• 산업경영시스템학회지
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• 제46권3호
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• pp.251-258
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• 2023

This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

• 농촌계획
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• 제30권2호
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• pp.1-11
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• 2024

Farmland transaction prices are affected by various factors such as politics, society, and the economy. The purpose of this study is to identify multiple factors that affect the farmland transaction price due to changes in the actual transaction price of farmland by farmland unit from 2016 to 2020. There are several previous studies analyzed the determinants of farmland transaction prices by considering spatial dependency. However, in the case of land transactions where the time and space of the transaction affect simultaneously, if only spatial dependence is considered, there is a limitation in that it cannot reflect spatial dependence that occurs over time. In order to solve these limitations, To address these limitations, this study builds a spatio-temporal autoregressive model that simultaneously considers spatial and temporal dependencies using farmland transactions in Jinju City as an example. As a result of the analysis, it was confirmed that there was significant spatio-temporal dependence in farmland transactions within the previous 30 days. This means that if the previous farmland transaction was carried out at a high price, it has a spatio-temporal spillover effect that indirectly affects the increase in the price of other nearby farmland transactions. The study also found that various location attributes and socioeconomic attributes have a significant impact on farmland transaction prices. The spatio-temporal autoregressive model of farmland prices constructed in this study can be used to improve the prediction accuracy of farmland prices in the farmland transaction market in the future, and it is expected to be useful in drawing policy implications for stabilizing farmland prices

• 한국정보통신학회논문지
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• 제15권2호
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• pp.395-403
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• 2011

모바일 GIS 환경에서 최신의 시공간 정보를 제공하기 위해 여러 가지 연구들이 수행되었다. 양방향 동기화 기법은 변경된 시공간 정보를 모바일 단말기를 이용하여 현장에서 수집하고 서버와 동기화를 통해 신속하게 최신의 시공간 데이터를 수집할 수 있다. 그러나 다른 모바일 단말기들이 수집된 시공간 데이터를 제공받기 위해서는 서버와 주기적으로 동기화를 수행해야 한다. 모바일 단말기들이 주기적으로 서버에 접속하여 동기화를 수행하지 않으면 수집된 최신의 시공간 데이터를 활용할 수 없다. 이 논문에서는 모바일 단말기로부터 수집된 시공간 데이터에 대한 변경전파 기법을 제안한다. 변경전파 기법은 변경전파에 영향이 있는 다양한 요소들을 고려해야 하므로, 각 요소에 따른 다양한 변경전파 정책들을 제공한다.

• Communications for Statistical Applications and Methods
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• 제30권2호
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• pp.119-133
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• 2023

With the rapid growth of the economy and fossil fuel consumption, the concentration of air pollutants has increased significantly and the air pollution problem is no longer limited to small areas. We conduct statistical analysis with the actual data related to air quality that covers the entire of South Korea using R and Python. Some factors such as SO₂, CO, O₃, NO₂, PM₁₀, precipitation, wind speed, wind direction, vapor pressure, local pressure, sea level pressure, temperature, humidity, and others are used as covariates. The main goal of this paper is to predict air quality index (AQI) spatio-temporal data. The observations of spatio-temporal big datasets like AQI data are correlated both spatially and temporally, and computation of the prediction or forecasting with dependence structure is often infeasible. As such, the likelihood function based on the spatio-temporal model may be complicated and some special modelings are useful for statistically reliable predictions. In this paper, we propose several methods for this big spatio-temporal AQI data. First, random effects with spatio-temporal basis functions model, a classical statistical analysis, is proposed. Next, neural networks model, a deep learning method based on artificial neural networks, is applied. Finally, random forest model, a machine learning method that is closer to computational science, will be introduced. Then we compare the forecasting performance of each other in terms of predictive diagnostics. As a result of the analysis, all three methods predicted the normal level of PM_2.5 well, but the performance seems to be poor at the extreme value.

• 대한원격탐사학회지
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• 제22권5호
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• pp.313-323
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• 2006

Forest Canopy Density is a dynamic process mediated by various natural and anthropogenic factors. It can be changed over time and locations in the same forest type and landscape. However, human dimensions are considered as the primary force of landscape change and subsequent forest canopy loss in tropical regions of the world. Many studies have been indicated that roads have a far greater impact on forests than simply allowing access for human use. Similarly, rivers have been used as means of transportation, hence illegal logging and felling further deplete forest canopy density. The main objective of this study was to investigate the spatio-temporal dynamic alterations of Forest Canopy Density (FCD) across with site associated factors such as biophysical, physical and human interferences in tropical region of Nepal from 1988 to 2001. Landsat TM and ETM+ of 1988 and 2001 were used to assess the spatial and temporal dynamic alterations of FCD. This analysis revealed that distance to human settlements at P=<0.01, rivers, human interferences (path and fire) and species composition had a statistically significance at P=<0.05 level. However, other factors did not show any significant relation. So, we concluded that understanding of dynamic alterations of FCD with respect to factors was quite complex phenomena. Other surrounding environment could also playa significant role. A comprehensive analysis could be required to understand such complexities. Therefore, additional factors such as climatic, biophysical, social, and institutional with respect to spatio-temporal variability should be considered for the better understanding of canopy dynamic.

