• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.150-160
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• 2005

In this study, the spatiotemporal surface temperature changes were analyzed in the Korean peninsula. The surface temperature variation was estimated using the split window method and NOAA/AVHRR data in 1991, 1995 and 2000. The ranges of differences in temperature between day time and night time were $3-15^{\circ}C$ around the peninsula. The differences in seasonal variations and yearly fluctuations in big cities were lower than those in rural areas and showed clearly the effects of the urbanization. The characteristics of urban heat affects were further determined based on the day and night time temperature comparison on Busan metropolitan area between these periods. Finally, the future use of this technology was suggested for the urban environmental planning.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.73-79
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• 2014

Visible light communication is a communication method using an LED having a high-speed ON / OFF rate data to be transmitted, it is used as a wireless high speed data transmission. VLC system evolves, the problem of basic research is intended to improve performance and ensure reliability of the communication. The nature of the visible light communication, communication is performed only in the reach of the light, which indicates a big difference by the emission angle of the light. Therefore, in this paper, in the case of indoor environments generally, with the attributes of the multiple LED is equipped, was applied to a MIMO (Multiple Input Multiple Output) communication system. and analyzed SNR performance and total power can be obtained on the reception side by changing the emission angle of the transmitter. As a result of the simulation was run against this, it was confirmed that there is a significant impact on the performance of BER and SNR performance by the emission angle of the transmitter.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.71-78
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• 2020

Recently, as the issue of gentrification emerges, it becomes important to understand the dynamics of local commercial district, which plays the important role for facilitating the local economy and building the community in a city. This paper attempts to provide the framework for systemically analyzing and understanding the local commercial district. Then, this paper empirically analyzes the patterns of sales and flow of floating population by focusing on two representative local commercial districts in Seoul. In addition, the floating population data from telecommunication bases is further modeled with Markov chain for systemically understanding the local commercial districts. Finally, the transition patterns and consumption amounts of floating population are comprehensively analyzed for providing the implications on the evolutions of local commercial districts in a city. We expect that findings of our study could contribute to the economic growth of local commercial district, which could lead to the continuous development of city economy.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.133-143
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• 2012

The purpose of this study is to investigate the characteristics of urban heat island considering urban space at nighttime. We used to analyze landuse and landcover data of 1:1,000 scale, DTM, and surface temperature extracted ASTER image satellite of nighttime. According to the analytical results, heat intensity in single-family residential is higher than that in industrial area, public facility area, and commercial area because the anthropogenic heat by energy consumption is released. Likewise, the temperature difference were big in the buildings of industrial area depending on operating hours. Meanwhile, green and river area had cooling impacts mitigating the urban heat island. Therefore, we have to mitigate heat intensity through constructing green space and waterfront area. As mentioned above, we think that the results of this study will be used as base data for effective spatial planning when formulating development planning to mitigate urban heat island at nighttime.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.15-28
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• 2016

This paper proposes a system recommending spatial information what user wants with collecting and analyzing tweets around the user's location by using the GPS information acquired in mobile. This system has built an emotion dictionary and then derive the recommendation score of morphological analyzed tweets to provide not just simple information but recommendation through the emotion analysis information. The system also calculates distance between the recommended tweets and user's latitude-longitude coordinates and the results showed the close order. This paper evaluates the result of the emotion analysis in a total of 10 areas with two keyword 'Restaurants' and 'Performance.' In the result, the number of tweets containing the words positive or negative are 122 of the total 210. In addition, 65 tweets classified as positive or negative by analyzing emotions after a morphological analysis and only 46 tweets contained the meaning of the positive or negative actually. This result shows the system detected tweets containing the emotional element with recall of 38% and performed emotion analysis with precision of 71%.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.913-924
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• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.

• Journal of the Economic Geographical Society of Korea
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• v.7 no.1
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• pp.97-115
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• 2004

The purpose of this study is to investigate the spatial pattern of retail services and the consumer behaviors. For the purpose we select Jeju Island as the study area, because it retains relatively little distorted retail service systems by it's locational isolation. The retail service systems comprise three types: large-scale modern marts, conventional markets, and periodic markets. This study attempts to examine the interrelationships between these three different types, of retail services, and to figure out the spatial characteristics of consumer behaviors for each of them. We performed questionnaire surveys for getting the data of consumer behaviors. We applied several statistical methods to analyze the survey data. Most of retail services are located in two urban centers, Jeju City and Seoguipo City. We found that the locations of retail services are determined strongly by population size. The selection of market type and the location to go for shopping are related strongly with the types of goods. However, there is a wide difference in the consumer behaviors according to the consumer's socio-economic characteristics. Young wives tend to go shopping to large-scale marts in Jeju City which is the higher level central place, while old wives go shopping to conventional markets and periodic markets. They also show different shopping behaviors according to the household income levels. Low income groups prefer to go conventional markets located near to their residence, middle income groups go to large-scale marts in Jeju, and high income group go out of the Jeju Island. However, the consumer behavior does not show big difference according to the size of family. There are also no difference in the selection for shopping location according to the consumer's resident locations.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.24-35
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• 2019

In this study, a hotspot analysis was conducted to suggest a new method for interpreting soil heavy-metal contamination data of abandoned metal mines according to statistical significance level. The spatial autocorrelation of the data was analyzed using the Getis-Ord $Gi{\ast}$ statistic in order to check whether soil heavy metal contamination data showing abnormal values appeared concentrated or dispersed in a specific space. As a result, the statistically significant data showing abnormal values in the mine area could be classified as follows: (1) the contamination degree and the hotspot value (z-score) were both high, (2) the contamination degree was high but the z-score was low, (3) the contamination degree was low but the z-score was high and (4) the contamination degree and the z-score were both low. The proposed method can be used to interpret the soil heavy metal contamination data according to the statistical significance level and to support a rational decision for soil contamination management in abandoned mines.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.48-71
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• 2024

Typhoons are representative oceanic and atmospheric phenomena that cause interactions within the Earth's system with diverse influences. In recent decades, the typhoons have tended to strengthen due to rapidly changing climate. The 2022 revised science curriculum emphasizes the importance of teaching-learning activities using advanced science and technology to cultivate digital literacy as a citizen of the future society. Therefore, it is necessary to solve the temporal and spatial limitations of textbook illustrations and to develop effective instructional materials using global-scale big data covered in the field of earth science. In this study, according to the procedure of the PDIE (Preparation, Development, Implementation, Evaluation) model, the inquiry activity data was developed to visualize the track of the typhoon using the image data of GK-2A. In the preparatory stage, the 2015 and 2022 revised curriculum and the contents of the inquiry activities of the current textbooks were analyzed. In the development stage, inquiry activities were organized into a series of processes that can collect, process, visualize, and analyze observational data, and a GUI (Graphic User Interface)-based visualization program that can derive results with a simple operation was created. In the implementation and evaluation stage, classes were conducted with students, and classes using code and GUI programs were conducted respectively to compare the characteristics of each activity and confirm its applicability in the school field. The class materials presented in this study enable exploratory activities using actual observation data without professional programming knowledge which is expected to contribute to students' understanding and digital literacy in the field of earth science.