While most recent investigation in satellite- based remotely sensed data has concentrated upon the biophysical characteristics of overstory vegetation for large area, little attention has been given to the reflectance contribution of their associated understory, versus overstory plantation reflectance to the recorded pixel value. In this research, shrubs and herbs were considered as consistent backgrounds which have an inverse effect, in contrast to plantation overstory, to the recorded pixel value in terms of their surfaceexposure to satellite sensors. Given the fact that planted tree crown closure is correlated with their height and diameter at breast height (DBH) in the early stages of the plantation, it is expected that a relationship exists between tree canopy closure, height, DBH and their associated reflectance values. The proposed concept was tested in a case study for a Jack Pine (pinus banksina) plantation using Landsat Thematic Mapper (T. M.). The crown width height, and DBH of planted trees were measured in an area of 30m X 30m, for every 2-year age interval from 1 to 21 years. Other understory natural regeneration within a 2m radius was recorded. Crown closure, mean height, and DBH of each plot (with shrub and herb understory of more than 60%) were plotted against their associated Digital Numbers (DN(s)) for 6 T. M. bands (1, 2, 3, 4, 5 and 7). The visible region of the spectrum (bands 1, 2 and 3) showed a narrow range of reflectance and was not suitable for this purpose. Band 4 revealed a greater range of DN(s) than bands 1, 2 and 3. A strong inverse linear relationship between DN(s) and their associated canopy closure, height, and DBH were found in band 5 as r2 = 0.863, 0.941, 0.873 respectively. Band 7 showed a stronger relationship with canopy closure (r2 = 0. 81) than did the other T. M. bands (except band 5). Overall, the results of this study have shown the importance of T. M. band 5 for estimating DBH and the height of plantations based on the contrast between reflectance of the overstory and understory.

Quantifying the mechanical properties of roots is one of the most important issues in stabilizing slopes and modeling soil reinforcement. The aim of this study was to estimate the mechanical properties of hornbeam trees in three stem diameter classes include small, medium, and large trees in Patom district of Kheyrud forest. For this purpose, number of five trees in small (7. 5-32. 5 cm), medium (32. 5-57. 5 cm) and large (57. 5-82. 5 cm) diameter classes were selected and roots on both up and down sides (slope of 20-30 percent) of the trees were collected, then placed between two jaws of the Instron machine. Tensile strength test and tensile force were performed. The results showed that there is a positive power relationship between root diameter and tensile force. In all stem diameter classes at both sides of trees, tensile strength decreases by increasing root diameter based on negative power function. The results of covariance analysis showed that tensile force and tensile strength were significantly different among three stem diameter classes. Tensile force was higher in medium and small trees at up and down sides, respectively. While, in large trees tensile force in downside was more than upside. In medium trees, tensile strength were significantly higher in upside and downside (F=12. 9, P<0. 05) than small and large trees. Covariate factor (root diameter) was significant in all cases. The results of this study showed that stem diameter of trees and up and down sides of the trees affect the tensile force and tensile strength of hornbeam trees and it is possible to change the amount of tensile strength with age. Therefore, it is necessary to investigate changes in roots mechanical properties in different ages of trees in order to modeling the slope stability.

Parrotia persica is one of the few species growing naturally in the northern forests of Iran. This specie is reproduced through asexual reproduction by coppice (shoot). This research was done to study the effects of DBH on sprouting and to select the best diameter classes regarding to asexual reproduction in experimental and educational forests of Kheyrud. Nitty nine 0.1 ha circular samples plots were randomly established. Trees were classified into three diameter classes, class1: 10-30 cm, class 2: 30-60 cm and class 3: more than 60 cm. Regeneration was separated into four classes with diameter 2-4, 4-6, 6-8, 8-10 cm. To compare the mean number of coppice in diameter classes, Analysis of Variance and Duncan tests were used with 95 percent confidence level. The results indicated that Parrotia persica trees in class 2 (30-60) had the highest number of coppices (10.8).The average number of coppices in diameter class1,2 and 3 and are 6.6, 10.8 and 6.5 per base, respectively. Healthy coppices with more diameters are better than other coppices. The number of coppices with diameter 2-4 cm is higher than other classes, and class 2 (30-60) has the maximum number of coppices. The results of ANOVA showed significant difference in the average number of coppices with diameters 2-4, 4-6, 6-8, 8-10 cm. The results of this study indicated that diameters at breast height affect the asexual reproduction of Parrotia persica. To establish asexual reproduction of this species, the diameter class 30-60 cm is more important.

