• Computers and Concrete
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• v.19 no.3
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• pp.275-282
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• 2017

The aim of this study is to build Machine Learning models to evaluate the effect of blast furnace slag (BFS) and waste tire rubber powder (WTRP) on the compressive strength of cement mortars. In order to develop these models, 12 different mixes with 288 specimens of the 2, 7, 28, and 90 days compressive strength experimental results of cement mortars containing BFS, WTRP and BFS+WTRP were used in training and testing by Random Forest, Ada Boost, SVM and Bayes classifier machine learning models, which implement standard cement tests. The machine learning models were trained with 288 data that acquired from experimental results. The models had four input parameters that cover the amount of Portland cement, BFS, WTRP and sample ages. Furthermore, it had one output parameter which is compressive strength of cement mortars. Experimental observations from compressive strength tests were compared with predictions of machine learning methods. In order to do predictive experimentation, we exploit R programming language and corresponding packages. During experimentation on the dataset, Random Forest, Ada Boost and SVM models have produced notable good outputs with higher coefficients of determination of R2, RMS and MAPE. Among the machine learning algorithms, Ada Boost presented the best R2, RMS and MAPE values, which are 0.9831, 5.2425 and 0.1105, respectively. As a result, in the model, the testing results indicated that experimental data can be estimated to a notable close extent by the model.

• Journal of Ecology and Environment
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• v.41 no.1
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• pp.1-8
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• 2017

Background: Though the biomass of floral vegetation in understory plant communities in a forested ecosystem only accounts for less than 1% of the total biomass of a forest, they contain most of the floral resources of a forest. The diversity of understory honey plants determines visitation rate of pollinators such as honey bee (Apis mellifera) as they provide rich food resources. Since the flower visitation and foraging activity of pollinators lead to the provision of pollination service, it also means the enhancement of plant-pollinator relationship. Therefore, an appropriate management scheme for understory vegetation is essential in order to conserve pollinator population that is decreasing due to habitat destruction and disease infection. This research examined the diversity of understory honey plant and studied how it is related to environmental variables such as (1) canopy density, (2) horizontal heterogeneity of canopy surface height, (3) slope gradient, and (4) distance from roads. Vegetation survey data of 39 plots of mixed forests in Chuncheon, Korea, were used, and possible management practices for understory vegetation were suggested. Results: This study found that 113 species among 141 species of honey plant of the forests were classified as understory vegetation. Also, the understory honey plant diversity is significantly positively correlated with distance from the nearest road and horizontal heterogeneity of canopy surface height and negatively correlated with canopy density. Conclusions: The diversity of understory honey plant vegetation is correlated to vegetation structure and human impact. In order to enhance the diversity of understory honey plant, management of density and height of canopy is necessary. This study suggests that improved diversity of canopy cover through thinning of overstory vegetation can increase the diversity of understory honey plant species.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.3
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• pp.39-45
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• 2010

Quantification of carbon absorption and understanding the human induced land use changes (LUC) forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by LUC through remote sensing technology. The Landsat imagery four time periods was classified with the hybrid classification method in order to quantify carbon absorption by LUC. Thereafter, for estimating the amount of carbon absorption, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated with the crown width extracted from digital forest cover type map. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the IPCC guideline, was used to convert the stand biomass into the amount of carbon absorption. Total carbon absorption has been modeled by taking areal estimates of LUC of four time periods and carbon factors for land use type and standing biomass. Results of this study, through LUC suggests that over a period of construction, 7.10 % of forest and 9.43 % of barren were converted into urban. In the conversion process, there has been a loss of 6.66 t/ha/y (7.94 %) of carbon absorption from the study area.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.315-328
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• 2011

Landsat data incorporated with additional bands-normalized difference vegetation index (NDVI) and band ratios were used to assess the extent and rate of deforestation in the Gunung Mutis Nature Reserve (GMNR), a mountainous tropical forest in Eastern of Indonesia. Hybrid classification was chosen as the classification approach. In this approach, the unsupervised classification-iterative self-organizing data analysis (ISODATA) was used to create signature files and training data set. A statistical separability measurement-transformed divergence (TD) was used to identify the combination of bands that showed the highest distinction between the land cover classes in training data set. Supervised classification-maximum likelihood classification (MLC) was performed using selected bands and the training data set. Post-classification smoothing and accuracy assessment were applied to classified image. Post-classification comparison was used to assess the extent of deforestation, of which the rate of deforestation was calculated by the formula suggested by Food Agriculture Organization (FAO). The results of two periods of deforestation assessment showed that the extent of deforestation during 1989-1999 was 720.72 ha, 0.80% of annual rate of deforestation, and its extent of deforestation during 1999-2009 was 1,059.12 ha, 1.31% of annual rate of deforestation. Such results are important for the GMNR authority to establish strategies, plans and actions for combating deforestation.

