• Spatial Information Research
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• v.18 no.1
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• pp.77-87
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• 2010

Spatio-temporal join operators are essential to the management of spatio-temporal data such as moving objects. For example, the join operators are parts of processing to analyze movement of objects and search similar patterns of moving objects. Various studies on spatio-temporal join queries in outdoor space have been done. Recently with advance of indoor positioning techniques, location based services are required in indoor space as well as outdoor space. Nevertheless there is no one about processing of spatio-temporal join query in indoor space. In this paper, we introduce continuous spatio-temporal self-join queries in indoor space and propose a method of processing of the join queries over stream data of moving objects. The continuous spatio-temporal self-join query is to update the joined result set satisfying spatio-temporal predicates continuously. We assume that positions of moving objects are represented by symbols such as a room or corridor. This paper proposes a data structure, called Candidate Pairs Buffer, to filter and maintain massive stream data efficiently and we also investigate performance of proposed method in experimental study.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.21-31
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• 2012

Recently, according to the development of ubiquitous computing technology, the efficient management of locations of moving objects is increasing rapidly in various fields. However, MODBMS and DSMS can not support the efficient real-time management of spatio-temporal stream data of moving objects. Therefore, this paper designed and implemented a spatio-temporal DSMS which can support the efficient real-time management of spatio-temporal stream data of moving objects. Especially, to develop the spatio-temporal DSMS, we extended STREAM of Stanford University and used GEOS that supports spatial data types and spatial operators of OGC. Finally, this paper proved the efficiency of the spatio-temporal DSMS by applying it to the real-time monitoring field which requires the real-time management of spatio-temporal stream data of moving objects.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.873-884
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• 2003

So far, significant achievements have been studied on the development of models for spatial and spatiotemporal objects with indeterminate boundaries which are found in many applications for geographic analysis and image understanding. Therefore, in this paper we propose the spatiotemporal data model which is applicable for spatial and spatiotemporal objects with uncertainty. Based on this model, we defined topological relationships among the indeterminate spatiotemporal objects and designed the algorithm for the operations. For compatibility with existing spatial models, the proposed model has been designed by extending the spatiotemporal object model which is based on the open GIS specification. We defined indeterminate spatial objects, such as the objects whose position and the shape change discretely over time, and the objects whose shape changes continuously as well as the position. We defined topological relationships among these objects using the extended 9-IM. The proposed model can be efficiently applied to the management systems of natural resource data, westher information, geographic information. and so on.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.839-852
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• 2014

This study analyzed the applicability of a rainfall downscaling algorithm in space-time multifractal framework (RDSTMF) in Korean Peninsula. To achieve this purpose, the 8 heavy rainfall events that occurred in Korea during the period between 2008 and 2012 were analyzed using the radar rainfall imagery. The result of the analysis indicated that there is a strong tendency of the multifractality for all 8 heavy rainfall events. Based on the multifractal exponents obtained from the analysis, the parameters of the RDSTMF were obtained and the relationship between the average intensity of the rainfall events and the parameters of the RDSTMF was developed. Based on this relationship, the synthetic space-time rainfall fields were generated using the RDSTMF. Then, the generated synthetic space-time rainfall fields were compared to the observation. The result of the comparison indicated that the RDSTMF can accurately reproduce the multifractal exponents of the observed rainfall field up to 3rd order and the cumulative density function of the observed space-time rainfall field with a reasoable accuracy.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.43-56
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• 2002

Most of works have been performed on representation of spatiotemporal objects from various points of view. Most of them represent spatiotemporal objects using approaches from GIS, temporal databases, object-oriented databases or data type. Spatiotemporal objects can be classified as objects whose position and shape changes discretely over time, objects whose position changes continuously and objects whose shape changes continuously as well as position. Previous works on spatiotemporal model have focused on only one of them. In this paper, we propose a spatiotemporal model that can represent three types of objects in Euclidean plan. For this purpose, we represent both discrete and continuous moving objects by defining temporal model extended from valid time and by defining relationship between two consecutive versions of objects. The proposed spatiotemporal object model is based on open GIS specification so that it has compatibility with existing spatial data model.

