• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.269-281
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• 2016

The process of spatial big data, such as social media, is being paid more attention in the field of spatial information in recent years. This study, as an example of spatial big data analysis, analyzed the spatial and temporal distribution of Tweet data based on the location and time information. In addition, the characteristics of its spatial pattern by times were identified. Tweet data in Busan city are collected, processed, and analyzed to identify the characteristics of the temporal and spatial pattern. Then, the results of Tweet data analysis were compared with the characteristics of the land type. This study found that spatial pattern of tweeting in the city was associated with given time periods such as daytime and nighttime in both weekdays and weekends. The spatial distribution patterns of individual time periods were compared with the characteristics of the land for the spatially concentrated area. The results of this study showed that tweeted data would be related to different spatial distribution depending on the time, which potentially reflects the daily pattern and characteristics of the land type of urban area to some extent. This study presented the possible incorporation of social media data, e. g. Tweet data, into the field of spatial information. It is expected that there will be more advantage to use a variety of social media data in areas such as land planning and urban planning.

• Journal of Fisheries and Marine Sciences Education
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• v.23 no.3
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• pp.477-485
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• 2011

For the identifying of spatial distribution pattern, Moran's Index(I) which has the range of values from -1 to +1 is common method for the spatial autocorrelation measurement. When I is close to 1, all neighboring features have close to the same value, indicating clustered pattern. Conversely, if the spatial pattern is dispersed, I is close to -1. And I closing to 0 means spatially random pattern. However, this index equation is influenced by how defining the neighboring features for target feature. To compare and understand the difference of neighborhood definition methods, fixed distance neighboring method and Gabriel Network method were used for I. In this study, these two methods were applied to two marine environments with water quality data. One is Gwangyang Bay which has complex geometric coastal structure located in South Sea of Korea. Another is Uljin area adjacent to open sea located in east coast of Korea. The distances between water quality observed locations were relatively regular in Gwangyang Bay, however, irregular in Uljin area. And for the fixed distance method popular Arc GIS tool was used, but, for the Gabriel Network, Visual Basic program was developed to produce Gabriel Network and calculate Moran's I and its Z-score automatically. According to this experimental results, different spatial pattern was showed differently for some data with using of neighboring definition methods. Therefore there is need to choose neighboring definition method carefully for spatial pattern analysis.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.5-14
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• 2017

Korea, which has undergone a rapid urbanization, faces various problems such as the management of facilities, safety, environment and transportation. To solve civil complaints, local governments receive electronic complaints, but complaints are increasing. Therefore, this study conducted the spatial distribution pattern analysis and the trend analysis by presenting location data on spatial information through Geo-coding by collecting electronic civil petition data over the last 10 years targeting Jinju city. Using the ARIMA model, this study predicted the occurrence of complaints over the next two years (2016~2017) through a time series forecast analysis. As a result, the complaints related to illegal parking were the highest, the complaint related to noise was the second highest, and the complaints related to illegal garbage dumping was the third highest. In addition, the analysis of the spatial distribution pattern shows that the largest hot spot was formed in the central commercial district every year. As a result of the time series forecasting analysis for the crackdown of the illegal parking, complaints increased slightly. To compare the predicted value and the actual data showed a similar pattern. It is judged that this study will be utilized to establish effective countermeasures against civil complaints.

• Bulletin of the Korean Mathematical Society
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• v.52 no.4
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• pp.1113-1122
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• 2015

This paper is concerned with the pattern formation of a diffusive predator-prey model with two time delays. Based upon an analysis of Hopf bifurcation, we demonstrate that time delays can induce spatial patterns under some conditions. Moreover, by use of a series of numerical simulations, we show that the type of spatial patterns is the spiral wave. Finally, we demonstrate that the spiral wave is asymptotically stable.

