• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.39 no.4
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• pp.1-9
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• 2021

The purpose of this study was to determine the definition of traditional landscape and the appropriate English notation. To confirm the appropriate concept, the charter's relevant terminology was synthesised and the meaning of the vocabulary used in international studies was examined. ICOMOS The Charter on Historic Gardens(The Florebce Charter, 1981), ICOMOS-IFLA Document on Historic Urban Parks(New Delhi, 2017), and UNESCO Recommendation on The Historic Urban Landscape(Paris, 2011) were analysed to examine the concept, and the words describing definitions, space, objects, value, and activity were arranged. Big data was used to analyse the research literature related to overseas traditional landscapes. This study examined the characteristics of each word and examined the appropriate name for expressing the historic and cultural characteristics of landscape in research literature, which included traditional, historic, cultural, classical, vernacular, landscape-related gardens, parks, and landscape words related to historic culture. Consequently, the International Charter declared the suitability of 'historic' gardens and parks, as well as traditional landscape for expressing unique designs, composition technique, and ecological meaning of Korea, while historic landscape was deemed suitable for explaining gardens and parks in landscape history.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.98-105
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• 2022

It is essential for vertical smart farms that artificially grow crops in an enclosed space to properly utilize air environment facilities to create an appropriate growth environment. However, domestic vertical smart farm companies are creating a growing environment by relying on empirical data rather than systematic methods. Using IoT to create a growing environment based on systematic and precise monitoring can increase crop production yield and maximize profitability. This study aims to construct a monitoring system using IoT and to analyze the cause by demonstrating the imbalance of temperature environment, which is a significant factor in crop cultivation. 1) The horizontal temperature distribution of the multi-layer shelf was measured with different operating methods of LED and air conditioner. As a result, there was a temperature difference of "up to 1.7℃" between the sensors. 2) As a result of measuring the vertical temperature distribution, the temperature difference was "up to 6.3℃". In order to reduce this temperature gap, a strategy for proper arrangement and operation of air conditioning equipment is required.

• Journal of the Korean Regional Science Association
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• v.38 no.1
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• pp.21-32
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• 2022

The purpose of this study is two things. First, it is to develop and demonstrate a sharong taxi platform. To this end, the implications for platform development were derived by analyzing consumers' perceptions of existing taxi services using IPA. As a result, abnormal business activities and safe services in the maintenance area were found to be safe rides and easy rides in the key improvement area. Safety such as usage fee level and driver information provision were derived in the areas subject to improvement, and friendly response and internal and external cleanliness were derived in the areas of excessive investment. The second purpose of this study is to estimate the value given to users for sharing taxi service platforms using the CVM. As a result of estimating the value of the demonstration service of the shared taxi platform developed through this study, the WTP was 3,621 won/per household/per year when expanding throughout Gimhae-si, and 2,515 won/per household/per year. Compared to the willingness to pay for empirical services, only 69.5% of the willingness to pay for the spread project in Gimhae-si. This is the result of a combination of service spread to an unspecified number of people and concerns about service quality due to spatial expansion. This suggests that it is necessary to build data through continuous demonstration and to carefully build a roadmap for spread by upgrading services based on this.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.7
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• pp.217-224
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• 2022

Today, with the development of technology and industry, fire accidents in special buildings are increasing as special buildings increase. However, despite the rapid development of information and communication technology, human casualties are steadily occurring due to the underdeveloped and ineffective indoor fire alarm system. In this study, we confirmed that the existing indoor fire alarm system using acoustic alarm could not deliver a sufficiently large alarm to the in-room personnel. To improve this, we designed and implemented a fire alarm system using edge computing and beacons. The proposed improved fire alarm system consists of terminal sensor nodes, edge nodes, a user application, and a server. The terminal sensor nodes collect indoor environment data and send it to the edge node, and the edge node monitors whether a fire occurs through the transmitted sensor value. In addition, the edge node continuously generate beacon signals to collect information of smart devices with user applications installed within the signal range, store them in a server database, and send application push-type fire alarms to all in-room personnel based on the collected user information. As a result of conducting a signal valid range measurement experiment in a university building with dense lecture rooms, it was confirmed that device information was normally collected within the beacon signal range of the edge node and a fire alarm was quickly sent to specific users. Through this, it was confirmed that the "blind spot problem of the alarm" was solved by flexibly collecting information of visitors that changes time to time and sending the alarm to a smart device very adjacent to the people. In addition, through the analysis of the experimental results, a plan to effectively apply the proposed fire alarm system according to the characteristics of the indoor space was proposed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.217-226
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• 2022

