• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.2
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• pp.57-69
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• 2021

Urban green spaces supply ecosystem services (ESs), which are consumed by city residents and generate demand, to improve air quality. It is important to determine supply and demand for ESs and reduce the gap for efficient management. This study proposed a method to use the concept of supply and demand for ESs in the decision-making process for urban planning or management. PM₁₀ concentrations were converted to weight for demand assessment on PM₁₀ reduction, and PM₁₀ absorption capacity of all green spaces including the forests, and that of urban green spaces excluding forests, was calculated for each supply assessment. The differences in the calculated supply and demand were analyzed to derive the mismatched regions in Suwon. As a result, regions with big forested areas showed sufficient supply, indicating that the degree of mismatch among administrative neighborhoods (dong) varied greatly depending on whether they had a forest. An analysis of only urban green spaces showed that all neighborhoods lacked supply. Forests with high PM₁₀ absorption capacity had a great effect, but urban green spaces can be considered a key element in reducing PM₁₀ in daily life. Considering the mismatch of supply and demand, spatial distribution, and population distribution, it is possible to prioritize the supply of urban green spaces to reduce PM₁₀ and, furthermore, support decision making for priority zones subject to forest conservation and designation and cancellation of green spaces, which gives significance to this study.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.61-80
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• 1997

This study tried to propose the guidelines for the ecological preservation zoning in Korea. So some related laws and regulations were inspected, which were Natural Environment Preservation Act, Nature Park Act, Cultural Asset Conservation Act, Forest Act and Urban Planning Act. In these acts, I could find several concepts related to the ecosystem that are described as the protection area. But there aren't detailed and practical characteristics in those concepts. So for making the practical concept of ecosystem preservation, I considered Multiple Use Module, Wildlife habitat model, and Environmental evaluation model. Thorough this step, the process and methodology was established for evaluating and analysing. The potentiality of the GIS system was inspected. So the TM5 scene of the site was acquired and processed by ER-Mapper, Idrisi, Arc/Info and Arcview. And several digitized data were input by scanning and vecterizing. The Erdas format was mostly exchangeable to any program. The site is the Byonsan Peninsula National Park. The forest stand information and topographic data were digitized, types of which are forest year, DBH, density, slope, aspect etc. And also the watershed boundary, roads and paths, natural and cultural resources were mapped and analysed. Modelling of preservation suitability found the dispersed patterns for the best suitable zone through all the site. And the development potential areas were checked on downwatershed. This patterns are thought to result from the forest location for the wildlife habitat and the low altitude and no-steep slopes for developing. And Early warning system concept was introduced by overlapping these two patterns on the both potential area. As the conclusions, I proposed that the preservation zone be assigned according to the watershed unit as the main ecosystem zone. This main area should be linked by the eco-corridor through the point type eco-system. Finally, I thought the comprehensive information system should be established for making the rational and efficient decision making in natural area.

• Journal of Forest and Environmental Science
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• v.32 no.4
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• pp.392-399
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• 2016

This review paper presents guidelines which stakeholders use in addressing on-farm tree planting configuration, establishment, tending, silvi- cultural management, management of pests and diseases, challenges and opportunities as practiced in the medium to high potential areas of Kenya. The tree planting configurations discussed includes blocks planting (woodlot), boundary, compound planting, home/fruit gardens, trees intercropped or mixed with pasture, trees on riverbanks and roadside. Participatory monitoring and evaluation techniques have been highlighted. The main challenges facing tree planting activities include culture and attitude of local people, land and tree tenure, inadequate technical support, lack of recognition and integration of technical information and indigenous knowledge, capital and labour shortages, lack of appropriate incentives measures, damage by domestic and wild animals, conflict over trees on the boundary and policy and legal issues. This guideline targets forest managers, extension agents, students and other practitioners in policy and day to day decision making processes in Kenya.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.43-57
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• 2022

