• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.327-338
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• 2000

The forest conditions of North Korea has been a great concern since it was known to be closely related to many environmental problems of the disastrous flooding, soil erosion, and food shortage. To assess the long-term changes of forest area as well as the canopy conditions, several sources of multitemporal satellite data were applied to the study area near Kaesung. KOMPSAT-1 EOC data were overlaid with 1981 topographic map showing the boundaries of forest to assess the deforestation area. Delineation of the cleared forest was performed by both visual interpretation and unsupervised classification. For analyzing the change of forest canopy condition, multiple scenes of Landsat and SPOT data were selected. After preprocessing of the multitemporal satellite data, such as image registration and normalization, the normalized difference vegetation index (NDVI) was derived as a representation of forest canopy conditions. Although the panchromatic EOC data had radiometric limitation to classify diverse cover types, they can be effectively used t detect and delineate the deforested area. The results showed that a large portion of forest land has been cleared for the urban and agricultural uses during the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. Possible causes of the deforestation and the temporal pattern of canopy conditions are discussed.

• Journal of Platform Technology
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• v.8 no.1
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• pp.3-9
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• 2020

In Korea, 63% of the nation's land is made up of forests, and the average temperature of the earth has been increasing. Forest service has been operating a proactive control system for preventing the spread of forest pests such as Pine wilt disease. but there were some hurdles in timely control due to weather, topography and manpower management difficulties. In this paper, we propose a model for building fast, accurate and efficient control system by categorizing the damage and dead wood automatically based on the images acquired using small unmanned aerial vehicles based on information and communication technology. In particular, the proposed model establishes an effective response system for government affairs through cooperation in the private sector. It can also create new jobs in the unmanned aerial vehicle business and service industries.

• The Plant Pathology Journal
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• v.37 no.3
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• pp.243-257
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• 2021

Bacillus pumilus is the causal agent of trunk bulges disease affecting rubber and rubberwood quality and yield production. In this study, B. pumilus and other closely related species were included in B. pumilus group, as they shared over 99.5% similarity from 16S rRNA analysis. Multilocus sequence analysis (MLSA) of five housekeeping genes and repetitive elements-based polymerase chain reaction (rep-PCR) using REP, ERIC, and BOX primers conducted to analyze the diversity and systematic relationships of 20 isolates of B. pumilus group from four rubber tree plantations in Peninsular Malaysia (Serdang, Tanah Merah, Baling, and Rawang). Multi rep-PCR results revealed the genetic profiling among the B. pumilus group isolates, while MLSA results showed 98-100% similarity across the 20 isolates of B. pumilus group species. These 20 isolates, formerly established as B. pumilus, were found not to be grouped with B. pumilus. However, being distributed within distinctive groups of the B. pumilus group comprising of two clusters, A and B. Cluster A contained of 17 isolates close to B. altitudinis, whereas Cluster B consisted of three isolates attributed to B. safensis. This is the first MLSA and rep-PCR study on B. pumilus group, which provides an in-depth understanding of the diversity of these rubber-pathogenic isolates in Malaysia.

• Journal of architectural history
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• v.32 no.1
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• pp.35-45
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• 2023

Bongsu(Beacon Fire Station) is a facility that sends signals with fire and smoke and has been used in Korea since the Three Kingdoms period. This facility was installed to know the north and south crises. This trend continues until the Joseon Dynasty, and it has been somewhat completed in the 17th century. In previous studies, beacon fire was identified mainly from the border area to Hanyang. Based on this, it was classified into Gyeongbongsu, Yeonbyeonbongsu, and Naejibongsu. However, it is difficult to define the characteristics of beacon fire in coastal areas only with this classification. In the case of beacon fire in island areas, there was a tendency to value communication connection within the region rather than connection with the capital. As a case analysis for this, an academic review was conducted with the cases of Ganghwa Island and Jeju Island. As a result, it was confirmed that the role and character of the beacon vary depending on the defense system and the physical distance from the land, even if it has the topographical commonality of the same island.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.175-175
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• 2023

Detection and monitoring of wildfires are essential for limiting their harmful effects on ecosystems, human lives, and property. In this research, we propose a novel method running in the Google Earth Engine platform for identifying and characterizing burnt regions using a hybrid of Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (multispectral photography) images. The 2022 Uljin wildfire, the severest event in South Korean history, is the primary area of our investigation. Given its documented success in remote sensing and land cover categorization applications, we select the Random Forest (RF) method as our primary classifier. Next, we evaluate the performance of our model using multiple accuracy measures, including overall accuracy (OA), Kappa coefficient, and area under the curve (AUC). The proposed method shows the accuracy and resilience of wildfire identification compared to traditional methods that depend on survey data. These results have significant implications for the development of efficient and dependable wildfire monitoring systems and add to our knowledge of how machine learning and remote sensing-based approaches may be combined to improve environmental monitoring and management applications.

