• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.108-120
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• 2008

This paper discusses the prediction of deforestation areas using probability models from forest census database, Geographic information system (GIS) database and the land cover database. The land cover data was analyzed using remotely-sensed (RS) data of the Landsat TM data from 1989 to 2001. Over the analysis period of 12 years, the deforestation area was about 40ha. Most of the deforestation areas were attributable to road construction and residential development activities. About 80% of the deforestation areas for residential development were found within 100m of the road network. More than 20% of the deforestation areas for forest road construction were within 100m of the road network. Geographic factors and vegetation change detection (VCD) factors were used in probability models to construct deforestation occurrence map. We examined the size effect of area partition as training area and validation area for the probability models. The Bayes model provided a better deforestation prediction rate than that of the regression model.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.4
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• pp.41-53
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• 2007

The Baekdudaegan Mountain Range is a backbone of the Korean Peninsula which carries special spiritual and sentimental signatures for Koreans as well as significant ecological values for diverse organisms. However, in spite of importance of this region, the forests of Baekdudaegan have been damaged in a variety of human activities by being used as highland vegetable grower, lumber region, grass land, and bare land, and are still undergoing destruction. The existing researches had determined the details of the damage through on-site and recent observations. Such methods cannot provide quantitative and integrated analysis therefore could not be utilized as objective data for the ecological conservation of Baekdudaegan forests. The goal of this study is to quantitatively analyze the forest damage in the Baekdudaegan preservation region through land cover categorization and change detection techniques by using satellite images, which are 1980s, and 1990s Landsat TM, and 2000s Landsat ETM+. The analysis was executed by detecting land cover changed areas from forest to others and analyzing changed areas' spatial patterns. Through the change detection analysis based on land cover classification, we found out that the deforested areas were approximately three times larger after the 1990s than from the 1980s to the 1990s. These areas were related to various topographical and spatial elements, altitude, slope, the distance form road, and water system, etc. This study has the significance as quantitative and integrated analysis about the Baekdudaegan preservation region since 1980s. These results could actually be utilized as basic data for forest conservation policies and the management of the Baekdudaegan preservation region.

• Research in Plant Disease
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• v.23 no.3
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• pp.207-211
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• 2017

In December of 2016, 'The Forest Protection Act' was amended partly in The National Assembly and the socalled 'Tree Doctor Act' was promulgated. Tree Doctor Act will be enforced from June 28, 2018. Under the new Act, none other than 'Tree Hospital' can do disease and pest management work for trees in public living space. The only exclusive qualification for tree hospital is a 'Tree Doctor', the government registered license which is newly established by the Act. To become a tree doctor, he/she must complete the tree doctor training courses in the designated 'Tree Doctor Academy' and pass the qualification test. Currently, Korea Forest Service is drafting the enforcement ordinances and regulations for the implement of Tree Doctor Act. When taking into consideration that the most fundamental and important discipline of the plant and tree health care is the plant pathology, and that the tree health care is a promising business for young plant pathology people, Korean Society of Plant Pathology is ought to be actively involved in the preparation of the enforcement ordinances and regulations, and help the early establishment of the new tree health care system in living spaces of Korea.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1341-1347
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• 2021

The need for an effective disaster management system has grown these days to protect public safety as the number of disasters causing massive damage increases. Since disaster-induced damage can develop in various ways, rapid and accurate countermeasures must be prepared soon after disasters occur. Numerous studies have continuously developed remote sensing and GIS (Geographic Information System)-based techniques for disaster monitoring and damage analysis. This special issue presents the research results on disaster prediction and monitoring based on various remote sensors on different platforms from ground to space and disaster management using GIS techniques. The developed techniques help manage various disasters such as storms, floods, and forest fires and can be combined to achieve an integrated and effective disaster management system.

• Journal of Korean Society of Forest Science
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• v.87 no.3
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• pp.347-357
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• 1998

The objective of this study was to present the proper criteria which could be efficiently used for dividing the land-use zones in Korean national parks. Delphi technique was employed to collect data for this study. The Delphi process was designed with 3 round questionaries for Korean panel experts. A list of 30 criteria was obtained to be considered in dividing land-use zones. From the results, the biological category, in which 10 criteria were involved, occupied the most part of them. This means that the panels consider the biological criteria to be the most important ones under the serious situation of environmental deterioration. Using the 30 criteria emerged from this study, it could be possible to analyze the fitness of the existing land-use zoning system. Prior to the application of these criteria to each park, however, the areal characteristics should be surveyed to select the proper criteria. The new zoning system based on the regional characteristics of each park could be efficiently utilized for management of Korean national parks.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.246-251
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• 2017