This study aims to classify forest fire-affected areas, identify forest types by the intensity of forest fire damage using multi-time Landsat-satellite images before and after forest fires and to analyze the effects of artificial restoration sites and natural restoration sites. The difference in the values of the Normalized Burned Ratio(NBR) before and after forest fire damage not only maximized the identification of forest fire affected and unaffected areas, but also quantified the intensity of forest fire damage. The index was also used to confirm that the higher the intensity of forest fire damage in all forest fire-affected areas, the higher the proportion of coniferous forests, relatively. Monitoring was conducted after forest fires through Normalized Difference Vegetation Index(NDVI), an index suitable for the analysis of effects by restoration type and the NDVI values for artificial restoration sites were found to no longer be higher after recovering the average NDVI prior to the forest fire. On the other hand, the natural restoration site witnessed that the average NDVI value gradually became higher than before the forest fires. The study result confirms the natural resilience of forests and these results can serve as a basis for decision-making for future restoration plans for the forest fire affected areas. Further analysis with various conditions is required to improve accuracy and utilization for the policies, in particular, spatial analysis through forest maps as well as review through site checks before and immediately after forest fires. More precise analysis on the effects of restoration will be available based on a long term monitoring.

• Journal of Forest and Environmental Science
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• v.34 no.6
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• pp.461-471
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• 2018

In this study, the deforestation and forest degradation areas have been obtained in Myanmar using a land cover lamp (LCM) and a tree cover map (TCM) to get the $CO_2$ potential reduction and the strength of occurrence was evaluated by using the geostatistical technique. By applying a multiple criteria decision-making method to the regions having high strength of occurrence for the $CO_2$ potential reduction for the deforestation and forest degradation areas, the priority was selected for candidate lands for REDD+ project. The areas of deforestation and forest degradation were 609,690ha and 43,515ha each from 2010 to 2015. By township, Mong Kung had the highest among the area of deforestation with 3,069ha while Thlangtlang had the highest in the area of forest degradation with 9,213 ha. The number of $CO_2$ potential reduction hotspot areas among the deforestation areas was 15, taking up the $CO_2$ potential reduction of 192,000 ton in average, which is 6 times higher than that of all target areas. Especially, the township of Hsipaw inside the Shan region had a $CO_2$ potential reduction of about 772,000 tons, the largest reduction potential among the hotpot areas. There were many $CO_2$ potential reduction hot spot areas among the forest degradation area in the eastern part of the target region and has the $CO_2$ potential reduction of 1,164,000 tons, which was 27 times higher than that of the total area. AHP importance analysis showed that the topographic characteristic was 0.41 (0.40 for height from surface, 0.29 for the slope and 0.31 for the distance from water area) while the geographical characteristic was 0.59 (0.56 for the distance from road, 0.56 for the distance from settlement area and 0.19 for the distance from Capital). Yawunghwe, Kalaw, and Hsi Hseng were selected as the preferred locations for the REDD+ candidate region for the deforestation area while Einme, Tiddim, and Falam were selected as the preferred locations for the forest degradation area.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.35-48
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• 2018

The study of air defense against North Korean tactical ballistic missiles (TBM) should consider the rapidly changing battlefield environment. The study for target re-designation for intercept missiles enables effective operation of friendly defensive assets as well as responses to dynamic battlefield. The researches that have been conducted so far do not represent real-time dynamic battlefield situation because the hit probability for the TBM, which plays an important role in the decision making process, is fixed. Therefore, this study proposes a target re-designation algorithm that makes decision based on hit probability which considers real-time field environment. The proposed method contains a trajectory prediction model that predicts the expected trajectory of the TBM from the current position and velocity information by using random forest and moving window. The predicted hit probability can be calculated through the trajectory prediction model and the simulator of the intercept missile, and the calculated hit probability becomes the decision criterion of the target re-designation algorithm for the missile. In the experiment, the validity of the methodology used in the TBM trajectory prediction model was verified and the superiority of using the hit probability through the proposed model in the target re-designation decision making process was validated.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.61-68
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• 2024

