• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1761-1775
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• 2022

Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.60.1-60.1
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• 2015

We present the current operation status of StarDB web services by showing its user access statistics. The StarDB web services started its operation in late November, allowing world-wide users to access results of new variability analysis for Northern Sky Variability Survey light curves. New analysis results of various time-series data have been added to the StarDB services. Importantly, our services have supported a simple cone search, which is an internationally well-defined catalog search interface in the international Virtual Observatory systems. We have collected user access statistics such as how users find our analysis data since its operation in later November. We expect our analysis of the StarDB operation to help Korean community members who plan and operate their own web services preparing for a future era of big survey data.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.3 no.2
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• pp.81-89
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• 1999

This study estimates the correlation dimensions of the land-sea breeze phenomenon, that has a clear diurnal cycle, in order to gain a more detailed understanding of this phenomenon. The data adopted include north-south wind velocity component(v) and temperature(T) time series that were observed at Kimhae Airport and Inje University over a period of 5 days, from the 4th to the 8th of August, 1994. The embedding phase space of the time series were reconstructed from 2 to 14 dimensions, and the correlation dimensions of the attractors were then estimated. The results show that the land-sea breeze phenomenon exhibits a deterministic chaos with non-integer correlation dimension values between 2 and 3. Accordingly, 3 is the minimum number of independent variables required to model the dynamics of the landsea breeze phenomenon in the Kimhae area. Since the saturated embedding dimension, when the correlation dimension remains unchanged, is larger for the wind velocity v-component than for temperature, this indicates that wind velocity is susceptible to topology.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.14-28
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• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.32-39
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• 2015

In this paper, We propose the futuristic map using variety technology of advanced ICT-based. The futuristic maps are expected to developed into a new format of user participation to express the results in various formats through the understanding and interpretation of the facts and phenomena of tangible and intangible that exist in the real world. In the future, the map is expected to be developed into form of a new paradigm map made in real time that economy, industry, the collection of information necessary for everyday life, processing, usage, analysis, distribution and sharing. In this paper, we provide a real-time personalized contents to digitize the information of the real space based on the concept of map, databases, spatial analysis and describes the key technologies that characterized by the representation of time-series data by analyzing and prediction every field macro phenomena of society, economy, culture and etc. And we establish the concepts of the 'New Paradigm Map' for future creative economy.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.52.1-52.1
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• 2015

We have recently installed SQUEAN on the 82 inch telescope at the McDonald Observatory, USA. This instrument consists of an ANDOR CCD camera, a focal reducer, an electronic box, an auto guiding system and a new filter wheel which holds up to 20 filters. Currently the filter wheel is equipped with Johnson-Cousins BVRI filters, SDSS rizY and isiz filters, and 50nm medium band pass filters (M625(625nm), M675(675nm), M725(725nm), M775(775nm), M825(825nm), M875(875nm), M925s(925nm), M975(975nm), and M1025(1025nm)). Our medium band pass filter system is suitable with SED fitting. Filter transformation methods are essential for time-domain observations including transient objects, e.g., supernovae, variable stars, and solar system bodies. In this work, we develop a series of equations to convert the open clusters photometry data within these filter systems.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.70.2-70.2
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• 2013

We present collections of optical photometry for a pre-main sequence star HBC 722. It showed large amplitude optical outburst (${\Delta}V=4.7$ mag) in 2010 and classified as a FU Orionis type object. We have been observing HBC 722 from 2011 April to 2013 May, using Camera for QUasars in EArly uNiverse (CQUEAN) attached to the 2.1 m Otto Struve telescope at the McDonald Observatory. Time-series monitoring data (minute-scale interval) were obtained in SDSS r, i and z bands to see short-scale behaviors as well as trace the long-term brightness changes after the eruption in 2010. Interestingly, it started to brighten from 2011 early summer and became brighter than the first outburst peak in our 2013 May observation. We expect that the recovering phase would result from re-increase of disk accretion rate, might attribute to distinctive short-scale color features. In this presentation, we report long- and short-timescale optical behaviors of HBC 722 in the post-outburst phase.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.773-779
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• 2019

We developed the automatic ground deformation monitoring system using Sentinel-1 satellites which is operating by European Space Agency (ESA) for the Korea Peninsula's ground disaster monitoring. Ground deformation occurring over a long-term period are difficult to monitoring because it occurred in a wide area and required a large amount of satellite data for analysis. With the development of satellites, the methods to regularly observe large areas has been developed. These accumulated satellite data are used for time series ground displacement analysis. The National Disaster Management Research Institute (NDMI) established an automation system for all processes ranging from acquiring satellite observation data to analyzing ground displacement and expressing them. Based on the system developed in this research, ground displacement data on the Korean Peninsula can be updated periodically. In the future, more diverse ground displacement information could be provided if automated small regional analysis systems, multi-channel analysis method, and 3D analysis system techniques are developed with the existing system.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.4
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• pp.13-30
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• 2020

This study aims to analyze the qualitative and quantitative effects of environmental policies in terms of green space management using logistic regression model(LRM). Landsat satellite imageries in 1985, 1992, 2000, 2008, and 2015 are classified using a hybrid-classification method. Based on these classified maps, logistic regression model having a deforestation tendency of the past is built. Binary green space change map is used for the dependent variable and four explanatory variables are used: distance from green space, distance from settlements, elevation, and slope. The green space map of 2008 and 2015 is predicted using the constructed model. The conservation effect of Ulsan's environmental policies is quantified through the numerical comparison of green area between the predicted and real data. Time-series analysis of green space showed that restoration and destruction of green space are highly related to human activities rather than natural land transition. The effect of green space management policy was spatially-explicit and brought a significant increase in green space. Furthermore, as a result of quantitative analysis, Ulsan's environmental policy had effects of conserving and restoring 111.75㎢ and 175.45㎢ respectively for the periods of eight and fifteen years. Among four variables, slope was the most determinant factor that accounts for the destruction of green space in the city. This study presents logistic regression model as a way of evaluating the effect of environmental policies that have been practiced in the city. It has its significance in that it allows us a comprehensive understanding of the effect by considering every direct and indirect effect from other domains, such as air and water, on green space. We conclude discussing practicability of implementing environmental policy in terms of green space management with the focus on a non-statutory plan.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.117-124
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• 2007

This paper describes methodology that enables animators to create the facial expression animations and to control the facial expressions in real-time by reusing motion capture datas. In order to achieve this, we fix a facial expression state expression method to express facial states based on facial motion data. In addition, by distributing facial expressions into intuitive space using LLE algorithm, it is possible to create the animations or to control the expressions in real-time from facial expression space using user interface. In this paper, approximately 2400 facial expression frames are used to generate facial expression space. In addition, by navigating facial expression space projected on the 2-dimensional plane, it is possible to create the animations or to control the expressions of 3-dimensional avatars in real-time by selecting a series of expressions from facial expression space. In order to distribute approximately 2400 facial expression data into intuitional space, there is need to represents the state of each expressions from facial expression frames. In order to achieve this, the distance matrix that presents the distances between pairs of feature points on the faces, is used. In order to distribute this datas, LLE algorithm is used for visualization in 2-dimensional plane. Animators are told to control facial expressions or to create animations when using the user interface of this system. This paper evaluates the results of the experiment.