• International conference on construction engineering and project management
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• 2022.06a
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• pp.839-846
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• 2022

Traditionally, the construction industry has shown low labor productivity and productivity growth. To improve labor productivity, it must first be accurately measured. The existing method uses work-sampling techniques through observation of workers' activities at certain time intervals on site. However, a disadvantage of this method is that the results may differ depending on the observer's judgment and may be inaccurate in the case of a large number of missed scenarios. Therefore, this study proposes a model to automate labor productivity measurement by monitoring workers' actions using a deep learning-based pose estimation method. The results are expected to contribute to productivity improvement on construction sites.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.209-216
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• 2023

This study aimed to use national forest inventory data to develop a forest productivity index and yield prediction model of a Tilia amurensis stand. The site index displaying the forest productivity of the Tilia amurensis stand was developed as a Schumacher model, and the site index classification curve was generated from the model results; its distribution growth in Korea ranged from 8-16. The growth model using age as an independent variable for breast height and height diameter estimation was derived from the Chapman-Richards and Weibull model. The Fitness Indices of the estimation models were 0.32 and 0.11, respectively, which were generally low values, but the estimation-equation residuals were evenly distributed around 0, so we judged that there would be no issue in applying the equation. The stand basal area and site index of the Tilia amurensis stand had the greatest effect on the stand-volume change. These two factors were used to derive the Tilia amurensis stand yield model, and the model's determination coefficient was approximately 94%. After verifying the residual normality of the equation and autocorrelation of the growth factors in the yield model, no particular problems were observed. Finally, the growth and yield models of the Tilia amurensis stand were used to produce the makeshift stand yield table. According to this table, when the Tilia amurensis stand is 70 years old, the estimated stand-volume per hectare would be approximately 208 m³ . It is expected that these study results will be helpful for decision-making of Tilia amurensis stands management, which have high value as a forest resource for honey and timber.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.155-158
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• 2008

Site index is the essential tool for forest management to estimate the productivity of forest land Generally, site index equation is developed and used by relationship between stand age and dominant tree heights. However, there is a limit to use the site index equation in the application of variable ages, environmental influence, and estimation of site index for unstocked land. Therefore, it was attempted to develop a new site index equations based on various environmental factors including site and topographical variables. This study was conducted to develop regional site index equations based on the relationship between site index and soil factors for Pinus densiflora. Environmental factors that obtained from GIS application, were selected by stepwise-regression. Site index Equation was estimated by multiple regression from selected factors. Four environmental factors were selected in the final site index equations by stepwise regression. It was observed that coefficients of determination for site index equations were ranged from 0.34 which seem to be relatively low but good enough for estimation of forest stand productivity. The site index equations developed in this study were also verified to be useful by three evaluation statistics such as model's estimation bias, model's precision and mean square error type of measure.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.5
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• pp.429-434
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• 2007

This study was conducted to estimate site productivity of Quercus acutissima and Quercus mongolica by four forest climatic zones. We used site environmental variables (28 geographical and pedological factors) and site index as a site productivity indicator from nation-wide 23,315 stands. Based on multiple regression analysis between site index and major environmental variables, the best-fit multivaliate models were made by each species and forest climatic zone. Most of site index prediction models by species were regressed with seven to eight factors, including altitude, relief, soil depth, and soil moisture etc. For those models, three evaluation statistics such as mean difference, standard deviation of difference, and standard error of difference were applied to the test data set for the validation of the results. According to the evaluation statistics, it was found that the models by climatic zones and species fitted well to the test data set with relatively low bias and variation. Also having above middle of site index range, total area of productive sites for the two Quercus spp. estimated by those models would be about 6% of total forest area. Northern temperate forest zone and central temperate forest zone had more productive area than southern temperate forest zone and warm temperate forest zone. As a result, it was concluded that the regressive prediction with site environmental variables by climatic zones and species had enough estimation capability of forest site productivity.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1140-1147
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• 2009

Productivity measurement of construction machinery is a significant issue faced by many contractors especially those involved in earthwork projects. Traditionally, equipment production rate has been estimated using data available in manufacturers' catalogues, results of previous construction projects, or personal experience and assessments of the site personnel. Actual production rates obtained after the completion of a project demonstrate the fact that most of these methods fail to provide accurate results and as a direct consequence, may lead to unrealistic project cost estimations prepared by the contractors. What makes this more critical is that in most cases, inadequate cost estimations lead the entire project to exceed the initial budget or fall behind the schedule. In this paper, a linear regression method to estimate bulldozer productivity is introduced. This method has been developed using SPSS-16 software package. The presented method is used to estimate the productivity of Komatsu D-155A1 series which is commonly used in many earthmoving operations in Iran. The data required for the numerical analysis has been collected from actual site observation and productivity measurement of 60 pieces of D-155A1 series currently being used in several earthmoving projects in Iran. Comparative analysis of the output data of the presented regression method and the existing productivity tables provided by the manufacturer shows that when compared to the actual productivity data collected on the jobsite, a significant increase in accuracy and a remarkable reduction of data variance can be achieved by using the presented regression method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.97-106
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• 2006

