• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.3
• /
• pp.251-258
• /
• 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.

• Journal of Korean Society of Rural Planning
• /
• v.30 no.2
• /
• pp.1-11
• /
• 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

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.2
• /
• pp.395-403
• /
• 2011

Various studies were performed for providing the latest spatio-temporal information in mobile GIS Environments. The two-way synchronization scheme collects updated spatio-temporal data in the field and synchronizes with a server by using the wireless network. However, the other mobile terminals have to perform periodically synchronizes with a server. In this paper, we propose the update propagation scheme about spatio-temporal data collected from the mobile terminal. The update propagation scheme does considering various factors where an influence is in the update propagation. Therefore, it provides various update propagation policies according to each factors.

• Communications for Statistical Applications and Methods
• /
• v.30 no.2
• /
• pp.119-133
• /
• 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.

• Korean Journal of Remote Sensing
• /
• v.22 no.5
• /
• pp.313-323
• /
• 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.

• Korean Journal of Environmental Biology
• /
• v.21 no.4
• /
• pp.422-427
• /
• 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.

• Journal of Navigation and Port Research
• /
• v.48 no.5
• /
• pp.409-417
• /
• 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.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.2
• /
• pp.209-215
• /
• 2020

In order to understand the characteristics of natural droughts, it is very important to interpret the spatio-temporal relationship between different types of droughts. In this study, meteorological and hydrological drought events were defined to account for the overlap between drought duration and spatial extent in three dimensions (i.e., latitude, longitude, and timing). In other words, the spatio-temporal drought propagation characteristics were analyzed based on the drought characteristic factors (duration, area, depth, center). The drought map considering the characteristics of spatio-temporal drought propagation can be used to find the fundamental cause of the hydrological drought which is expected to frequently occur in the future. In addition, the drought map is expected to be useful in preparing an effective drought response plan.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.2
• /
• pp.20-41
• /
• 2023

Recently, urban shrinkage due to low birth rate and aging population and the decline of local cities are causing a new urban problem of empty houses. This study examines the distribution of vacant homes using spatial panel data collected from 2015 to 2019 at local administraitve districts and estimates the factors of vacant house occurrence using a spatial panel model considering spatio-temporal dependency. As a result, the spatio-temporal dependence of vacant houses was identified and it was estimated using spatial panel model not OLS model. Based on the spatial panel model, it was found that the most influential factor in the occurrence of vacant houses was the housing-related factor. This result shows that policy considerations for housing supply are necessary for the management of vacant housing as well as population movement and poor infrastructure.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.56 no.4
• /
• pp.558-568
• /
• 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.