• Korean Journal of Remote Sensing
• /
• v.35 no.2
• /
• pp.299-316
• /
• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.

• Plant Breeding and Biotechnology
• /
• v.6 no.4
• /
• pp.391-403
• /
• 2018

Genome resequencing by next-generation sequencing technology can reveal numerous single nucleotide polymorphisms (SNPs) within a closely-related cultivar group, which would enable the development of sufficient SNP markers for mapping and the identification of useful genes present in the cultivar group. We analyzed genome sequence data from 13 Korean japonica rice varieties and discovered 740,566 SNPs. The SNPs were distributed at 100-kbp intervals throughout the rice genome, although the SNP density was uneven among the chromosomes. Of the 740,566 SNPs, 1,014 SNP sites were selected on the basis of polymorphism information content (PIC) value higher than 0.4 per 200-kbp interval, and 506 of these SNPs were converted to Kompetitive Allele-Specific PCR (KASP) markers. The 506 KASP markers were tested for genotyping with the 13 sequenced Korean japonica rice varieties, and polymorphisms were detected in 400 KASP markers (79.1%) which would be suitable for genetic analysis and molecular breeding. Additionally, a genetic map comprising 205 KASP markers was successfully constructed with 188 $F_2$ progenies derived from a cross between the varieties, Junam and Nampyeong. In a phylogenetic analysis with 81 KASP markers, 13 Korean japonica varieties showed close genetic relationships and were divided into three groups. More KASP markers are being developed and these markers will be utilized in gene mapping, quantitative trait locus (QTL) analysis, marker-assisted selection and other strategies relevant to crop improvement.

• Journal of Korean Society of Forest Science
• /
• v.108 no.3
• /
• pp.364-371
• /
• 2019

This study was conducted to provide the basic information for a reasonable forest management plan and sustainable forest management by developing a dominant tree height growth model using diameter at breast height (DBH) and site index curves for Pinus densiflora and Chamaecyparis obtusa growing in Jeolla-do. The altitude, slope, orientation, soil type, height and DBH of a dominant tree, and the ages of trees were measured for 3055 Pinus densiflora trees (611 plots) and 3345 Chamaecyparis obtusa trees (699 plots), and these data were used to develop a customized afforestation map. In the dominant tree height growth model, the relationship to DBH was used in the Petterson, Michailow, and log equations. Also, a dominant tree height growth model in relationship to age used the Chapman-Richards, Schumacher, and Gompertz equations. The Petterson equation, which has a lower mean square error, was used to model dominant tree height growth in relationship to DBH. In the model of dominant tree height growth in relationship to age, three kinds of equations were considered to have little statistical difference. Therefore, the Chapman-Richards equation was chosen for modeling on the national level. Thirtyyears was used as the base age, which is an important factor for estimating the site index curves. In the results, a more varied range of site index family curves with 6-18 was developed for Pinus densiflora, and with 6-22 for Chamaecyparis obtusa. As the new site index curves indicated influences on growth of Pinus densiflora and Chamaecyparis obtusa, a reasonable forest management plan will be possible in the future for Jeolla-do.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.4
• /
• pp.577-584
• /
• 2021

Electrical energy is an essential component in present societies, which is an important basis for our technological society. In the design of new power infrastructure, it is important to consider the psychological aspects of how our culture considers and aspects its development as an integral component of the community environment. The construction of new high voltage overhead transmission lines has become a controversial issue for public policy of government due to social opposition. The members of community are concerned about how these power lines may have an impact on their lives, basically caused by their effects on health and safety. The landscape and visual impact is one of the most impact that can be easily perceived for local community. The computer 3D simulation of new landscape is illustrated by a real life use corresponding to the selection of the power line route with least observability for local community. This paper used ArcGIS(geographic information system tool) for planning, survey, basic route and detailed route, route for implementation of transmission line corridor. Also, the paper showed the map of natural environment, living environment, safety and altitude using database of power line corridor, and transmission siting model was developed by this study. The suggested landscape of computer simulation with lowest visibility on a power line zone can contribute to reducing oppositions of local community and accelerating the construction of new power lines.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.6
• /
• pp.591-598
• /
• 2020

The all revision of the Road Name Address Act, which contains the contents to be used by expanding the road name address as a means of indicationg the location, has been resloved by the National Assembly. Addresses will be assigned to large-sized facilities (3D mixed-use complex spaces). Here, the 3D (Three-dimensional) address is assigned an indoor path section in the inner passage, dividing the section at intervals. The 3D address will be built on the address information map. For 3D address, data should be built and managed for a 3D complex space(indoor space). Therefore, in this study, the object of the 3D address is defined based on the address conceptual model defined in the international standard, and the 3D address data model is proposed based on IndoorGML. To this, it is proposed as a method of mapping the Core and Navigation module of IndoorGML so that the entity of the 3D address can be expressed in IndoorGML. This study has a limitation in designing a 3D address data model only, but it is meaningful that it suggested a standard for constructing 3D address data in the future.

