Required data for research or decision making for lots of environmental sciences have been provided by field INVENTORY which consume a great deal of the budget. As time and financial resources for INVENTORY are limited, having more information about the effective factors that influences INVENTORY is necessary. Also, new instruments in FOREST INVENTORY such as GPS or laser meter needs to be studied. In this research, required time for field INVENTORY with respect to weather and field conditions were assessed using continues correlation time study method. Required time for each part of field operation was recorded based on 150 10R plots with 300×400 sampling design. Total pure and gross time for recording plots data was 57 and 86 minutes, respectively. The results of two way ANCOVA showed a significant effect of weather and field condition on required time for measuring plots data and crossing distances between plots. Required time for measuring plot data was increased 33 and 43 percent while weather and field condition getting worse, respectively. On the other hand, undesirable weather and field condition increased time for crossing distances between plots 20% and 47% respectively. A regression model for estimating required time of INVENTORY based on distance (d) and slope (s) between plots were developed. The results of ANCOVA also revealed that the effect of number of trees on required time for measuring data was significant but the effect of slope of plots was not significant.

Landscape diversity is considered as the variety of land cover classes in a landscape and it is usually calculated on land cover maps of entire landscape. However, in this study it is aimed to present a new procedure, that is, the use of field-based national FOREST inventories (NFIs) to estimate two diversity indices: Shannon’ s diversity and inverse Simpson. Specifically, it is also intended to investigate how well a combination estimator can improve the precision of the estimates. The permanent square cluster plots produced more precise (smaller variance) estimate of the indices than temporary ones. In addition, estimated variance of the indices using combination estimator was smaller than both permanent and temporary square cluster plots. The applied procedure in this study is very simple where classes of land cover are usually determined and recorded by field surveyor. The main advantages of using field-based inventories are that there is no need for land cover/ use maps or images of the landscape. In addition, quality of the landscape diversity assessment through remotely-sensed data is still highly dependent on the availability and quality of field data. As long as historical datasets from FOREST inventories is available in many countries it is thus possible to do trend analysis in landscape diversity over time.

Improving participation in voluntary activities in Iran is important because increasing productivity among young people, given the country's young population, contributes to community sustainability. Therefore, a better understanding of volunteer motivation in Iranian youth is needed. The Volunteer Functions INVENTORY (VFI) for assessing volunteer motivations has good psychometric properties and is adapted to several languages, but no validated Iranian translation yet exists. The purpose of this study was to investigate the psychometric Characteristics of voluntary functions INVENTORY in members of Iranian Red Crescent Society. Sample size was 595 members of Youth Organization of Iranian Red Crescent Society from 31 provinces and 175 cities of Iran that were selected by multi-stage cluster sampling method and responded to voluntary functions INVENTORY. Data were collected using a demographic sample and voluntary functions INVENTORY (VFI). Confirmatory factor analysis using principal components method was used for data analysis. The results of the present study showed that the voluntary functions INVENTORY had validity and reliability. Also, the factor structure showed that 29 items and 6 factors well assess people's attitudes to volunteering, and the structure of this INVENTORY was well-fitted and confirmed all goodness of fit models. The present study provides the use of the Iranian translation of the Voluntary Functions INVENTORY (6 scales and 29 items) to assess volunteer motivation among young Iranian volunteers.

The Big Five INVENTORY (BFI) is one of the most widely used personality questionnaires, but very few studies have been conducted on its psychometric properties in Iranian population. This study was carried out with the aim of studying the psychometric properties of the BFI questionnaire. For this purpose, 390 university students in Tehran (210 girls and 180 boys) with an age range of 18 to 56 years (M = 27.52; SD = 8.79) were selected using the convenience sampling method and completed BFI and NEO-FFI questionnaires. Cronbach's alpha, multitrait-multimethod matrix, and confirmatory factor analysis were used to estimate the psychometric properties of the questionnaire. The result of the confirmatory factor analysis showed that 15 of the 44 items did not have a strong factor loading (higher than 0.40) on the corresponding factors and were therefore removed from the questionnaire. The fit indices showed that the Persian version of 29 questions (BFI-29) with 5 factors has a good fit with the data. The reliability analysis also showed that the range of Cronbach's alpha coefficients of the factors is from 0.70 to 0.79. The lowest Cronbach's alpha coefficient was related to agreeableness factor and the highest was related to conscientiousness. The findings from the multitrait-multimethod matrix showed that the BFI-29 questionnaire has good convergent and divergent validity with the NEO-FFI questionnaire. In general, based on the results of the present study, it can be said that the BFI-29 questionnaire has desirable psychometric properties and whenever a short tool for personality measurement is needed, this questionnaire can be used.

Geographic Information System (GIS) is one of the most important tools to prepare FOREST management plan and, in general, as a tool for management, sustainable logging and future planning based on the derived statistical data from FORESTed regions. The purpose of this study was spatial simulation of trees in FOREST to have in hand an example of an uneven aged FOREST (simulated FOREST). By means of the simulated FOREST, it is possible to test different statistical methods and various management activities before they are carried out in real world. The study area, Gorazbon, is a district of Kheyrud research-educational FOREST, with 1001 hectares area located in East of Nowshahr city. The INVENTORY was implemented using systematic random sampling.Afterwards, trees were randomly distributed within the compartments of this district, using the results of full callipering INVENTORY with Arc GIS 9.3 software and FOREST was simulated. In this stage, the INVENTORY process was implemented in simulated FOREST similar to the INVENTORY of real FOREST. These results were compared with the results of the ground INVENTORY, and nostatistically significant difference was found in any of repetitions. Consequently, it can infer that the simulated FOREST is remarkably applied to the FOREST INVENTORY implementations. Furthermore, it is a functional tool to provide FOREST management plans of Kheyrud FOREST.To say in other words, this makes possible to test different methods of FOREST INVENTORY and also type and dimensions of plot and INVENTORY net unquestionably.

Sampling methods have a theoretical basis and should be operational in different FORESTs; therefore selecting an appropriate sampling method is effective for accurate estimation of FOREST characteristics. The purpose of this study was to estimate the stand density (number per hectare) in Arasbaran FOREST using a variety of the plotless density estimators of the nearest neighbors sampling method includes the Closest Individual, the Nearest Neighbor, the Second Nearest Neighbor, the Compound, the Shared Point and the Continues Nearest Neighbor due to introducing the most suitable estimator for FORESTs. For this purpose, all number of trees was counted per hectare (as control). Then, distances between random sampling points and five closest nearest neighboring trees were measured in a systematic randomized network. The density estimators were calculated in each method. The calculated value of the actual density was compared to estimators' values by the one sample t-test (p< 0. 05) method in the R software and based on the value of accuracy criterion. Finally, the tree spatial distribution pattern was calculated by Johnson-Zimmer and Hopkins indices. The results showed that the difference between all estimators value was significant (p≤ 0. 05) compared to the actual density (339. 5 N. ha1), except the Morisita and Cottam estimators in Closest Individual method, Byth and Ripley and Cottam & Curtis 1 estimators in Nearest Neighbor method and 4th and 5th neighbors estimators in Continuous Nearest Neighbor method. The results of the spatial distribution pattern showed the random distribution of trees in the study area. The performance evaluation of these estimators for other quantitative characteristics is recommended in the Arasbaran FOREST stands.