• Economic and Environmental Geology
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• v.56 no.1
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• pp.65-73
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• 2023

As one of the most vulnerable countries to floods, there should be an increased necessity for accurate and reliable flood forecasting in Indonesia. Therefore, a new prediction model using a machine learning algorithm is proposed to provide daily flood prediction in Indonesia. Data crawling was conducted to obtain daily rainfall, streamflow, land cover, and flood data from 2008 to 2021. The model was built using a Random Forest (RF) algorithm for classification to predict future floods by inputting three days of rainfall rate, forest ratio, and stream flow. The accuracy, specificity, precision, recall, and F1-score on the test dataset using the RF algorithm are approximately 94.93%, 68.24%, 94.34%, 99.97%, and 97.08%, respectively. Moreover, the AUC (Area Under the Curve) of the ROC (Receiver Operating Characteristics) curve results in 71%. The objective of this research is providing a model that predicts flood events accurately in Indonesian regions 3 months prior the day of flood. As a trial, we used the month of June 2022 and the model predicted the flood events accurately. The result of prediction is then published to the website as a warning system as a form of flood mitigation.

• Journal of English Language & Literature
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• v.58 no.4
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• pp.611-632
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• 2012

Beckett's life-long struggling with death may be illuminated in terms of the Western tradition of thanatology as well as Philippe Ariès's anthropological classification of death. Among the Western tradition, Beckett's oeuvre incarnates memento mori, timor mori, nihilism, theatrum mundi, life as afterlife, and the transsubstantiation of the self. Among the five views of death Ariès suggests, Beckett appears to foreground the death of the self and the invisible dirty death. In a world devoid of transcendental Signified, Beckett's resident is "a poor player/That struts and frets his hour upon the stage." Our contemporary vision of death is dominated by the dirty death and timor mori resurrected from the cultural icon of danse macabre in the late Mediaeval age as vividly dramatized in W;t by Margaret Edson. Beckett stands in no man's land: Lucky complains of divine aphathia as well as scopes at the possibility of God's existence like Hamm. Beckett's way of getting out of the dilemma is laughing a mirthless and dianoetic laugher. To bourgeois class who shudder at the sight of Grim Death after forgettable years of indulgence and addiction to capitalist consumption, Beckett seems to preach, your life is a death-in-life, you are not born yet until you are baptized with existential awakening as Gregor Samsa in Kafka's Verwandlung, or Tolstoy in Confession.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.15-23
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• 2024

This research aimed to assess the possibility of detecting forest degradation using time-series satellite imagery and three different deep learning-based change detection techniques. The dataset used for the deep learning models was composed of two sets, one based on surface reflectance (SR) spectral information from satellite imagery, combined with Texture Information (GLCM; Gray-Level Co-occurrence Matrix) and terrain information. The deep learning models employed for land cover change detection included image differencing using the Unet semantic segmentation model, multi-encoder Unet model, and multi-encoder Unet++ model. The study found that there was no significant difference in accuracy between the deep learning models for forest degradation detection. Both training and validation accuracies were approx-imately 89% and 92%, respectively. Among the three deep learning models, the multi-encoder Unet model showed the most efficient analysis time and comparable accuracy. Moreover, models that incorporated both texture and gradient information in addition to spectral information were found to have a higher classification accuracy compared to models that used only spectral information. Overall, the accuracy of forest degradation extraction was outstanding, achieving 98%.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1029-1038
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• 2010

In meteorology Korea has 2/3 of rain of annual total rainfall at the month of Jun through Sept and it has possibility to have serious flood damage because geographically it is composed of mountainous area with steep slope which account for 70% of its country. Also, the increase of impervious layer due to industrialization and urbanization causes direct runoff, which deteriorates contamination of rivers by moving the contaminated material on the surface at the beginning of rain. In particular, the area of leisure facilities needs the management of water quality absolutely because dense population requires space of park function and place to relax and increases moving capability of non-point pollution source. For disposition of rainfall & runoff, the standard of initial rainfall, which is to be used for the computation of disposition volume, is significant factors for the runoff study of non-point pollution source, Until now, a great deal of study has been done by many researchers. However, it is the current reality that the characteristics of runoff varies according to land protection comprising river basin and the standard of initial rainfall by each researcher is not clearly defined yet. Therefore, in this research, it is suggested that, with the introduction of SOM (Self-Organizing Map), the standard of initial rainfall be determined after analyzing each sectional data by executing pattern classification about runoff and water quality data measured at the test river basin for this research.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.10-27
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• 2014

HAZUS-MH is a GIS-based computer program that estimates potential losses from multi-hazard phenomena: earthquakes, floods and hurricanes. With respect to seismic disaster, characteristics of a hypothetical or actual earthquake are entered into HAZUS. Then HAZUS estimates the intensity of ground shaking and calculates the correspondent losses. In this study, HAZUS was used as a part of the preparations of the future seismic events at a coastal plant facility area. To reliably characterize the target facility area, many geotechnical characteristics data were synthesized from the existing site investigation reports. And the buildings and facilities were sorted by analyzing their material and structural characteristics. In particular, the study area was divided into 17 blocks taking into account the situation of both land development and facility distribution. The ground conditions of blocks were categorized according to the site classification scheme for earthquake-resistant design. Moreover, seismic fragility curves of a main facilities were derived based on the numerical modeling and were incorporated into the database in HAZUS. The results estimated in the study area using HAZUS showed various seismic damage and loss potentials depending on site conditions and structural categories. This case study verified the usefulness of the HAZUS for estimating earthquake losses in coastal facility areas.