• Journal of the Korean Geographical Society
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• v.37 no.2
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• pp.191-202
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• 2002

Characteristics and patterns of geographic features and human activities can be interpreted in terms of spatiality and temporality. The necessity to record the historical changes and the ability to reason in the real world has lead to a new field of research so called Integrated Spatio-Temporal analysis. The objective of this study is to investigate temporal maps for Spatio-temporal analysis, which have the integration functionality for visualizing spatiality and temporality of the geographic appearances and human activities. Land information is composed of spatial, attribute and temporal data and requires spatio-temporal representations. It is possible to visualize spatio-temporal variations with spatio-temporal databases and temporal map produced by integrated data models. This study constructs spatio-temporal model for temporal maps of land price variation analysis. Taking advantage of the spatio-temporal model proposed here, it is possible to visualize spatio-temporal variations with spatio-temporal database and temporal map. On a practical level, this study would be extended and utilized to various geographic features.

• Molecules and Cells
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• v.21 no.3
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• pp.436-442
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• 2006

Different proliferation of neuroblast 6-4 (NB6-4) in the thorax and abdomen produces segmental specific expression pattern of several neuroblast marker genes. NB6-4 is divided to form four medialmost cell body glia (MM-CBG) per segment in thorax and two MM-CBG per segment in abdomen. As homeotic genes determine the identities of embryonic segments along the A/P axis, we investigated if temporal and specific expression of homeotic genes affects MM-CBG patterns in thorax and abdomen. A Ubx loss-of-function mutation was found to hardly affect MM-CBG formation, whereas abd-A and Abd-B caused the transformation of abdominal MM-CBG to their thoracic counterparts. On the other hand, gain-of-function mutants of Ubx, abd-A and Abd-B genes reduced the number of thoracic MM-CBG, indicating that thoracic MM-CBG resembled abdominal MM-CBG. However, mutations in Polycomb group (PcG) genes, which are negative transregulators of homeotic genes, did not cause the thoracic to abdominal MM-CBG pattern transformation although the number of MM-CBG in a few percent of embryos were partially reduced or abnormally patterned. Our results indicate that temporal and spatial expression of the homeotic genes is important to determine segmental-specificity of NB6-4 daughter cells along the anterior-posterior (A/P) axis.

• ETRI Journal
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• v.43 no.2
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• pp.272-287
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• 2021

This article presents a multi-dimensional spatial pattern analysis of crime events in San Francisco. Our analysis includes the impact of spatial resolution on hotspot identification, temporal effects in crime spatial patterns, and relationships between various crime categories. In this work, crime prediction is viewed as a classification problem. When predictions for a particular category are made, a binary classification-based model is framed, and when all categories are considered for analysis, a multiclass model is formulated. The proposed crime-prediction model (HotBlock) utilizes spatiotemporal analysis for predicting crime in a fixed spatial region over a period of time. It is robust under variation of model parameters. HotBlock's results are compared with baseline real-world crime datasets. It is found that the proposed model outperforms the standard DeepCrime model in most cases.

• 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 Information Science Theory and Practice
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• v.9 no.1
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• pp.35-53
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• 2021

The study reported in this paper aimed to evaluate the topics and opinions of COVID-19 discussion found on Twitter. It performed topic modeling and sentiment analysis of tweets posted during the COVID-19 outbreak, and compared these results over space and time. In addition, by covering a more recent and a longer period of the pandemic timeline, several patterns not previously reported in the literature were revealed. Author-pooled Latent Dirichlet Allocation (LDA) was used to generate twenty topics that discuss different aspects related to the pandemic. Time-series analysis of the distribution of tweets over topics was performed to explore how the discussion on each topic changed over time, and the potential reasons behind the change. In addition, spatial analysis of topics was performed by comparing the percentage of tweets in each topic among top tweeting countries. Afterward, sentiment analysis of tweets was performed at both temporal and spatial levels. Our intention was to analyze how the sentiment differs between countries and in response to certain events. The performance of the topic model was assessed by being compared with other alternative topic modeling techniques. The topic coherence was measured for the different techniques while changing the number of topics. Results showed that the pooling by author before performing LDA significantly improved the produced topic models.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.101-112
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• 2022