Site index is an essential tool to estimate forest productivity. Generally, a site index equation is developed and used from the relationship between stand age and dominant tree heights. However, there is a limit to the use of the site index equation in the application of variable ages, environmental influence, and estimation of site index for the unstocked forest. Therefore, it has been attempted to develop a new site index equation based on various environmental factors including site, climate, and topographical variables. This study was conducted to develop a site index equation based on the relationship between site index and environmental factors for the species of Pinus koraiensis in Yangpyung-Gun, Gyunggi Province. The influence of climatic factors (temperature and solar irradiation ratio), topographical factors (elevation, slope, ratio of slope to valley and aspect) and soil profiles (soil depth by layer and soil consistency) on site index were evaluated by multiple regression analysis. Five environmental factors were selected in the final site index equation for Pinus koraiensis. The site index equation developed in this study was also verified by three evaluation statistics: model's estimation bias, model's precision, and mean square error of measurement. Based on the site index equation, the number of productive areas for Pinus koraiensis were estimated by applying GIS technique to digitized forest maps. In addition, the distribution of productive areas was compared with the areas of current distribution of Pinus koraiensis. It is expected that the results obtained in this study could provide valuable information about the amount and distribution of productive areas for Pinus koraiensis reforestation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.36-44
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• 2010

In order to rehabilitate forest sites damaged by wildfire via natural or artificial restoration, it is important to determine right tree species, which can acclimate to biogeoclimatic environment at the sites. The objectives of this study were to develop site index equation of different tree species for estimating forest productivity and to provide information on species selection for post-wildfire restoration. Site index equation was developed based on environmental information from wildfire damaged areas in Gangneung, Goseong, Donghae, and Samcheok, where were located in east coastal areas of South Korea. Despite the small numbers (4~5) of environmental variables used for the development of the site index equations, statistical analysis (e.g. mean difference, standard deviation of difference, and standard error of difference) showed relatively low bias and variation, suggesting that those equations can provide relatively high capability of estimation and practical applicability with high effectiveness. The small numbers of the variables enabled the model to be applied in a wide range of usages including determination of appropriate tree species for post-wildfire restoration. The estimation of forest site productivity showed the possibility of large distribution in east coastal region as the best site for Korean ash (Fraxinus rhynchophylla) and original oak (Quercus variabilis) that can be used for firebreak in the region. These results imply that damages by forest fire can be reduced significantly by replacing existing pure coniferous forests in the area with ones dominated by broad-leaved deciduous stands, which can play an important role as fire break and/or prevent a transition from surface fire to crown fire.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.395-404
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• 2012

This study was conducted to develop site index equations and to estimate productive areas for major coniferous species in Korea such as Pinus densiflora Sieb. et. Zucc, Pinus densiflora for. erect, Larix leptolepis and Pinus koraiensis using environmental factors. Using the large data set from both a digital forest site map and a climatic map, a total of 43 environmental factors including 15 climatic variables were regressed on site index by tree species to develop site index equations. Six environmental factors by species were selected as independent variables in the final site index equations. The result showed that the coefficients of determination for site index equations by species were ranged from 0.36 to 0.56, which seem to be relatively low but good enough for the estimation of forest stand productivity. The site index equations developed in this study were also verified by three evaluation statistics such as the estimation bias of model, precision of model, and mean square error of measurement. According to the evaluation statistics, it was found that the site index equations by species fitted well to the test data sets with relatively low bias and variation. As a result, it was concluded that the site index equations by species were well capable of estimating site quality. Based on the site index equations, the productive areas by species for all forest areas were estimated by applying GIS technique to the digital forest site map and climate map. In addition, the distribution of productive areas by species was illustrated by using GIS technique.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.437-445
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• 2013

This study was conducted to develop site index equations and to estimate productive areas of Quercus acutissima by ecoprovince in Korea using environmental factors. Using the large data set from both a digital forest site map and a climatic map, a total of 48 environmental factors including 19 climatic variables were regressed on site index to develop site index equations. Four to six environmental factors for Quercus acutissima by ecoprovince were selected as independent variables in the final site index equations. The result showed that the coefficients of determination for site index equations were ranged from 0.30 to 0.41, which seem to be relatively low but good enough for the estimation of forest stand productivity. The site index equations developed in this study were also verified by three evaluation statistics such as the estimation bias of model, precision of model, and mean square error of measurement. According to the evaluation statistics, it was found that the site index equations fitted well to the test data sets with relatively low bias and variation. As a result, it was concluded that the site index equations were well capable of estimating site quality. Based on the site index equations of Quercus acutissima by ecoprovince, the productive areas by ecoprovince were estimated by applying GIS technique to the digital forest site map and climate map. In addition, the distribution of productive areas by ecoprovince was illustrated by using GIS technique.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.283-284
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• 2012

High-rise building construction has been increasing for the recent years and the construction process has become more complicated. This suggests a need for precise planning based on reliable data to prevent cost overruns and delays. However, the process planning is implemented based mainly on the experience of engineers that can result in critical damage in cost and time. Accurate productivity estimation and unit cost analysis must be considered important matter to prevent such disaster. This study estimates productivity and unit cost of curtain wall operations in high-rise building construction by simulation techniques and statistical methodologies. This study suggests a decision making methodology for the site personnel that enables to compare various combinations of productivity and unit cost based on reliable data that has been collected in actual construction sites. It is expected that this study contributes to the following research of developing an optimized construction performance assembling model for the site personnel.