문화재 분포 예측을 위한 GIS 활용방안 연구

Seok-Hwan Won; Eun-Kyeong Kim; Jeon-Young Kang; Chul-Sue Hwang

문화재 분포 예측을 위한 GIS 활용방안 연구

Translated title of the contribution: GIS Application for Prediction of Archaeological Site Distribution

Seok-Hwan Won
, Eun-Kyeong Kim
, Jeon-Young Kang
, Chul-Sue Hwang

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

Abstract

The goal of this study is to enhance existing cultural heritage site-environment analysis models and propose effective GIS-based strategies for predicting cultural heritage distribution. The importance of cultural heritage management is increasing, and a large amount of cultural heritage data is being collected due to amendments to the Cultural Heritage Protection Act. This study analyzed the distribution of buried cultural heritage sites using Geographically Weighted Regression (GWR) and evaluated predictive models. Results from analysis in the Buyeo area indicate that the GWR method is particularly suitable for micro-scale analysis.

Translated title of the contribution	GIS Application for Prediction of Archaeological Site Distribution
Original language	Korean
Title of host publication	대한지리학회 학술대회논문집
Subtitle of host publication	대한지리학회 2011년 연례학술대회 및 정기총회 발표논문 요약집
Publisher	The Korean Geographical Society
Pages	301-304
Number of pages	4
Publication status	Published - May 2011
Externally published	Yes

Access to Document

https://www.dbpia.co.kr/Journal/articleDetail?nodeId=NODE01659344

Cite this

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title = "문화재 분포 예측을 위한 GIS 활용방안 연구",

abstract = "The goal of this study is to enhance existing cultural heritage site-environment analysis models and propose effective GIS-based strategies for predicting cultural heritage distribution. The importance of cultural heritage management is increasing, and a large amount of cultural heritage data is being collected due to amendments to the Cultural Heritage Protection Act. This study analyzed the distribution of buried cultural heritage sites using Geographically Weighted Regression (GWR) and evaluated predictive models. Results from analysis in the Buyeo area indicate that the GWR method is particularly suitable for micro-scale analysis.",

author = "Seok-Hwan Won and Eun-Kyeong Kim and Jeon-Young Kang and Chul-Sue Hwang",

year = "2011",

month = may,

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

pages = "301--304",

booktitle = "대한지리학회 학술대회논문집",

publisher = "The Korean Geographical Society",

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

}

문화재 분포 예측을 위한 GIS 활용방안 연구. / Won, Seok-Hwan; Kim, Eun-Kyeong; Kang, Jeon-Young et al.
대한지리학회 학술대회논문집: 대한지리학회 2011년 연례학술대회 및 정기총회 발표논문 요약집. The Korean Geographical Society, 2011. p. 301-304.

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

TY - GEN

T1 - 문화재 분포 예측을 위한 GIS 활용방안 연구

AU - Won, Seok-Hwan

AU - Kim, Eun-Kyeong

AU - Kang, Jeon-Young

AU - Hwang, Chul-Sue

PY - 2011/5

Y1 - 2011/5

N2 - The goal of this study is to enhance existing cultural heritage site-environment analysis models and propose effective GIS-based strategies for predicting cultural heritage distribution. The importance of cultural heritage management is increasing, and a large amount of cultural heritage data is being collected due to amendments to the Cultural Heritage Protection Act. This study analyzed the distribution of buried cultural heritage sites using Geographically Weighted Regression (GWR) and evaluated predictive models. Results from analysis in the Buyeo area indicate that the GWR method is particularly suitable for micro-scale analysis.

AB - The goal of this study is to enhance existing cultural heritage site-environment analysis models and propose effective GIS-based strategies for predicting cultural heritage distribution. The importance of cultural heritage management is increasing, and a large amount of cultural heritage data is being collected due to amendments to the Cultural Heritage Protection Act. This study analyzed the distribution of buried cultural heritage sites using Geographically Weighted Regression (GWR) and evaluated predictive models. Results from analysis in the Buyeo area indicate that the GWR method is particularly suitable for micro-scale analysis.

M3 - Conference contribution

SP - 301

EP - 304

BT - 대한지리학회 학술대회논문집

PB - The Korean Geographical Society

ER -