Background and Objectives: Estimating forest tree structural attributes such as height and diameter at breast height (DBH) is crucial for understanding the structure and management of forest resources. One important method for estimating these parameters is the individual tree detection (ITD) method using appropriate remote sensing data, such as airborne LiDAR data. However, it should be noted that different ITD methods have various limitations and capabilities and react differently to changes in forest tree species and the vertical structure of the canopy.Methodology: This study presents a hybrid individual tree detection method that combines raster-based and point-based methods in a multi-scale framework to identify single trees from LiDAR data. In this method, tree crown scale levels are obtained from morphological filters in the canopy height model (CHM). Segmentation is then performed using a multi-scale method, and the results are merged. To better separate adjacent and understory trees, the point cloud inside the segments is analyzed using the probability density function, and tree crown segments are modified. After detecting single trees, DBH and height parameters were estimated using ground control data and extracted features from LiDAR data with machine learning algorithms, including random forest (RF), support vector machine (SVM), and cubist (CB), in the form of 10-fold nested cross-validation (10-fold NCV). The Boruta feature selection algorithm was used to identify the most important metrics based on the LiDAR point cloud, which played an effective role in improving the performance of machine learning algorithms. Due to limited access to LiDAR and ground data from Iran’s forests, this study uses the NEWFOR single tree detection benchmark dataset, collected from forests of the Alpine region with a combination of different tree species and vertical canopy structures.Results: Although understory trees cannot be extracted with the same accuracy as overstory trees, the results of this study showed that, on average, the developed multi-scale individual tree detection (MSITD) method detected 89% of the tree crowns in the highest height layer and the highest number of small overstory trees with a detection rate of 48% in the lowest height layer (2-5 meters). The analysis of the machine learning algorithms’ results in estimating forest structural attributes showed that, despite slight differences in performance, the SVM algorithm performed better than the RF and CB algorithms in estimating both height and DBH attributes. For the height attribute, the mean values of RMSE, rRMSE, and R2 in the SVM algorithm were 1.75 m, 9%, and 0.85, respectively. For the DBH attribute, the values obtained for RMSE, rRMSE, and R2 were 4.74 cm, 19%, and 0.78, respectively.Conclusion: The evaluation of the results showed that the methods presented in this study for identifying single trees and estimating forest tree structural attributes have high potential for practical applications. 

The distribution of diameter classes is the most important structural characteristics of forest stands. Determining the fitting pattern of diameter classes in forests shows that, the overall status of these forests from the destruction process and ecological sequence points of view at different times. The aim of this study was to evaluate of frequency distributions of trees DBH in different development stages of natural stands in forests of Guilan. In order to study the statistical distributions of trees dbh, In order to determine the mixed stands characteristics in untouched forests for applying in silvicultural interventions, a reserve area in region in watershed number 9 (shafarod) from west of the Hyrcanian forests, northern Iran was selected. three sample plots of one hectare, were selected in three development stages. In three of development stages initial, optimal and decay were measured 419, 259 and 161 trees respectively. Beta, gamma, normal, lognormal, exponential, logistic and Johnson’s SB probability distribution patterns were fitted to diameter classes. Characteristics of distribution patterns were estimated using maximum likelihood method. Kolmogorov-Smirnov, Anderson-Darling and Chi-square tests were used for comparing of actual probability and probability which derived from functions. The results showed that the proper distribution function is different in three stages,So that in the initial stage, Johnson’s SB, in optimal stage, the Weibull, and in the decay stage, Weibol and Johnson’s SB have a good fit. Therefore, these distribution functions can be used for those who want to simulate changes of forests.

