and for verifying the spatial pattern, they need to complete map of spatial location of these trees. The use of these methods depends on study scale in a way that changes in study scale cause changes in spatial pattern. In this regard, present study aims to determine the optimum area of sample plots to quantify the spatial pattern of Juniperus Excelsa M. Beib. In southern facing slopes of Alborz mountains.

A plot with area of six hectares was selected and spatial pattern of trees were evaluated by using g(r) function. In next step, area of plot decreased to five, four, three, two, and one hectare and spatial pattern of trees were determined by using g(r) function and were compared with six hectare plot.

The results of this function indicates regular spatial pattern in trees distances to four meter, cluster pattern at distances of six to ten meter, and random pattern shows in other distances. The results of comparing figures of g(r) functions in different area showed that the overall trend of this functions almost constant up to three hectares. Hence, in this study the appropriate area is achieved three hectares.

It should be noted that in structure studies to determine the best area of plot could reduce time and costs while increasing the precision of the study.

This research aimed at determining the economic planting interval, planting pattern, and rotation age for high-yield black poplar in the West Azerbaijan Province, Iran. For this purpose, a decision support system called the bio-economic model was employed. The model simulates the dynamics of stand’s bio-economic variables over time. The statistical population consists of poplar farmers and timber merchants in Orumiyeh and Naghadeh counties where black poplar plantations were highly concentrated. Biological data were collected using full calipering inventory (diameter) and systematic random sampling (height and wet wood density). The economic data (stumpage price and costs) were obtained through a field survey based on a semi-structured interview. Multiple regression analysis and OLS estimator were used to estimate the biological (e.g., growth and yield) and economic (e.g., planting cost) sub-models. By integrating sub-models within an Excel spreadsheet, a bio-economic model was constructed for black poplar plantations. Finally, land expectation value (Faustmann formula) was simulated over a wide range of planting intervals, planting patterns and rotation age. As a result, the economic planting interval/pattern and rotation age of average-fertility plantations appeared to be square, 2.5´2.5 meter and 12 years while the common standards are rectangular, 3´1 meter and 8 years, respectively. The results revealed that implementing economically optimal planting and harvest standards increase the per-hectare merchantable volume production, quadratic mean diameter and land expectation value by 56, 46 and 143 percent, respectively. Further research will be required to model and to optimize the growth response of poplar plantations to management activities (e.g., ploughing, fertilization, irrigation, vegetation control, and thinning).

Orthphoto mosaic, and digital elevation models (DEMs) that created from UAV imagery can be used to delineate tree crowns. The goal of this research is to compare two segmentation techniques in the estimation of crown diameter. In this regard, two successful flights were carried out in two different seasons (leaf-off and leaf-on). Then we generated accurate CHM through a photogrammetric workflow using DTM and DSM. We used invert watershed (IWS) and multiresolution segmentation (MRS) to detect tree crowns on CHM and orthophoto mosaic, respectively. To compare the estimates of mean crown diameter from UAV images with actual values, 95 trees were measured. The results of comparing the estimated and field measured values showed that all two algorithms effectively delineate tree crowns. The results of linear regression showed there is a high agreement between estimated and measured values, which were (R2=0.88) for MRS and (R2=0.92) for IWS. The best result was obtained using IWS techniques (RMSE= 7.02 % and MAE = 5.97 %). T-test results showed that there are no significant differences between the field measurement and IWS estimated values. Although the t-test result showed there are significant differences between the means of MRS estimated and measured crown diameters, but based on RMSE (8.74 %) and MAE (8.11 %) of the MRS technique, the error of crown diameter estimation was small and therefore acceptable. Finally, the results showed that this methodology, as an accurate and low-cost process, could be used to estimate mean tree crown diameter.

Height Measurement of all trees in a forest or forest stand is almost impractical. For this reason, today different researchers prefer to estimate the tree height by the relationship between the DBH and height of trees.

In this study, to fitting different statistical models in different stages of forest development, after field inspection, three one hectare sample plots located in different development stages in Beech forest of Kheirud forest, Natural Resources Faculty in Tehran University were selected. Then the DBH of 251 trees have been measured randomly and 80 percent of trees were used for modeling and 20 percent were used to validate 22 regression models. In order to determine the best model for each of development stages, R2, E, MBE and NMPE criteria were used.