• Journal of Korean Society of Forest Science
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• v.22 no.1
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• pp.63-65
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• 1974

In this study, it is aimed to elucidate the relationship between the distribution of barren land in mountainous area and the geological and topographical characteristics of barren land in south Korea. To do this, the Land Use Classification Maps for mountainous areas (scale:1/50,000), compiled by the Roseources Survey Office of Mountainous and Forest Areas, Geological Maps of Korea (scale: 1/50,000), and Map of Geology of Korea (scale: 1,000,000), compiled by the construction Research Institute of Korea were used. The following conclusions have been obtained from this study. 1) Areas of strata that are most liable to dilapidation are found in such order of the broadest to broad as region of granite, granite-gneiss, and the specific stratum called the Kyongsang Stratum (named after the provinces) of the northern and southern Kyongsang Provinces comprising sandstones, gravelstones, crumblestones, and other stones similar to these species. These rocky hills occupy vast areas in size, so to speak, they are estimated to cover roughly 57% of the total barren and naked areas in the country. 2) The average size in area of barren and nated land, as one piece of land, 32 hectares of granite region, 15 hectares of granite-gneiss region and little less than 13 hectares of Kyongsang strata region were calculated.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.653-664
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• 2010

The land surface reflectance is a key parameter influencing the climate near the surface. Therefore, it must be determined with sufficient accuracy for climate change research. In particular, the characteristics of the bidirectional reflectance distribution function (BRDF) when using earth observation system (EOS) are important for normalizing the reflected solar radiation from the earth's surface. Also, wide swath satellites like SPOT/VGT (VEGETATION) permit sufficient angular sampling, but high resolution satellites are impossible to obtain sufficient angular sampling over a pixel during short period because of their narrow swath scanning. This gives a difficulty to BRDF model based reflectance normalization of high resolution satellites. The principal objective of the study is to add BRDF modeling of high resolution satellites and to supply insufficient angular sampling through identifying BRDF components from SPOT/VGT. This study is performed as the preliminary data for apply to high-resolution satellite. The study provides surface parameters by eliminating BRD effect when calculated biophysical index of plant by BRDF model. We use semi-empirical BRDF model to identify the BRD components. This study uses SPOT/VGT satellite data acquired in the S1 (daily) data. Modeled reflectance values show a good agreement with measured reflectance values from SPOT satellite. This study analyzes BRD effect components by using the NDVI(Normalized Difference Vegetation Index) and the angle components such as solar zenith angle, satellite zenith angle and relative azimuth angle. Geometric scattering kernel mainly depends on the azimuth angle variation and volumetric scattering kernel is less dependent on the azimuth angle variation. Also, forest from land cover shows the wider distribution of value than cropland, overall tendency is similar. Forest shows relatively larger value of geometric term ($K_1{\cdot}f_1$) than cropland, When performed comparison between cropland and forest. Angle and NDVI value are closely related.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.385-398
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• 2018

Although the importance of developing reliable and systematic GHG inventory has increased, the GIS/RS-based national scale LULUCF (Land Use, Land-Use Change and Forestry) sector analysis is insufficient in the context of the Paris Agreement. In this study, the change in $CO_2$ storage of forest land due to land use change is estimated using two GIS/RS methodologies, Sampling and Wall-to-Wall methods, from 2000 to 2010. Particularly, various imagery with sampling data and land cover maps are used for Sampling and Wall-to-Wall methods, respectively. This land use matrix of these methodologies and the national cadastral statistics are classified by six land-use categories (Forest land, Cropland, Grassland, Wetlands, Settlements, and Other land). The difference of area between the result of Sampling methods and the cadastral statistics decreases as the sample plot distance decreases. However, the difference is not significant under a 2 km sample plot. In the 2000s, the Wall-to-Wall method showed similar results to sampling under a 2 km distance except for the Settlement category. With the Wall-to-Wall method, $CO_2$ storage is higher than that of the Sampling method. Accordingly, the Wall-to-Wall method would be more advantageous than the Sampling method in the presence of sufficient spatial data for GHG inventory assessment. These results can contribute to establish an annual report system of national greenhouse gas inventory in the LULUCF sector.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.405-417
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• 2019