• Korean journal of applied entomology
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• v.58 no.4
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• pp.291-297
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• 2019

Since Metcalfa pruinosa was first reported in Koera, it has continually caused damage to sweet persimmon orchard in southern part of Korea. Metcafa pruinosa exist not only in farmland but also in forest areas, and are difficult to control due to the influx of individuals from near forest. M. pruinosa has been occurred in orchard and its surroundings because of various host range. Thus, it has been difficult to decide spatial range and control time for efficient management. In this study, occurrence and dispersal pattern of M. pruinosa in persimmon orchard were surveyed using clear sticky traps, and spatial patterns were analyzed with SADIE(Spatial Analysis by Distance IndicEs), based on location information at sticky traps. Spatial association between survey time was also analyzed to identify when the spatial pattern changed. In sweet persimmon orchard, M. pruinosa mainly dispersed in mid to late May, when the first instar hatches, and in August, emerging season of adult. The first instar nymphs hatched in mid-May were randomly distributed in orchard, but distribution was changed to aggregative pattern after dispersed surroundings of orchard. Adults showed random distribution pattern after immigration to orchard again. These tendency was also observed in density change at orchard and its surroundings, and matched to actual density of M. pruinosa in sweet persimmon trees.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.893-900
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• 2004

This paper is to define the method that develops the software In proper to application areas of Geographic Information Systems and design patterns according to functions and roles that implement the system for safety evaluation of the groundwater well based on an object oriented spatial model. In order to design the user interface of the groundwater well, this paper proposes the framework that should classify only requisite components adaptable to various application areas. By specifying De pattern appropriate to the application domain and designing the analysis pattern using the UML based on the object oriented methodology. this paper shah contribute to enhance the reuse of components that can develop and distribute a .large scale open system.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.642-645
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• 2009

Brain Computer Interface (BCI) is a communication pathway between devices (computers) and human brain. It treats brain signals in real-time basis and discriminates some information of what human brain is doing. In this work, we develop a EEG BCI system using a feature extraction such as common spatial pattern (CSP) and a classifier using Fisher linear discriminant analysis (FLDA). Two-class EEG motor imagery movement datasets with both cued and uncued are tested to verify its feasibility.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1260-1264
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• 2009

Precipitation time series is a mixture of complicate fluctuation and changes. The monthly precipitation data of 61 stations during 36 years (1973-2008) in Korea are comprehensively analyzed using the EOFs technique and CSEOFs technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The twenty-five leading EOF modes account for 98.05% of the total monthly variance, and the first two modes account for 83.68% of total variation. The first mode exhibits traditional spatial pattern with annual cycle of corresponding PC time series and second mode shows strong North South gradient. In CSEOF analysis, the twenty-five leading CSEOF modes account for 98.58% of the total monthly variance, and the first two modes account for 78.69% of total variation, these first two patterns' spatial distribution show monthly spatial variation. The corresponding mode's PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation and first mode's PC time series shows increasing linear trend which represents that spatial and temporal variability of first mode pattern has strengthened. Compared with the EOFs analysis, the CSEOFs analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of Korean historical precipitation.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1367-1375
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• 2017

Recently, the use of land cover maps has been continuously increasing to analyze spatial patterns such as spatial compositions, functions and changes of landscape mosaics. In this paper, we propose a landscape analysis system that extracts patches, which is an element of landscape mosaics, in the land cover map using region-based image processing technique, and computes patch-based measures at patch level and class level. Also we propose a patch-based spatial pattern that can represent spatial relations using the computed measures. To validate the proposed system's effectiveness, we apply to Gwangju metropolitan city and analyze Gwangju's land use and spatial patterns.

• Journal of Cadastre & Land InformatiX
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• v.45 no.1
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• pp.241-256
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• 2015

The purpose of this paper is to verify the spatial distribution difference between formation and dissolution of start-up firms related to life-cycle. For this purpose, a Korean business directories and information on business closures were used, and location information, starting time, and closure time of start-up firms in the Seoul metropolitan region from 2007 to 2009 were generated in this study. It applied The spatial distribution analysis methods on the formation and dissolution of the start-up firms included Barcki measurements and global spatial autocorrelation. The total number of start-up firms was 5,810, and their five-year survival rate was 77.25%. The dissolution pattern of the start-up firms was dispersed more than their formation pattern in each of the Seoul metropolitan regions, the city of Seoul, and the city of Incheon-Gyeonggi province. In addition, differences between the formation and dissolution patterns according to size and industry category of the firms were confirmed.