The results of this study indicated the suitability of Rational Function and Weibull models in initial stage, Modified Exponential in optimal stage and Gompertz and Richard models in Decay stages.

Based on the results of this study it can be concluded that different regression models doesn’t have the same ability in fitting the data of DBH and height of different forest stands and the same model can’t be used to fit the data of DBH and height of different forest stands.

The main pre-request of the forest management and planning program is the availability of quantitative and qualitative data from forest structure. Therefore, the forest inventory plays a vital role in the estimation of the current status and future planning. In this study, spatial pattern of trees in Gorazbon section of Kheyroud forest in northern Iran was simulated to compare the random systematic sampling and complete random systematic sampling method based on the full calipering method. By using the Arc GIS software, the spatial pattern of forest trees was simulated. Buffer function was used to calculate the random systematic sampling and complete random systematic sampling method based on the full calipering method. In order to compare random systematic sampling with full calipering single-sample, a t-test was used. The results showed that there was no significant difference between random systematic sampling and full calipering method to estimate the average diameter of Alnus, Fagus orientalis, and Tilia begonifolia. However, there was a significant difference between two methods in the estimation of average diameter of Carpinus orientalis and Quercus persica. The results of T-test revealed that there is no significant difference between Alnus and Tilia begonifolia but significant difference was observed between the trees of the Fagus orientalis, Carpinus orientalis, and Quercus persica. In addition, paired t-test was used to compare the random systematic sampling and complete random systematic sampling method. Results showed that there is no significant difference between random systematic sampling and complete random systematic sampling method.

Juniperus excelsa forests are thinner and have distribution in areas with severe living conditions andcompletely rocky beds. Due to inventories of these forests are hard, costly, and time-consuming,therefore, in this study, the most suitable sampling method was investigated to determine the density andpercentage of canopy cover in Juniper forests. For this purpose, an area of 15.9 ha of forests in Alborzprovince made an inventory with a full callipering method. The results of full callipering show thatdensity is 61 trees per hectare, and the percentage of canopy is 20.51 in this stand. In the next stage, sitestudy was made an inventory by using seven distance sampling methods (nearest individual method,nearest neighbor method, second nearest neighbor, random pairs method, T-square method, and pointcentered quarter method), density and percentage of canopy were calculated for each method andcompared to Full callipering method. Results show that random pairs method estimated density 58.3 treesper hectare (the difference is -3.79 percent) and T-square method estimated density 62.97 trees perhectare (the difference is +3.91 percent) has less difference in estimating trees density. The random pairsmethod estimated canopy cover 23.4 percent (the difference is 14.09 percent), and is the lowest error toestimate the percentage of the canopy in these forests. According to the specific condition of Juniperforests, using a random pairs method is suggested because it can be easily measured, has less error andsaving time and money.

Today, the important of growth models as an important management tool and factors affecting them is clear. So, in this study, factors affecting the growth models were examined. Data from 256 permanent sample plots for the years 2003 and 2012 of Kheyroud Forest was used. First, the relationship between topographic factors including slope, direction and altitude with site productivity for beech was obtained using an empirical regression model. Then, the factors affecting the individual trees diameter increment were investigated using regression relations. Also, in order to better understand the effect of these factors, tree species were separated in four species group as beech, hornbeam, chestnut-leaved oak and other species. In order to evaluate the model, three statistics including RMSE, MBE and performance coefficients were used. The results showed that the relationship between the site productivity index and three factors of direction, gradient and elevation is sinusoidal, almost decreasing, at first increased and then decreased. Also, the behavior of the studied indicators in relation to tree species is different. For instance, in the diameter increment model of beech species, all of the indices, except for site productivity and Shannon-Wiener index had a significant effect and the use of these indicators for beech species reduces the error and bias and increases the efficiency of the model. The mortality model was also presented with a high percentage prediction. In general, the present study showed that the relationship between growth models and various indices has a lot of complexity and more research is needed.