• Korean journal of applied entomology
• /
• v.60 no.1
• /
• pp.79-90
• /
• 2021

Landscape composition and structure are important factors determining biological diversity including pests and natural enemires in agricultural ecosystem. This study was conducted to indentify effect of landscape composition on occurrence of lepidopteran pest population in Geochang, Gyoungdnam. For this, orchard characteristics and management practices were surveyed in 80 conventional apple orchards in Geochang, Korea, along with the monitoring of pest population densities. The landscape features of each surveyed orchard also obtained by extracting information from the public-service map. Grapholita molesta was the most dominat and damaging pest followed by Phyllonorycter ringoniella and Carposina sasakii in trap catches. Adoxophyes paraorana occurrences were low. Farmers spray insecticides and fungicides ap. 12.4 times per year respectively while acaricides were sprayed 2.4 times. Major landscape features such as surrounding apple orchard or paddy field did not influence the pest populations but presence of plum, peach, wild peach, graph, and even abandoned orchards significantly resulted in higher pest population mostly on G. molesta. C. sasakii population was higher in orchards with grape, peach, and P. ringoniella with peach, grape, abandoned orchards and jujube. Results highlight the need of landscape management not only for the rural amenity but also for increasing functional diversity of agroecosystem as well as reducing pest population.

• Food Science and Industry
• /
• v.51 no.3
• /
• pp.209-217
• /
• 2018

Delphi technique is widely used to develop consensus on group opinion. It is important to identify the strategic technologies and evaluate technology level for the establishment of national R&D policy to upgrade technology level. The aim of this article was to reflect on Food Safety technology level by using Delphi methodology. And, competitiveness of patents and journal articles is evaluated for Korea, USA, Japan, China and EU. As a result, USA is the most competitive country for all technology categories. The average technology level of Korea was 79.5% of world-top coungry and average technological gap was 6.1 years. Korea is grouped in middle-lower class for overall food safety technology level. However, there are some variances among the level of technologies. As a result of this study, food safety research management needs to expand R&D investment and training of food safety specialist. The results of this research can be utilized to establish a road map for transportation R&D and plans.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_1
• /
• pp.1277-1290
• /
• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.2
• /
• pp.62-73
• /
• 2022

As the competition among the autonomous vehicle (AV, here after) developers are getting fierce, Korean government has been supporting developers by deregulating safety standards and providing financial subsidies. Recently, some OEMs announced their plans to market Lv3 and Lv4 automated driving systems. However, these market changes raised concern among public road management sectors for monitoring road conditions and alleviating hazardous conditions for AVs and human drivers. In this regards, the authors proposed a methodology for monitoring road infrastructure to identify hazardous factors for AVs and categorizing the hazards based on their level of impact. To evaluate the degrees of the harm on AVs, the authors suggested a methodology for managing road hazard factors based on vehicle performance features including vehicle body, sensors, and algorithms. Furthermore, they proposed a method providing AVs and road management authorities with potential risk information on road by delivering them on the monitoring map with node and link structure.

• Korean Journal of Remote Sensing
• /
• v.38 no.2
• /
• pp.167-177
• /
• 2022

In order to obtain satellite image products using the image transmitted to the ground station after capturing the satellite images, many image pre/post-processing steps are involved. During the pre/post-processing, when converting from level 1R images to level 1G images, geometric correction is essential. An interpolation method necessary for geometric correction is inevitably used, and the quality of the level 1G images is determined according to the accuracy of the interpolation method. Also, it is crucial to speed up the interpolation algorithm by the level processor. In this paper, we proposed a lightweight CNN-based interpolation method required for geometric correction when converting from level 1R to level 1G. The proposed method doubles the resolution of satellite images and constructs a deep learning network with a lightweight deep convolutional neural network for fast processing speed. In addition, a feature map fusion method capable of improving the image quality of multispectral (MS) bands using panchromatic (PAN) band information was proposed. The images obtained through the proposed interpolation method improved by about 0.4 dB for the PAN image and about 4.9 dB for the MS image in the quantitative peak signal-to-noise ratio (PSNR) index compared to the existing deep learning-based interpolation methods. In addition, it was confirmed that the time required to acquire an image that is twice the resolution of the 36,500×36,500 input image based on the PAN image size is improved by about 1.6 times compared to the existing deep learning-based interpolation method.