• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.179-193
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• 2019

Landslides are one of the most damaging geological hazards worldwide, threating both humans and property. Hence, there have been many efforts to prevent landslides and mitigate the damage that they cause. Among such efforts, there have been many studies on mapping landslide susceptibility. Geographic information system (GIS)-based techniques have been developed and applied widely, and are now the main tools used to map landslide susceptibility. We reviewed the status of landslide susceptibility mapping using GIS by number of papers, year, study area, number of landslides, cause, and models applied, based on 776 articles over the last 20 years (1999-2018). The number of studies published annually increased rapidly over time. The total study area spanned 65 countries, and 47.7% of study areas were in China, India, South Korea, and Iran, where more than 500 landslides, 27.3% of all landslides, have occurred. Slope (97.6% of total articles) and geology (82.7% of total articles) were most often implicated as causes, and logistic regression (26.9% of total articles) and frequency ratio (24.7% of total article) models were the most widely used models. We analyzed trends in the causes of and models used to simulate landslides. The main causes were similar each year, but machine learning models have increased in popularity over time. In the future, more study areas should be investigated to improve the generalizability and accuracy of the results. Furthermore, more causes, especially those related to topography and soil, should be considered and more machine learning models should be applied. Finally, landslide hazard and risk maps should be studied in addition to landslide susceptibility maps.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.219-231
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• 1996

The aim here is to analyse the system of description of GIS in all of the high school textbooks passed with the official approval, to find the degree to which teachers understand about GIS, and to consider the present condition of GIS instruction. Most of the authors of textbooks generally underestimate importance of GIS, and there is difference among their awareness. In the system of description of GIS, there are only a few kinds of textbooks in which explanation of GIS is made coherently from the purpose of instruction aim through the chapter summary and to overall test in both of the Korean Geography and the World Geography. This trend is due to the degree of distribution of the GIS specialists in writing a textbook while the other texts books shows just a brief introduction of GIS concept. Although there is the limit for teachers to study how to teach GIS due to its very technological aspect as well as few previous training and teacher's guide. Thus it is evident that about a half of teachers who responded taught high school students without a knowledge on GIS, and a few of them even never referred to that concept. These facts may negatively affect the status of a geography in the society of information. For the solution of these issues, it is considered how to repair the description system and its contents. Besides, the variation among textbooks is reduced at the further revision of the 7th curriculum. And the printed matters of GIS are sufficiently provided for the teachers to use as their teaching aids. It is desirable that the GIS instruction models should be further developed for college education, and the programs for the on-the-job teachers training should be arranged. Besides, the previous training for the on-the-job teachers should be achieved more practically with enough time before the revision of curriculum.

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

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.79-101
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• 2023

The current status of local road pavement management in Jeollabuk-do only relies on the accomplishments of the site construction company's pavement repair and is only managed through Microsoft Excel and word documents. Furthermore, the budget is irregular each year. Accordingly, a systematic maintenance plan for local roads is necessary. In this paper, data related to road damage and road environment were collected and processed to derive possible areas which could suffer from road damage. The effectiveness of the methodology was reviewed through the on-site inspection of the area. According to the Ministry of Land, Infrastructure and Transport, in 2018, the number of damages on general national roads were about 47,000. In 2019, it reached around 38,000. Furthermore, the number of lawsuits regarding the road damages were about 93 in 2018 and it increased to 119 in 2019. In the case of national roads, the number of damages decreased compared to 2018 due to pavement repairs. To measure the priorities in maintenance of local roads at Jeollabuk-do, data on maintenance history, local port hole occurrence site, overlapping business section, and emergency maintenance section were transformed into data. Eventually, it led to improvements in maintenance of local roads. Furthermore, spatial data were constructed using various current status data related to roads, and finally the data was processed into a new form that could be utilized in machine learning and predictions. Using the spatial data, areas requiring maintenance on pavement were predicted and the results were used to establish new budgets and policies on road management.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.201-207
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• 2020

In this study, the practicality of unmanned aerial vehicle photography information was identified. Therefore, a total of four consecutive surveys were conducted on the field-level survey areas among the areas subject to photography using unmanned aerial vehicles, and the changes in crop conditions were analyzed using pictures of unmanned aerial vehicles taken during each survey. It is appropriate to collect and utilize photographic information by directly taking pictures of the survey area according to the time of the on-site survey using unmanned aerial vehicles in the field layer, which is an area where many changes in topography, crop vegetation, and crop types are expected. And it turned out that it was appropriate to utilize satellite images in consideration of economic and efficient aspects in relatively unchanged rice paddies and facilities. If the survey area is well equipped with systems for crop cultivation, deep learning can be utilized in real time by utilizing libraries after obtaining photographic data for a certain area using unmanned aircraft in the future. Through this process, it is believed that it can be used to analyze the overall crop and shipment volume by identifying the crop status and surveying the quantity per unit area.