• Journal of the Korean Geographical Society
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• v.47 no.2
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• pp.193-207
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• 2012

This study discussed characteristics of Shindu Coastal Dune as habitat, and relationship between geodiversity and biodiversity. It was identified spatio-temporal variation of incoming nutrients depended on geomorphic differences of foredunes. The main incoming path of nutrients into coastal dune was considered as influx with movement of wind blown sands from the beach and tidal f lat. Concentrations of Na, Mg, K, Ca, and P in blown sands were compared. Concentrations of Na, Mg, and K showed high and irregular pattern in favorable condition of influx of blown sand. So these nutrients were related with geomorphic characteristics of foredunes. However, Na was also influenced by other factor such as salt spray. P was independent from effects of sea water and blown sands. In the case of Ca, a large coastal dune system rather than localized forms of foredunes made differences in the variation. Due to differences in spatio-temporal variation of nutrients, patterns of major vegetation could be inferred to appear differently. This study shows geomorphic dynamics of coastal dunes as habitat, and will provide information for coastal dune management and for understanding biological distribution and growth pattern in coastal dune.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.4
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• pp.37-50
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• 2003

In the paper, we describe the query extension techniques for spatiotemporal query functionalities on object-relational DBMS. The spatial objects in real world change the shapes over time. Spatiotemporal databases support to manage a temporal dimension as well as a spatial dimension for history of the objects. The proposed techniques can make conventional object-relational databases to support spatiotemporal databases system by the implementation and inheritance of abstract data types. We define and implement spatial and temporal classes as superclass. And, spatiotemporal classes inherits and extends the classes. The proposed extensions make it easy that conventional database systems not only are transformed into the spatiotemporal database systems, but also do not need to be changed to support spatiotemporal applications.

• Water for future
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• v.57 no.6
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• pp.16-24
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• 2024

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.79-98
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• 2018

The purpose of this study is to suggest a model analysing spatio-temporal characteristics of the civil complaints for the officially assessed land price based on big data mining. Specifically, in this study, the underlying reasons for the civil complaints were found from the spatio-temporal perspectives, rather than the institutional factors, and a model was suggested monitoring a trend of the occurrence of such complaints. The official documents of 6,481 civil complaints for the officially assessed land price in the district of Jung-gu of Incheon Metropolitan City over the period from 2006 to 2015 along with their temporal and spatial poperties were collected and used for the analysis. Frequencies of major key words were examined by using a text mining method. Correlations among mafor key words were studied through the social network analysis. By calculating term frequency(TF) and term frequency-inverse document frequency(TF-IDF), which correspond to the weighted value of key words, I identified the major key words for the occurrence of the civil complaint for the officially assessed land price. Then the spatio-temporal characteristics of the civil complaints were examined by analysing hot spot based on the statistics of Getis-Ord $Gi^*$. It was found that the characteristic of civil complaints for the officially assessed land price were changing, forming a cluster that is linked spatio-temporally. Using text mining and social network analysis method, we could find out that the occurrence reason of civil complaints for the officially assessed land price could be identified quantitatively based on natural language. TF and TF-IDF, the weighted averages of key words, can be used as main explanatory variables to analyze spatio-temporal characteristics of civil complaints for the officially assessed land price since these statistics are different over time across different regions.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.28-36
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• 2010

Some context is characterized by a single event in computing environment, but many other contexts are determined by a lot of things which occur with a space and a time. The Realtime Sensor Network context-awareness service that interacts with the physical space can have property such as time. A methodology that is specified the relationship between the contexts and the service needs to be developed to Realtime context-awareness deal with spatio-temporal. In this paper, we propose an approach which should include spatio-temporal property in the context model, and verify its effectiveness using enhanced Petri-Net. The context-awareness service modeling of Realtime Sensor Network is discussed the properties of model such as basic Petri-Net, patterned Petri-Net, or Spatio-temporal Petri-Net. The proposed methodology demonstrated using an example that is SAEMANGUEM warming watching system. The use of Spatio-temporal Petri-Net will contribute not only to develop the application but also to model the spatio-temporal context awareness.