• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.161-170
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• 2023

We attempted to estimate the carbon accumulation of Hibiscus hamabo and Paliurus ramosissimus, semimangroves native to Jeju Island, by remote sensing and to build an artificial intelligence model that predicts its spatial variation with climatic factors. The aboveground carbon accumulation of semi-mangroves was estimated from the aboveground biomass density (AGBD) provided by the Global Ecosystem Dynamics Investigation (GEDI) lidar upscaled using the normalized difference vegetation index (NDVI) extracted from Sentinel-2 images. In Jeju Island, carbon accumulation per unit area was 16.6 t C/ha for H. hamabo and 21.1 t C/ha for P. ramosissimus. Total carbon accumulation of semi-mangroves was estimated at 11.5 t C on the entire coast of Jeju Island. Random forest analysis was applied to predict carbon accumulation in semi-mangroves according to environmental factors. The deviation of aboveground biomass compared to the distribution area of semi-mangrove forests in Jeju Island was calculated to analyze spatial variation of biomass. The main environmental factors affecting this deviation were the precipitation of the wettest month, the maximum temperature of the warmest month, isothermality, and the mean temperature of the wettest quarter. The carbon accumulation of semi-mangroves predicted by random forest analysis in Jeju Island showed spatial variation in the range of 12.0 t C/ha - 27.6 t C/ha. The remote sensing estimation method and the artificial intelligence prediction method of carbon accumulation in this study can be used as basic data and techniques needed for the conservation and creation of mangroves as carbon sink on the Korean Peninsula.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1719-1729
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• 2021

Leaf area index (LAI) provides valuable information necessary for sustainable and effective management of forests. Although global high resolution LAI data are provided by European Space Agency using Sentinel-2 satellite images, they have not considered forest characteristics in model development and have not been evaluated for various forest ecosystems in South Korea. In this study, we proposed a LAI estimation model combining machine learning and the PROSAIL radiative transfer model using Sentinel-2 satellite data over a local forest area in South Korea. LAI-2200C was used to measure in situ LAI data. The proposed LAI estimation model was compared to the existing Sentinel-2 LAI product. The results showed that the proposed model outperformed the existing Sentinel-2 LAI product, yielding a difference of bias ~ 0.97 and a difference of root-mean-square-error ~ 0.81 on average, respectively, which improved the underestimation of the existing product. The proposed LAI estimation model provided promising results, implying its use for effective LAI estimation over forests in South Korea.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.403-406
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• 2005

In order to evaluate the Capability of ETM+ remotely- sensed data to provide 'Forest-shrub land-Rangeland' cover type map in areas near the timberline of northern forests of Iran, the data were analyzed in a portion of nearly 790 ha located in Neka-Zalemroud region. First, ortho-rectification process was used to correct the geometric errors of the image, yielding 0/68 and 0/69 pixels of RMS. error in X and Y axis, respectively. The original and panchromatic bands were fused using PANSHARP Statistical module. The ground truth map was made using 1 ha field plots in a systematic-random sampling grid, and vegetative form of trees, shrubs and rangelands was recorded as a criteria to name the plots. A set of channels including original bands, NDVI and IR/R indices and first components of PCI from visible and infrared bands, was used for classification procedure. Pair-wise divergence through CHNSEL command was used, In order to evaluate the separability of classes and selection of optimal channels. Classification was performed using ML classifier, on both original and fused data sets. Showing the best results of $67\%$ of overall accuracy, and 0/43 of Kappa coefficient in original data set. Due to the results represented above, it's concluded that ETM+ data has an intermediate capability to fulfill the spectral variations of three form- based classes over the study area.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.623-632
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• 2018

Both investors and researchers are attentive to the prediction of stock price movement directions since the accurate prediction plays an important role in strategic decision making on stock trading. According to previous studies, taken together, one can see that different factors are considered depending on stock markets and prediction periods. This paper aims to analyze what data mining techniques show better performance with some representative index and stock price datasets in the Korea stock market. In particular, extreme gradient boosting technique, proving itself to be the fore-runner through recent open competitions, is applied to the prediction problem. Its performance has been analyzed in comparison with other data mining techniques reported good in the prediction of stock price movement directions such as random forests, support vector machines, and artificial neural networks. Through experiments with the index/price datasets of 12 years, it is identified that the gradient boosting technique is the best in predicting the movement directions after 1 to 4 days with a few partial equivalence to the other techniques.

• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1125-1137
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• 2014

This paper studies what affects the private education cost for the elementary, middle, and high school students. It is a big issue now because there can be a problem in the equal opportunity for education if the portion of private education cost is very high in the total education cost. If we spend more time and money on the private education than the school education, it can cause the polarization among the classes and regions. The excessive private education also can deteriorate the school system. we use various regression and classification methods to analyze the cost of private education and find the important variables in the models. we found that large cities spend more money on the private education than small cities. We also found that high school students spend more than middle school students and the elementary students and the household with more income spend more money on the private education.