In the view of the application of high-precision spatial information production, UAV (Umanned Aerial Vehicle)-Photogrammetry has a problem in that it lacks specific procedures and detailed regulations for quantitative quality verification methods or certification of captured images. In addition, test tools for UAV image quality assessment use only the GSD (Ground Sample Distance), not MTF (Modulation Transfer Function), which reflects image resolution and contrast at the same time. This fact makes often the quality of UAV image inferior to that of manned aerial image. We performed MTF and GSD analysis simultaneously using a siemens star to confirm the necessity of MTF analysis in UAV image quality assessment. The analyzing results of UAV images taken with different payload and sensors show that there is a big difference in σ_MTF values, representing image resolution and the degree of contrast, but slightly different in GSD. It concluded that the MTF analysis is a more objective and reliable analysis method than just the GSD analysis method, and high-quality drone images can only be obtained when the operator make images after judging the proper selection the sensor performance, image overlaps, and payload type. However, the results of this study are derived from analyzing only images acquired by limited sensors and imaging conditions. It is therefore expected that more objective and reliable results will be obtained if continuous research is conducted by accumulating various experimental data in related fields in the future.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.901-912
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• 2022

The frequency of disasters is increasing due to global climate change, and unusual heavy rains and rainy seasons are occurring in Korea. Periodic monitoring and rapid detection are important because these weather conditions can lead to drought and flooding, causing secondary damage. Although research using optical images is continuously being conducted to determine the waterbody, there is a limitation in that it is difficult to detect due to the influence of clouds in order to detect floods that accompany heavy rain. Therefore, there is a need for research using synthetic aperture radar (SAR) that can be observed regardless of day or night in all weather. In this study, using Sentinel-1 SAR images that can be collected in near-real time as open data, the UNet model among deep learning algorithms that have recently been used in various fields was applied. In previous studies, waterbody detection studies using SAR images and deep learning algorithms are being conducted, but only a small number of studies have been conducted in Korea. In this study, to determine the applicability of deep learning of SAR images, UNet and the existing algorithm thresholding method were compared, and five indices and Sentinel-2 normalized difference water index (NDWI) were evaluated. As a result of evaluating the accuracy with intersect of union (IoU), it was confirmed that UNet has high accuracy with 0.894 for UNet and 0.699 for threshold method. Through this study, the applicability of deep learning-based SAR images was confirmed, and if high-resolution SAR images and deep learning algorithms are applied, it is expected that periodic and accurate waterbody change detection will be possible in Korea.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.765-779
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• 2022

This study evaluates the accuracy in identifying the burned area in South Korea using multi-temporal data from Sentinel-2 MSI and Landsat 8/9 OLI. Spectral indices such as the Difference Normalized Burn Ratio (dNBR), Relative Difference Normalized Burn Ratio (RdNBR), and Burned Area Index (BAI) were used to identify the burned area in the March 2022 forest fire in Uljin. Based on the results of six indices, the accuracy to detect the burned area was assessed for four satellites using Sentinel-2 and Landsat 8/9, respectively. Sentinel-2 and Landsat 8/9 produce images every 16 and 10 days, respectively, although it is difficult to acquire clear images due to clouds. Furthermore, using images taken before and after a forest fire to examine the burned area results in a rapid shift because vegetation growth in South Korea began in April, making it difficult to detect. Because Sentinel-2 and Landsat 8/9 images from February to May are based on the same date, this study is able to compare the indices with a relatively high detection accuracy and gets over the temporal resolution limitation. The results of this study are expected to be applied in the development of new indices to detect burned areas and indices that are optimized to detect South Korean forest fires.