시공간 GIS자료의 3차원 유형화 연구

Eun-Kyeong Kim; Chul-Sue Hwang

시공간 GIS자료의 3차원 유형화 연구

Translated title of the contribution: 3D Sequential Object Clustering for Spatio-temporal Data Analysis

Eun-Kyeong Kim
, Chul-Sue Hwang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This study aims to develop improved techniques for effectively typifying and geographically visualizing extensive spatio-temporal trajectory data. Spatio-temporal trajectories are influenced by environmental factors, and analyzing these trajectories can help in understanding the relationship between daily activities and the environment. However, there are limitations in data processing and visualization. By using a three-dimensional sequence object model based on geometric elements, clustering analysis was conducted with the DBSCAN algorithm, and the results were visualized using ArcGIS. Depending on the frequency of movements, the number of clusters identified in the research was 17, 6, 2, and 3, respectively. Representative objects were generated based on average geometric elements, allowing for effective visualization.

Translated title of the contribution	3D Sequential Object Clustering for Spatio-temporal Data Analysis
Original language	Korean
Title of host publication	대한지리학회 학술대회논문집
Subtitle of host publication	대한지리학회 2010년 연례학술대회 및 정기총회 발표논문 요약집
Publisher	The Korean Geographical Society
Pages	136-141
Number of pages	6
Publication status	Published - May 2010
Externally published	Yes

Access to Document

https://www.dbpia.co.kr/Journal/articleDetail?nodeId=NODE01472260

Cite this

@inproceedings{234f4fb8c699483c885d4a639ae08a4b,

title = "시공간 GIS자료의 3차원 유형화 연구",

abstract = "This study aims to develop improved techniques for effectively typifying and geographically visualizing extensive spatio-temporal trajectory data. Spatio-temporal trajectories are influenced by environmental factors, and analyzing these trajectories can help in understanding the relationship between daily activities and the environment. However, there are limitations in data processing and visualization. By using a three-dimensional sequence object model based on geometric elements, clustering analysis was conducted with the DBSCAN algorithm, and the results were visualized using ArcGIS. Depending on the frequency of movements, the number of clusters identified in the research was 17, 6, 2, and 3, respectively. Representative objects were generated based on average geometric elements, allowing for effective visualization.",

author = "Eun-Kyeong Kim and Chul-Sue Hwang",

year = "2010",

month = may,

language = "Cor{\'e}e",

pages = "136--141",

booktitle = "대한지리학회 학술대회논문집",

publisher = "The Korean Geographical Society",

address = "Cor{\'e}e du Nord",

}

TY - GEN

T1 - 시공간 GIS자료의 3차원 유형화 연구

AU - Kim, Eun-Kyeong

AU - Hwang, Chul-Sue

PY - 2010/5

Y1 - 2010/5

N2 - This study aims to develop improved techniques for effectively typifying and geographically visualizing extensive spatio-temporal trajectory data. Spatio-temporal trajectories are influenced by environmental factors, and analyzing these trajectories can help in understanding the relationship between daily activities and the environment. However, there are limitations in data processing and visualization. By using a three-dimensional sequence object model based on geometric elements, clustering analysis was conducted with the DBSCAN algorithm, and the results were visualized using ArcGIS. Depending on the frequency of movements, the number of clusters identified in the research was 17, 6, 2, and 3, respectively. Representative objects were generated based on average geometric elements, allowing for effective visualization.

AB - This study aims to develop improved techniques for effectively typifying and geographically visualizing extensive spatio-temporal trajectory data. Spatio-temporal trajectories are influenced by environmental factors, and analyzing these trajectories can help in understanding the relationship between daily activities and the environment. However, there are limitations in data processing and visualization. By using a three-dimensional sequence object model based on geometric elements, clustering analysis was conducted with the DBSCAN algorithm, and the results were visualized using ArcGIS. Depending on the frequency of movements, the number of clusters identified in the research was 17, 6, 2, and 3, respectively. Representative objects were generated based on average geometric elements, allowing for effective visualization.

M3 - Conference contribution

SP - 136

EP - 141

BT - 대한지리학회 학술대회논문집

PB - The Korean Geographical Society

ER -