Crop models have been used to predict a heading date for efficient management of fertilizer application. Recently, the ORYZA (v3) model was developed to improve the ORYZA2000 model, which has been used for simulation of rice growth in Korea. Still, little effort has been made to assess applicability of the ORYZA (v3) model to rice farms in Korea. The objective of this study was to evaluate reliability of heading dates predicted using the the ORYZA (v3) model, which would indicate applicability of the model to a decision support system for fertilizer application. Field experiments were conducted from 2015-2016 at the Rural Development Administration (RDA) to obtain rice phenology data. Shindongjin cultivar which is mid-late maturity type was grown under a conventional fertilizer management, e.g., application of fertilizer at the rate of 11 Kg N/10a. Another set of heading dates was obtained from annual reports at experiment farms operated by the National Institute of Crop Science and Agricultural Technology Centers in each province. The input files for the ORYZA (v3) model were prepared using weather and soil data collected from the Korean Meteorology Administration (KMA) and the Korean Soil Information System, respectively. Input parameters for crop management, e.g., transplanting date and planting density, were set to represent management used for the field experiment. The ORYZA (v3) model predicted heading date within 1 day for two seasons. The crop model also had a relatively small error in prediction of heading date for three ecotypes of rice cultivars at experiment farms where weather input data were obtained from a near-by weather station. Those results suggested that the ORYZA (v3) model would be useful for development of a decision support system for fertilizer application when reliable input data for weather variables become available.

• Journal of Korean Society of Forest Science
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• v.89 no.3
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• pp.440-451
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• 2000

This study was conducted in order to provide essential data and relevant management proposal to conserve and maintain big and old trees in a rational way. For the field survey, 77 big and old trees preserved by the laws in Chollabuk-do, Korea were investigated. The study results are summarized as follows : 1. To conserve and manage big and old trees, the valuable trees have been designated as natural monument trees and protection-needed trees. There are 141 individuals of 37 species designated as natural monuments and 10,049 individuals of 102 species designated as protection-needed trees. 2. Management budget for natural monument trees was devoted at 70% from the national expenditure, but that for protection-needed trees was devoted at 98% from the local expenditure. 3. Standardized sign boards and sign stones for natural monument trees were well placed and other protection facilities such as fences, branch supports and branch holdings were established. On the other hand, management of protection-needed trees was deficient overall. 4. Problems for designation process and management of protection-needed trees could include items such as insufficient management budget, various development activities, land ownership, misjudgement of tree age and species identification, unsatisfaction of sign board placement, insufficient surgery for damaged trees, pavement around tree root system and environmental pollution around the trees. 5. In order to improve the existing management methods of big and old trees, the following schemes were suggested : the development of practical criteria for natural monument and protection-needed trees, nationwide surveys of big and old tree resources, the security of national budget, securing sufficient spaces for the tree growth, specialization of management systems, extended practices of tree form management, establishment of permanent standard signs and consideration of opinions of village residents.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.908-913
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• 2010

This study analyzed the impact of climatic and topographic factors on tree radial growth of Pinus densiflora and Quercus spp. in central regions of Korea. To find the relationship between annual tree radial growth and climatic factors, we took the core samples from individual trees and measured the tree radial width. On the assumption that the tree radial growth is related to the tree age, we estimated the radial growth by the tree age as an independent variable. Also, we estimated the standard growth, defined as the radial growth of trees aged 30. As results, we found the spatial auto-correlation in the radial growth of the red pine. Moreover, we also found the relationships between climatic and topographic and the standard growth using the GAM (Generalized Additive Model). Increase of temperature has negative impacts on the radial growth of Pinus densiflora, while it has positive impacts on the radial growth of Quercus spp.. On the other hands, increase of precipitation has negative impacts on the radial growth of both species. Lastly, we predicted the spatial distribution changes of Pinus densiflora and Quercus spp. using the temperature increase scenario and the Geographic Information System (GIS) based forest type map. We could predict that Pinus densiflora is more vulnerable than Quercus spp. to climate change so that the habitats of Pinus densiflora will be gradually changed to the habitats of Quercus spp. in eastern coastal and southern regions of Korea after 60 years.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.28-34
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• 2021

The Fourth Industrial Revolution has led to the development of drones for commercial and private applications. Therefore, the malfunction of drones has become a prominent problem. Failure mode and effect analysis was used in this study to analyze the primary cause of drone failure, and blade breakage was observed to have the highest frequency of failure. This was tested using a vibration sensor placed on drones along the breakage length of the blades. The data exhibited a significant increase in vibration within the drone body for blade fracture length. Principal component analysis was used to reduce the data dimension and classify the state with machine learning algorithms such as support vector machine, k-nearest neighbor, Gaussian naive Bayes, and random forest. The performance of machine learning was higher than 0.95 for the four algorithms in terms of accuracy, precision, recall, and f1-score. A follow-up study on failure prediction will be conducted based on the results of fault diagnosis.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.663-671
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• 2020

Recently, there have been many natural disasters in Korea, not only in forest areas but also in urban areas, and the national requirements for them are increasing. In particular, there is no pre-disaster information system that can systematically manage the collapse of the slope of the national highway. In this study, big data analysis was conducted on the factors causing slope collapse based on the detailed investigation report on the slope collapse of national roads in Gangwon-do and Gyeongsang-do areas managed by the Cut Slope Management System (CSMS) and the basic survey of slope failures. Based on the analysis results, a slope collapse risk prediction model was established through Adaboost, a classification-based machine learning model, reflecting the collapse slope location and weather information. It also developed a visualization map for the risk of slope collapse, which is a visualization program, to show that it can be used for preemptive disaster prevention measures by identifying the risk of slope due to changes in weather conditions.