In this research, capability of Landsat 8 OLI was studied for estimation of aboveground biomass in pure stands of the common hornbeam (Carpinus betulus L.) in Hyrcanian forests of Iran. In order to obtain in situ aboveground biomass, diameters at breast height (DBH) of all trees greater than 7.5 cm were measured in 55 sample plots. Then, in situ aboveground biomass was calculated using local volume table and specific gravity in each plot. About 70 percentages of in situ measurements (40 sample plots) were used for modeling aboveground biomass based on Landsat 8 OLI data using different methods of stepwise regression, backward regression, artificial neural network, k-nearest neighbor and random forest. Validation of the models was done using 30 percentages of in situ measurements (15 sample plots). Based on the Pearson correlation coefficient, near-infrared band showed the highest correlation with aboveground biomass (0.52). Backward regression with adjusted R2 of 0.295 and RMSE% of 28.63%, and artificial neural network with RMSE% of 23.45% showed the best performance among parametric and non-parametric methods, respectively. Based on the results, Landsat 8 OLI data seems suitable for aboveground biomass estimation in pure stands of the common hornbeam only over large areas and small scale. Although more investigations are required to verify and generalize the results to the entire Hyrcanian forests of Iran.

The use of statistical experimental models is common practical methods among forest resource managers. Regression analysis is also a statistical method that can be used to estimate the volume. This method has limitations and requires assumptions such as normality, homogeneity of variance and non-linear relationship. The use of new techniques such as artificial neural networks can deal with these limitations. This study aims at comparing the performance of Artificial Neural Networks (ANN) and regression analysis to estimate the total volume of logs. For this purpose, 367 trees out of marked trees in research and educational forest of kheyroud were selected and DBH, diameter at stump height, stump height, total tree height, species, tree situation, minimum median diameter and topographic factors such as aspect and elevation were measured with high accuracy. Multilayer perceptron (MLP) and multivariate regression were developed to estimate the total volume of logging trees. The results indicated that the Neural Network was more accurate about 40% in estimating the total volume of logging trees than the regression method. Comparing evaluation criteria showed RMSE value 1.411 for ANN modeling and 3.49 for regression analysis. The difference between estimated and actual total volume was 6.5% to regression analysis and 1.7% to Neural Network. According to the results, the amount of difference was less for ANN model than regression model.

Monitoring forest structure, to understand many issues in ecology and forest management is essential. In general, the term "structure" emphasizes the combination of tree communities in terms of specific characteristics. Monitoring forest structure is essential for understanding many issues in ecology and forest management. Today, many indicators have been developed for assessing the position and biodiversity of the trees, which simplifies the structural analysis of the forest. The use of these indices in constant sample units facilitates population dynamics studies over time and makes it possible to monitor the diversity of the location, dimensions, diversity of trees and height of the trees. Due to the smallness of these indicators and the possibility of comparing a mass at two different times, these indicators are a useful tool for achieving sustainable forest management. Combination indexes, uniform angles, diameters and altitudes are among the most important indices in the analysis of forest spatial structure in static studies. These indicators are preferable to other methods because of their simplicity in calculations and balancing accuracy. In this research, using a randomized random method, a rectangular grid of 200 * 150 * meters was used to identify the Gorazbon of Kheyroud forest in the city of Noshahr. Then, in order to study the structure of the forest species (beech, oak, hornbeam, alder, apple, lambs, lambs, almonds, and durum wheat) over a period of ten years, the uniform angle index, Ming-Ling blending, close The largest neighbor and the index of differentiation of diameter and height of trees were used. According to The results, Average indexes uniform angle index, mixing Ming Ling, nearest neighbor and the diameter and height dominate the index, in the first period and the end of the monitoring period was calculated) 0/598 and 0/525, 0/582 and 5/645 and 5/35, 0/762 and 0/720, 0/5521 and 0/591 respectively This represents a cluster random distribution pattern, an optimal mix of diversity and high density and the average dispute between the diameter and height of neighboring trees then the reference tree. In order to compare species diversity, location, and size, paired t-test was used. Paired t-test results showed that there is no significant difference between these indices before and after the period of monitoring (ie, the ten-year period). Also, the results of t-pair test for each species were proved, that there is a significant difference between the indices of differentiation of hornbeam tree before and after the observation. But there was no significant difference between the other species before and after the observation. This is due to the dominance of hornbeam trees in neighboring trees