• Korean Journal of Veterinary Service
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• v.32 no.3
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• pp.265-273
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• 2009

A cross-sectional survey was undertaken to identify risk factors and clinical signs associated with parasitic helminth infections of cattle in Mymensignh district of Bangladesh. A nonrandom convenience sampling method was used to select 138 animals from 40 farmers/herds. The eggs per gram of faeces (epg) for nematodes and trematodes were determined by McMaster and Stoll's methods respectively. Animal-level and herd-level data were recorded by means of a questionnaire. Multi-collinearity amongst explanatory variables were assessed using $2{\times}2{\times}\;X^2$ test and one variable in a pair was dropped if $P{\leq}0.05$ formultiple logistic regression models. Association study between outcome and explanatory variables was conducted using classification tree, random forests and multiple logistic regression. A positive epg was considered as infected. Analyses were performed using $STATA^{(R)}$, version 8.0/Intercooled and $R^{(R)}$, Version 2.3.0. Seventy eight percent of the cattle were found to be infected with at least one type of helminth. Twenty four pairs of combinations of explanatory variables showed significant associations. Male animals (OR=3.3, P=.006, 95% CI=1.4, 7.7) were associated with significantly increased prevalence of nematode infection. Female cattle of the study area are mostly cross-breed, kept indoor, fed relatively good diet and not used for draught purpose. Males are used for draught purpose thereby more exposed to nematode infective stage and provided with relatively poor diet. So stressed male cattle may become more susceptible to nematode infection. All of the three statistical techniques selected gender and lumen motility as most important variables in association with nematode infection in cattle. The result of this survey can only be extrapolated to the periurban cattle population of traditional management system.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.7 no.1
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• pp.50-58
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• 2004

The aim of this study was to characterize the forest vegetation structure and site of Quercus serrata forest for ecological forest management and ecological niche. The results are as follows : The chemical properties of Q. serrata forest soil were 0.24% of total nitrogen, 8.27 of organic matter, 74ppm of available phosphorous, 1.64(me/100g) of Ca, 0.22(me/100g) of Mg, 0.74(me/100g) of K and 9.3(me/100g) of cation exchangeable capacity. The dominant species in Quercus serrata forest were Quercus serrata, Quercus acutissima, Quercus variabilis, Quercus mongolica, Styrax obassia, Fraxinus rhynchophylla and Styrax japonica. DBH analysis showed that Quercus serrata seems to remain as a dominant species for the present because they had random distribution based on few of big individuality, many of small and middle individuality. But the Q. serrata community is competing with Q. mongolica and F. rhynchophylla, whose density of small individuality has increased. With the classification of TWINSPAN, Q. serrata forest was classified three groups, such as Q. serrata-Acer mono, Q. serrata, Q. serrata-Q. acutissima communities. The results of the correlation analysis of Q. serrata major communities and environment factors are as follows; Q. serrata-A. mono community was found relatively in high elevated and eastern and northern area that has relatively high percentage organic matter. Also Q. serrata community was found in high elevated and eastern and northern area that has high percentage organic matter. Q. serrata-Q. acutissima community was found in low elevated and southern and western area that has low percentage organic matter.

• Journal of Korean Academy of Nursing
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• v.46 no.1
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• pp.140-148
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• 2016

Purpose: This study was performed to determine the physical and psychological effects of an urban forest-walking program for office workers. For many workers, sedentary lifestyles can lead to low levels of physical activity causing various health problems despite an increased interest in health promotion. Methods: Fifty four office workers participated in this study. They were assigned to two groups (experimental group and control group) in random order and the experimental group performed 5 weeks of walking exercise based on Information-Motivation-Behavioral skills Model. The data were collected from October to November 2014. SPSS 21.0 was used for the statistical analysis. Results: The results showed that the urban forest walking program had positive effects on the physical activity level (U=65.00, p <.001), health promotion behavior (t= - 2.20, p =.033), and quality of life (t= - 2.42, p =.020). However, there were no statistical differences in depression, waist size, body mass index, blood pressure, or bone density between the groups. Conclusion: The current findings of the study suggest the forest-walking program may have positive effects on improving physical activity, health promotion behavior, and quality of life. The program can be used as an effective and efficient strategy for physical and psychological health promotion for office workers.

• Journal of Korean Society of Forest Science
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• v.99 no.4
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• pp.590-596
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• 2010

To investigate and to compare the structure of Picea jezoensis forests at Chunwangbong area in the Jirisan National Park, 33 plots(400) were set up by a random sampling method. Dead individuals of Picea jezoensis trees were 15.6%, these were observed mainly in the upper-layer trees. A few seedlings of Picea jezoensis were found in this investigation area. This result indicates that Picea jezoensis might be gradually decreased in the future. Picea jezoensis stands were classified into two major groups by cluster analysis. There were strong positive correlations between Syringa reticulata and Acer pseudosieboldianum, Tripterygium regelii, Quercus serrata; Betula ermani and Lonicera maackii; Euonymus macropterus and Acer ukurunduense; Acer pseudosieboldianum and Tripterygium regelii, and relatively weak negative correlations were showed between Picea jezoensis and Abies koreana; Betula ermani and Acer ukurunduense; Acer pseudosieboldianum and Tripterygium regelii. Species diversity index(H') of investigated groups ranged from 1.0000 to 1.3010.