Background and objectives: Efficient and high-quality information about the current and future state of the forest is needed for sustainable management and basic planning of forest resources. Zagros forests, as one of the most important vegetation areas of Iran, have a very important effect on water supply, soil conservation, climate adjustment and economic and social balance in the whole country, hence, the sustainable protection and management of these forest ecosystems The main concern of researchers and managers in this area has become vegetation. The dominant species of these forests is Iranian oak (Quercus brantii Lindl). According to geographical and environmental conditions, this species has various habitats in the vegetation zone of the middle Zagros. Considering the noble position of the Iranian oak species in the forests of Zagros, the importance of developing more researches regarding this species is essential. The characteristics of tree diameter and height are the most important components needed in forest statistics. These variables are one of the main variables for measuring the appearance characteristics of forest trees and are used in cases such as determining the volume and drawing the height curve. Considering that measuring the height of all forest trees is a long and expensive operation, hence the use of diameter and height models to estimate the height of trees has been developed. The purpose of this research is to investigate the linear and non-linear diameter-height models of Iranian oak species (Q. brantii Lindl) in the high forests of the Middle Zagros in order to find the answer to the question of whether it is possible to estimate the height of Iranian oak high forest trees as There is a function of the diameter of the chest in this vegetative zone or not.Methodology: This research was conducted in Sefidkoh protected area of Lorestan. The dominant tree cover of this area is made of oak, like other areas of Zagros, but other plants and trees such as Cratagus persica pojark, Amygdalus sp, Astragalus sp, etc. can be mentioned in it. To carry out this research, by conducting numerous forest tours and getting to know the forests of the region, a stand with an area of approximately five hectares, which had a high forest vegetation structure, was selected. In the selected forest stand, the characteristics of DBH and total height of all Iranian oak trees whose DBH was more than 12.5 cm were counted as 100%. In total, 642 Iranian oak trees were measured in DBH and height. Linear and non-linear models were used to fit the data of DBH and height of trees, which include various models of exponential, power, density-product, growth, sigmoid and other functions. In this research, 80% of the data were used in the modeling process and 20% were used for evaluation, as well as for fitting the data and estimating the indicators of each of the models from the Curve Expert Professional software, which is a software Comprehensive software was used to fit the curves. In the modeling process, diameter data were used as independent variables and height data were used as dependent variables. In the upcoming research, to verify the accuracy of the obtained models, the RMSE, MAEand Bias in absolute and relative terms, as well as the R2 and the AIC was calculated as validation indices.Results: Based on the descriptive statistics of Iranian oak trees, the average, minimum and maximum DBH was 42.42, 12.5 and 150 cm, respectively, and the height was 6.3, 1.2 and 17 meters, respectively. Based on R2 values, the used models explained 62 to 86% of the total changes in tree height. The results of tree height-diameter modeling showed that Gompertz, MMF and Richard models have the highest explanatory coefficient (0.86, 0.86, 0.86), respectively, and the lowest standard error (307. 1, 1/307, 1/307) and AIC information criterion were (276/04, 277/13, 277/03). The results of the criteria used to validate the used models showed that the Gompertz, MMF and Richard models have RMSE of 22.22, 22.20 and 22.20%, respectively, as well as MAE respectively. 16.69, 16.74 and 16.79 percent were better able to estimate the characteristics of the height of trees. According to the mentioned results, it was found that Gompertz, MMF, and Richard models have a higher ability to estimate the characteristic height of Iranian oak trees compared to other models.Conclusion: Overall, the results of this research showed that linear and non-linear models have the ability to estimate the height of Iranian oak high forest trees in the growing region of the middle Zagros, and among these models, three non-linear models are Gompertz, MMF and Richard based on evaluation criteria. The performance was more accurate. Therefore, these models can be used in the forest areas of the middle Zagros vegetation zone, which have the same structure and habitat conditions as the studied area. It is suggested to use the generalized models of height and diameter in future researches.