We analyzed the profitability of Korea's forestry by evaluating stumpage prices of the main economic tree species. Stumpage prices are evaluated with a market value formula, subtracting logging and transporting costs from market prices of logs. If trees are sold at the current cutting age, the stumpage price of larch is about 4.5 million KRW per hectare and that of Korean pine is about 3.7 million KRW per hectare. The stumpage prices do not cover reforestation cost, which is about 6.1 million KRW per hectare. If government subsidies did not support the cost of reforestation and silviculture, there would be no profits at all. The cost of forestry is very high in terms of planting and silviculture. In the future, the prices of logs are not predicted to rise and the wages for labor are not predicted to fall. Without reforming the current forestry regime, Korean forestry is, thus, not sustainable. Therefore, low-cost forestry efforts like natural regeneration should be adopted to make forestry viable. Investments in forestry infrastructure like forest roads are also required to decrease the timber logging and transporting costs.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.1
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• pp.1-16
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• 2023

The current study aims to analyze the vegetation characteristics of the rocky slopes in expressway applied by different types of greening work. A field survey on the current status of vegetation were conducted in 50 rock slopes along 13 expressways in two years, 2020 to 2021. Specifically, the type of implemented greening and slope stabilization work, the soil properties, the vegetation coverage, and the emerged species were investigated on a every single slope. As the result of the implemented work types, the soil-media hydroseeding and the gabion work appeared to be the most implemented greening and slope stabilization work, respectively. As a result of the vegetation survey, 126 classification groups (42 families, 93 genera and 126 species) were identified in total and it was observed 26 IAP species and 5 invasive species were growing. The longer the time after greening work, the more frequent appearance of IAP species were observed. Woody species such as Robinia pseudoacacia and Lespedeza bicolo, and perennial herbs such as Artemisia princeps, Erigeron annuus, and Festuca arundinacea were appeared with high frequencies at the rocky slopes in expressway. It was also observed Pinus densiflora, Quercus dentata, Rubus crataegifolius and Miscanthus sinensis which had invaded from the adjacent forests naturally, and the largest number of species were invaded between 5~10 years usually after greening work in this study.

• Journal of Environmental Impact Assessment
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• v.27 no.2
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• pp.124-138
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• 2018

This research was conducted to examine the availability of spatial data for assessing absorption rates of $CO_2$ in the forest of Ansan-si and evaluate the validity of methods that analyze $CO_2$ absorption. To statistically assess the $CO_2$ absorption rates per year, the 1:5,000 Digital Forest-Map (Lim5000) and Standard Carbon Removal of Major Forest Species (SCRMF) methods were employed. Furthermore, Land Cover Map (LCM) was also used to verify $CO_2$ absorption rate availability per year. Great variations in $CO_2$ absorption rates occurred before and after the year 2010. This was due to improvement in precision and accuracy of the Forest Basic Statistics (FBS) in 2010, which resulted in rapid increase in growing stock. Thus, calibration of data prior to 2010 is necessary, based on recent FBS standards. Previous studies that employed Lim5000 and FBS (2015, 2010) did not take into account the $CO_2$ absorption rates of different tree species, and the combination of SCRMF and Lim5000 resulted in $CO_2$ absorption of 42,369 ton. In contrast to the combination of SCRMF and Lim5000, LCM and SCRMF resulted in $CO_2$ absorption of 40,696 ton. Homoscedasticity tests for Lim5000 and LCM resulted in p-value <0.01, with a difference in $CO_2$ absorption of 1,673 ton. Given that $CO_2$ absorption in forests is an important factor that reduces greenhouse gas emissions, the findings of this study should provide fundamental information for supporting a wide range of decision-making processes for land use and management.