• 환경생물
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• 제21권4호
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• pp.422-427
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• 2003

The spatio-temporal distribution of four coexisting acartiid species in two subgenera Acartiura (Acartia hongi and A. omorii) and Odontacartia (A. erythraea and A. pacifica) was examined at seven stations in the southwestern waters of Korea, between January to December 1998. A. hongi occurred dominantly in the northern regions from winter to spring while A. omorii predominated in the southern regions in spring and early summer when the more saline (> 33.0 psu) and high chlorophyll-$\alpha$ concentration water mass appeared. With the increase of temperature (> $20^{\circ}C$), however, both species disappeared and then replaced with A. erythraea and A. pacifica. A. erythraea (rare species), appeared in the middle regions where the high chlorophyll-$\alpha$ concentration ($3{\mu}g\; I^{-1}$) in the summer, while A. pacifica was abundant in all regions through summer and fall. It is suggested that the seasonal succession of the genus Acartia was subgenus-specifically affected by environmental factors such as temperature, salinity and chlorophyll-$\alpha$ concentration.

• 한국항해항만학회지
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• 제48권5호
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• pp.409-417
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• 2024

Recently, various marine development initiatives, including offshore wind farms and marina port facilities, have been launched to enhance utilization of coastal waters. In addition, advancements in technologies for autonomous ships and wing-in-ground effect craft are progressing swiftly, increasing the complexity of maritime traffic. Accordingly, proactive policy development and research are needed to ensure safe navigation and decrease maritime accidents. The dynamic interplay between vessel traffic and geographical features in coastal waters necessitates spatio-temporal analysis. Factors such as currents, waves, and fog, along with vessel traffic services, play pivotal roles in managing maritime traffic. In this study, AIS data were used to quantitatively evaluate the distribution and utilization of maritime traffic in coastal waters using a grid cell approach. Furthermore, a suitability model for maritime traffic routes was developed, taking into account spatio-temporal operational and environmental characteristics. Results were compared to existing national maritime traffic route and offshore wind farm plans, providing valuable insights for the development of future maritime traffic networks.

• 대한토목학회논문집
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• 제40권2호
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• pp.209-215
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• 2020

자연적인 가뭄의 발생특성을 이해하는 데 있어서는 서로 다른 유형의 가뭄 사이의 시공간적 관계를 해석하는 것이 매우 중요하다. 본 연구에서는 가뭄 지속시간과 3차원(즉, 위도, 경도 및 시간)의 공간 범위가 겹치는 것을 고려하여 기상 및 수문학적 가뭄사상을 정의하고 전이특성을 해석하였다. 이는 시공간적 가뭄 특성인자(지속기간, 면적, 심도, 중심)를 기반으로 하여 가뭄의 공간적 재현특성과 더불어 시간이라는 연속적인 개념을 결합한다는 것을 의미한다. 이처럼 개발된 시공간적 가뭄전이 특성을 고려한 가뭄지도는 향후 국지적으로 빈번히 발생하는 수문학적 가뭄의 발생 원인을 발견하고, 가뭄에 대한 효율적인 대응방안을 마련하는 데 활용도가 매우 높을 것으로 기대된다.

• 한국지리정보학회지
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• 제26권2호
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• pp.20-41
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• 2023

최근 저출산·고령화에 따른 도시축소 현상과 지방도시의 쇠퇴는 빈집이라는 새로운 도시문제를 낳고 있다. 본 연구는 전국 시·군·구를 대상으로 2015년부터 2019년까지 수집한 공간 패널 데이터를 이용하여 빈집 분포를 살펴보고 시공간적 종속성을 고려한 공간패널모형을 이용하여 빈집발생의 요인을 추정하는 것이 목적이다. 분석 결과 빈집은 시공간적으로 종속성이 있었으며, OLS 모형에 비해 시공간적 종속성을 고려하여 빈집 발생 요인을 추정하는 것이 타당함을 확인하였다. 동적공간패널모형을 이용하여 분석한 결과 빈집발생의 가장 큰 영향요인은 주택관련요인인 것으로 나타났다. 이 결과는 빈집 발생의 관리를 위해서는 인구이동, 양호하지 못한 인프라 등 뿐만 아니라 주택 공급량에 대한 정책적 고려가 필요함을 시사한다.

• 한국수산과학회지
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• 제56권4호
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• pp.558-568
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• 2023

The spatio-temporal distribution of the sand crab Ovalipes punctatus larvae was investigated in the Korean waters in 2019. Sea surface temperature (SST) was the lowest in February and highest in September. Sea surface salinity (SSS) was the lowest in September and highest in March. Further, sea surface chlorophyll a (SSC) was the highest in September. Larvae were distributed in the South Sea and coastal area of Jeju Island from April to June, and the abundance was the highest in May. The spatio-temporal distribution analysis suggested that larval groups showed a tendency to be dispersed over a wider area as the larvae developed, due to the increase in their swimming ability. The correlation analysis between environmental factors and larval density suggested that larvae appeared in the SST range 11.8-20.9℃ and SSS range 31.5-35.3 psu. The Megalopal stage appeared in a wider range of SST and SSS than other larval stages, possibly due to the increased environmental tolerance before settlement. Results of redundancy analysis (RDA) and Spearman's rank correlation analysis between the larval density by developmental stages and the environmental factors suggested that SST showed a positive correlation and SSC showed a negative correlation in the later stage.