Background and objectives: Accurate in situ measurement of DBH is easy and cost-effective but, height measurement is labor-intensive, time-consuming and expensive. Understanding its height–diameter relationship is essential for developing growth, biomass production and carbon storage prediction models to be applied in the current forest management projects. The existence of a strong relationship between the diameter and the height of trees is considered as a useful index in forest management and it can be described with mathematical models. Considering that non-linear models are flexible, interpretable and strong, therefore some of the most important models were used in this study. Materials and methods: In this research, 21 widely used candidate nonlinear and one simple linear models were fitted to tree height and diameter at breast height (DBH) data for Populus euphratica Oliv. within a 100 square meter plots at Shoosh area of Khuzestan province. Data from 1163 trees were used and split randomly into two sets: 80 % of the data were used to estimate model parameters (model fitting), and the remaining data (20 %) were reserved for model validation. All model performances were evaluated and compared by means of model performance criteria such as t-statistics of model parameters, root mean square error percentage (RMSE%), mean absolute error percentage (MAE%), mean bias error percentage (ME%), Akaike’s information criterion (AIC) and Bayesian information criterion (BIC).Results: The parameters of 8 models were not significant at a level of 5%. RMSE, MAE, Bias, AIC and BIC values for M12 model were obtained: 8.98%, 6.78%, -0.0010%, 1451.82 and 1469.73, respectively. The same values were obtained for M21 model: 9.15%, 6.94%, 0.0005%, 1476.95 and 1494.86 respectively. The predicted and actual height values in these two models were not significantly different at a level of 5%. The results of the paired sample t test showed that the nonlinear models M21 and M12 have predicted the height of Populus euophratica trees with appropriate accuracy. Two models (Prodan1 with the name of M12) and (Prodan2 with the name of M21) were selected as the best models based on the ranking of all model performance evaluation criteria in fit and validity data.Conclusion: The majority of two-parameter models and some three-parameter models showed a significant fit with the data. However, in terms of all performance evaluation criteria, two three-parameter models were chosen as the best models. According to the results of this study and the wide range of non-linear two and three parameter models, mixed models that include one or two covariates in the modeling in addition to the main variables, more research is needed in larger geographical areas, wider sites and stands with different structures are done.

Estimating urban trees growth, especially tree height is very important in urban landscape management. The aim of the study was to predict of tree height base on tree diameter. To achieve this goal, 921 trees from five species were measured in five areas of Mashhad city in 2014. The evaluated trees were ash tree (Fraxinus species), plane tree (Platanus hybrida), white mulberry (Morus alba), ailanthus tree (Ailanthus altissima) and false acacia tree (Robinia pseudoacacia). Regression analysis of tree height versus tree diameter revealed several models (linear, logarithmic, exponential and power) that could be used for estimating the tree height of these five species. The logarithmic, power and exponential functions provided a good fit to the data on tree height against tree diameter for ash tree (R2=0.9 and RMSE=0.74), ailanthus tree (R2=0.92 and RMSE=0.44) and plane tree (R2=0.72 and RMSE=0.72), respectively.

Measurements of production and utilization of key range plant species are of utmost important tools for making range management decisions specially for stocking rate determination. A study was conducted to examine the relationships of production and utilization of Agropyron cristatumand Stipa barbata, as key grasses in Chaharbagh region of Golestan province, with some dimensional parameters. For this purpose, plants height, basal diameter and canopy diameter and their dry weights were measured. Primarily, correlation matrices and Pearson correlation coefficient were used to assess the relationships of these three dimensional variables with production. The three variables were then evaluated for predicting production by using best subset and stepwise regression approaches. Utilization was assessed based on percentage of height removed in relation to percentage weight removed. Results showed that basal and canopy diameters could usefully predict the production of the two grasses. Finally, because of subjectivity of canopy diameter measurements and its weak role in explaining production variations, just basal diameter was considered in models, having linear relationship with production and the coefficient of determinations were calculated to be 72.4 and 71 for A. cristatum and S. barbata, respectively. Therefore, dimension analysis is an appropriate approach to estimate the production and utilization of range key grasses.

The objective of this research was to study of tree species diversity based on different (dbh) classes in the Norway maple sites in Shafarood forest of Guilan. In this regards 0.5 ha lozenge sample plots has been selected (34 plots) with considering presence of Norway maple in the study forest. In each plot, inutility geographic characteristics (i.e, slope, aspect and elevation) were documented, then diameter at breast height of trees that had 10£dbh class were measured. Also, type of woody species identified and documented. Shannon-Wiener’s and Simpson’s diversity indices were used for evaluating of woody species diversity, also, evenness and richness indices were calculated. In addition, diversity was calculated in four dbh class (10-35, 35-50, 55-80, 85-120). Results showed that Shannon-Wiener’ s index and Mc Arthur’ s N1 in 35-50 dbh class (cm) had the highest value while Simpson’ s index and Hill’s N2 in 10-30 dbh class had been shown the highest value but both of Shannon-Wiener' s and Simpson’ s indices in 85- 120 dbh class had the least value. With increasing dbh classes, initially diversity of tree species is ascended then are being decreased.