• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2281-2293
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• 1998

Spatial objects in the space II odd hale been changed bl eitber non-spiltial operations or spatial operations. For example, their states arc changed by the following operation: changing their owners, changing their owner's address, installing new constructions, changing precincts, splitting, and merging, The conventional geographic information system(GIS), however, did not also manage their histoncal information cecause it handles the snapshot image of spatial ohjects in the world. In this paper we therelore propose a spatiotemporal data model which is ahle to not un]y manage the historical information of spatial objects but also, support their historical intemlgation by extending a time dimension and a historical pointer for SDE(Spatial Database Engine) spatial data model. Finally, the proposed spatiotemporal data model using a layered time extension are going to contribute to manage the history of spatial objects in the world and retrieve them.

• Journal of Environmental Impact Assessment
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• v.18 no.6
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• pp.321-330
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• 2009

Spatiotemporal changes in the thermal environment in a large city, Seoul, Korea were analyzed using a thermal index, perceived temperature (PT), to standardize the weather conditions. PT is a standard index for the thermal balance of human beings in thermophysiological environment. For the analysis of PT, the data from long-term monitoring and intensive observations in and around the inner-city stream called 'Cheonggye' in Seoul, were compared with a reference data from the Seoul weather station. Long-term data were monitored by installing two automatic weather stations at 66m (S1) and 173m (S2) away from the center of the stream. Through the analysis of the data during the summer of 2006 and intensive observation periods, it was revealed that the stream's effects on the PT extended up to the distance of the S1 site. In winter, the increase of the PT between pre- and post-restoration was stronger at S1, which was nearer than S2 from the stream. These results suggest that PT can be used as an effective model in analyzing the changes of the thermal environment in relation with the changes of water surface areas.

• Journal of Environmental Impact Assessment
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• v.6 no.1
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• pp.55-66
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• 1997

This study summarizes the use of satellite data to detect the change of southwestern coastal wetlands in Korea. The images used for this study were two Landsat Thematic Mapper(TM) images (June 12, 1984 & June 2, 1992). TM images were used to classify such different types of wetlands as aquatic bed, nonaquatic bed and other land use in the region. Then it, was possible to a) determine the status of wetlands using image classification products, and b) detect the changes of various types of wetlands influenced by both human and nature. The results from spatiotemporal analysis showed that approximately 120 lad of coastal wetlands were lost from the year of 1984 to 1992. 71 % of the lost wetlands were converted to the reclaimed land. This loss of wetlands has been causing the profound environmental impacts. It has been successfully proved that satellite data are very effective for spatiatemporal change analysis, especially for that of coastal wetlands.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.178-185
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• 2023

Rapid urbanization and advancements in technology have led to a surge in the number of automobiles, resulting in frequent traffic accidents, and consequently, an increase in human casualties and economic losses. Therefore, there is a need for technology that can predict the risk of traffic accidents to prevent them and minimize the damage caused by them. Traffic accidents occur due to various factors including traffic congestion, the traffic environment, and road conditions. These factors give traffic accidents spatiotemporal characteristics. This paper analyzes traffic accident data to understand the main characteristics of traffic accidents and reconstructs the data in a time series format. Additionally, an LSTM-MLP based model that excellently captures spatiotemporal characteristics was developed and utilized for traffic accident prediction. Experiments have proven that the proposed model is more rational and accurate in predicting the risk of traffic accidents compared to existing models. The traffic accident risk prediction model suggested in this paper can be applied to systems capable of real-time monitoring of road conditions and environments, such as navigation systems. It is expected to enhance the safety of road users and minimize the social costs associated with traffic accidents.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.81-88
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• 2004

GIS (geographic information system) applications increasingly require the representation of geospatial objects with fuzzy extent and querying of time-varying information. In this paper, we Introduce a FSTDB (fuzzy spatiotemporal database) to represent and manage states and events causing changes of dynamic fuzzy objects using fuzzy set theory. We also propose the algorithms for the operators to be included in a GIS to make it able to answer queries depending on fuzzy predicates during a time interval and a method to identify the development process of objects during a certain period based on the designed database. They can be used in application areas handling time-varying geospatial data, including global change (as in climate or land cover change) and social (demographic, health, ect.) application.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.634-636
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• 2023

Surveillance systems play a pivotal role in ensuring the safety and security of various environments, including public spaces, critical infrastructure, and private properties. However, detecting abnormal human behavior in lowlight conditions is a critical yet challenging task due to the inherent limitations of visual data acquisition in such scenarios. This paper introduces a spatiotemporal framework designed to address the unique challenges posed by low-light environments, enhancing the accuracy and efficiency of human abnormality detection in surveillance camera systems. We proposed the pre-processing using lightweight exposure correction, patched frames pose estimation, and optical flow to extract the human behavior flow through t-seconds of frames. After that, we train the estimated-action-flow into autoencoder for abnormal behavior classification to get normal loss as metrics decision for normal/abnormal behavior.

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.435-436
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• 2012

실내에서는 GPS 신호를 수신할 수 없으므로 자신의 위치를 알 수 없다. 최근에 이러한 문제점을 해결하기 위하여 와이파이 엑세스 포인트(AP)를 이용한 실내 위치 정보 수집 방법들이 제안되고 있다. 본 논문에서는 AP를 이용한 이동체의 이동경로를 저장하는 시공간 데이터 모델 방법을 제안한다.

• Journal of Wetlands Research
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• v.14 no.2
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• pp.303-315
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• 2012

This study developed a wetland inventory describing the characteristics and change of Nakdong estuary wetland ecosystem. The data which are used to develop the inventory are Landsat TM(April 1, 1986; June 23, 1987; June 18, 1997), Kompsat(Jan. 12, 2008) and LiDAR(March 1, 2009) images and published monitoring data of Busan metropolitan city. The developed inventory was utilized for the classification of wetland cover, the spatiotemporal analysis of wetland and landscape pattern, the distribution of benthos species etc. Furthermore, the developed 3 dimensional wetland map showed a better way to delineate wetland boundary and understand wetland dynamics. Considering these results, it's concluded that it is possible to use the similar techniques for the development of wetland inventory in Korea.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.113-130
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• 2004

Most multimedia data contain text to emphasize the meaning of the data, to present additional explanations about the situation, or to translate different languages. But, the left makes it difficult to reuse the images, and distorts not only the original images but also their meanings. Accordingly, this paper proposes a support vector machines (SVMs) and spatiotemporal restoration-based approach for automatic text detection and removal in video sequences. Given two consecutive frames, first, text regions in the current frame are detected by an SVM-based texture classifier Second, two stages are performed for the restoration of the regions occluded by the detected text regions: temporal restoration in consecutive frames and spatial restoration in the current frame. Utilizing text motion and background difference, an input video sequence is classified and a different temporal restoration scheme is applied to the sequence. Such a combination of temporal restoration and spatial restoration shows great potential for automatic detection and removal of objects of interest in various kinds of video sequences, and is applicable to many applications such as translation of captions and replacement of indirect advertisements in videos.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.