Extreme precipitation events have recently become a leading cause of disasters. Thus, investigating the variability and trends of extreme precipitation is crucial to mitigate the increasing impact of such events. Spatial distribution and temporal trends in annual precipitation and four extreme precipitation indices of duration (CWD), frequency (R10 mm), intensity (Rx1day), and percentile-based threshold (R95pTOT) were analyzed using the daily precipitation data of 10 observation stations in Chungcheong province during 1974-2020. The precipitation at all observation stations, except the Boryeong station, showed nonsignificant increasing trends at 95% confidence level (CL) and increasing magnitudes from the west to east regions. The high variability in mean annual precipitation was more pronounced around the northeast and northwest regions. Similarly, there were moderate to high patterns in extreme precipitation indices around the northeast region. However, the precipitation indices of duration and frequency consistently increased from the west to east regions, while those of intensity and percentile-based threshold increased from the south to east regions. Nonsignificant increasing trends dominated in CWD, R10 mm, and Rx1day at all stations, except for R10 mm at Boeun station and Rx1day at Cheongju and Jecheon stations, which showed a significantly increasing trend. The spatial distribution of trend magnitude shows that R10 mm increased from the west to east regions. Furthermore, variations in precipitation were very strongly correlated (99% CL) with R10 mm, Rx1day, and R95pTOT at all stations, except with wR10 mm at Cheongju station, which was strongly correlated with a 95% CL.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.163-176
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• 2006

The concept of 'spatial association' explains spatial distribution pattern of geographical phenomenon based on similarity with neighborhoods, as in the Tobler's Law of Geography: 'Everything is related to everything else, but near things are more related than distant things.' In this study, we develop a time-series exploratory analysis tool for discovering temporal patterns of spatial association by combining spatial statistics and geo-visualization, and thus present a possibility to support spatial decision-making process. As for the spatial proximity weight matrix indispensable to measuring global and local spatial association, we employ a variety of flexible weighting schemes using geometric characteristics of areal unit. In addition, we renovate the existing visualization methods for more effective understanding of the procedures and results of time-series analysis on spatial association: for instance, temporal parallel coordinate plot with box plot, animated map for spatial association, and 3D Moran scatterplot. The feasibility of our system is verified by time-series analysis experiments on the spatial association of land price fluctuation rate for all administrative units in Korea, $1995{\sim}2004$.

• Spatial Information Research
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• v.19 no.3
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• pp.63-72
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• 2011

Urban space structure tends to have a significant change in accordance with maintenance of urban infrastructure such as a traffic route. For this reason, quantitative analysis has been needed to establish spatial distribution and location patterns by considering change of both road accessibility and urban infrastructure level, which can have the most pervasive influence in urban development process. Therefore, this paper aims to analyze spatio-temporal urban morphology through considering distribution patterns of road among transportation infrastructures, population, and spatial structure of metropolitan areas, focusing on Seoul where population growth and the size of urban area have been dramatically increased. For this, we firstly developed and constructed time-series GIS database by using satellite images and topographic maps of the last 70 years to analyze variables which affect urban growth and transportation. In particular, we analyzed the transform of the system of the street by Space Syntax which is able to grasp hierarchical spatial structure through visibility of space and spatial cognition in terms of accessibility. What's more, we analyzed and visualized the relationship urban morphology and road according the regions of Seoul through IPA(Importance Performance Analysis). In terms of the integration land-use and transportation, Space Syntax approach is expected to contribute to efficient urban planning through understanding the influence which various transportation phenomena has an effect on urban development patterns.

• Journal of Ecology and Environment
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• v.35 no.1
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• pp.51-58
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• 2012

In this study, we investigated carabid beetles residing in the wetlands to understand their ecological adaptation and strategy selection associated with restricted resources and habitat limitation. The species richness, abundance, seasonal activity, and spatial distribution of the carabid beetles between the Mujechi Wetlands (wetland sites) and Mt. Jeongjok (mountain sites) have been compared. A total of 1,733 individual beetles from 30 species were collected and classified at the studied sites. The wetland sites were identified as having lower species richness and abundance for carabid beetles when compared with the adjacent mountain sites, whereas these beetles were observed to be dominant in the wetland sites than in the adjacent mountain sites. Calosoma inquisitor cyanescens, Carabus sternbergi sternbergi, and Carabus jankowskii jankowskii species were dominant in both the wetland and mountain sites. These species showed significantly different seasonal activity patterns in the wetland sites relative to the mountain sites. Although the three listed carabid species were observed to be widely distributed throughout the wetland sites, they still showed preference for drier sites, which clearly shows a distinction in their habitats. The results of the spatial-temporal distribution of carabid beetles in the wetland sites reflect their special strategies regarding space and time partitioning for maintaining their population. The distribution patterns of carabid beetles in the wetland sites also showed the desiccation gradient and environmental changes prevalent in wetlands. Ecological surveys, which use carabid beetles in the wetlands, can then be performed when restoring wetlands and for establishing management practices for improving the habitat quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.