In the quest for advancing diabetes diagnosis, this study introduces a novel two-step machine learning approach that synergizes the probabilistic predictions of Logistic Regression with the classification prowess of Random Forest. Diabetes, a pervasive chronic disease impacting millions globally, necessitates precise and early detection to mitigate long-term complications. Traditional diagnostic methods, while effective, often entail invasive testing and may not fully leverage the patterns hidden in patient data. Addressing this gap, our research harnesses the predictive capability of Logistic Regression to estimate the likelihood of diabetes presence, followed by employing Random Forest to classify individuals into diabetic, pre-diabetic or nondiabetic categories based on the computed probabilities. This methodology not only capitalizes on the strengths of both algorithms-Logistic Regression's proficiency in estimating nuanced probabilities and Random Forest's robustness in classification-but also introduces a refined mechanism to enhance diagnostic accuracy. Through the application of this model to a comprehensive diabetes dataset, we demonstrate a marked improvement in diagnostic precision, as evidenced by superior performance metrics when compared to other machine learning approaches. Our findings underscore the potential of integrating diverse machine learning models to improve clinical decision-making processes, offering a promising avenue for the early and accurate diagnosis of diabetes and potentially other complex diseases.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.158-169
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• 2012

Sabah has experienced a rapid decline in the extent of forest cover. The precise impact of habitat loss on the conservation status of the plants of Sabah is uncertain. In this study we use the niche modelling algorithm MAXENT to construct preliminary, revised and final ecological niche models for Dipterocarpus lamellatus and Dipterocarpus ochraceus and combined these models with data on current land-use to derive conservation assessments for each species. Preliminary models were based on herbarium data alone. Ground surveys were conducted to evaluate the performance of these preliminary models, and a revised niche model was generated from the combined herbarium and ground survey data. The final model was obtained by constraining the predictions of the revised models by filters. The range overlap between the preliminary and revised models was 0.47 for D. lamellatus and 0.39 for D. ochraceus, suggesting poor agreement between them. There was substantial variation in estimates of habitat loss for D. ochraceus, among the preliminary, revised and constrained models, and this has the potential to lead to incorrect threat assessments. From these estimates of habitat loss, the historic distribution and estimates of population size we determine that both species should be classified as Critically Endangered under IUCN Red List guidelines. Our results suggest that ground-truthing of ecological niche models is essential, especially if the models are being used for conservation decision making.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.77-88
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• 2017

This study developed an inventory, using GIS-based resource assessment, for assisting forest management planning. The major inventory contents were relationally integrated, using field sample plots, to extract and calculate attributes such as general status, forest stand condition, forest site condition, forest site and soil area (ha) and growing stock (weight, in tons). Evaluating the efficiency of forest management plan implementations is critical to effective health and sustainability at a larger functional level, specifically in bamboo forests. This inventory is a valuable tool for decision-making, such as developing a long-term management plan for sustainably managing bamboo resources.

• Journal of Korean Society of Forest Science
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• v.90 no.6
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• pp.725-733
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• 2001

In this study, the relationship between growth factors for Pinus densiflora stands in Anmyun-Island was analyzed and dynamic growth model was prepared. A total of 96 sample plots was investigated in which dbh and height of individual trees were measured. From these plot data, quadratic mean dbh, mean height, dominant tree height, stem number per ha, basal area per ha and volume per ha were estimated. Several regression equations between growth factors were derived using NLIN and REG procedure of SAS. And dynamic growth model, in which the equations were interactively linked, was prepared for the prediction of stand growth and yield under different management regime. The predictions of dynamic growth model were found to be coincided with general growth principles. The dynamic growth model was considered as adequate for predicting growth and yield of Pinus densiflora stand in Anmyun-Island. In practice, the dynamic growth model can be applied for predicting the growth and development of stand for various forest treatments and for decision-making in forest management.