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2025 Vol.58, Issue 7 Preview Page

Research Article / 우수학생논문상

Development of an XGBoost-based methodology for identifying replacement sites of river wetlands

대체습지 후보지 선정을 위한 XGBoost 모형 기반의 방법론 개발: 하천습지를 중심으로

Jeemi Sunga
,
Changhyun Junb
,
Seunghyun Hwangc
,
Seoyeong Kud
,
Jongjin Baike*
성 지미a
,
전 창현b
,
황 승현c
,
구 서영d
,
백 종진e*
aPh.D. Student, Department of Civil, Environmental and Architectural Engineering, College of Engineering, Korea University, Seoul, Korea
bAssociate Professor, School of Civil, Environmental and Architectural Engineering, College of Engineering, Korea University, Seoul, Korea
cIntegrated Master & Ph.D. Student, Department of Civil, Environmental and Architectural Engineering, College of Engineering, Korea University, Seoul, Korea
dIntegrated Master & Ph.D. Student, Department of Civil, Environmental and Architectural Engineering, College of Engineering, Korea University, Seoul, Korea
eResearch Professor, Future and Fusion Lab of Architectural, Civil and Environmental Engineering, Korea University, Seoul, Korea
a고려대학교 일반대학원 건축사회환경공학과 박사과정
b고려대학교 공과대학 건축사회환경공학부 부교수
c고려대학교 일반대학원 건축사회환경공학과 석박사통합과정
d고려대학교 일반대학원 건축사회환경공학과 석박사통합과정
e고려대학교 미래건설환경융합연구소 연구교수
*Corresponding Author
31 July 2025. pp. 593-604
PDF XML Citation
Abstract

This study aims to identify replacement alternative sites for river wetlands by developing a binary classification model based on XGBoost to support the efficient conservation of river wetlands. Remote sensing and reanalysis data from 2017 to 2022 were used as input, incorporating a total of 13 hydrometeorological, vegetation, and carbon-related variables to reflect the diverse eco-environmental characteristics of river wetlands. The trained model was applied to annual representative data derived by averaging monthly remote sensing and reanalysis datasets from January to December 2023, enabling the identification of areas that could potentially be designated as substitute wetlands. > Based on the trained XGBoost model, the mean values of monthly remote sensing and reanalysis data from January to December 2023 were applied. The model results indicated that 451,373 pixels, approximately 1.2% of the national territory, exhibited over 99% similarity to existing river wetlands. These areas are therefore considered to have potential for designation as replacement river wetlands. Among the model outputs, five locations not currently designated as river wetlands (near Yeoju, Seonsan-eup, Yongdam Lake, Soyang Lake, and Paro Lake) were randomly selected for further analysis. In all five locations, essential wetland characteristics such as water bodies, geomorphology, and water sources were commonly observed. By utilizing remote sensing and reanalysis data, this study offers a data-driven approach that can serve as a preliminary step prior to traditional field-based surveys. It is expected to contribute to the efficient identification of river wetlands and support a balanced approach between development and environmental conservation.

Keywords
River wetland
Replacement wetland
XGBoost
Remote sensing data
Reanalysis data

본 연구에서는 효율적인 하천습지 보전을 위해 XGBoost 기반 이진 분류 모형을 구축하여 하천습지의 잠재적인 대체 후보지를 도출하는 방법론을 제안하였다. 2017년에서 2022년의 기간에 해당하는 원격탐사 및 재분석자료를 입력자료로 활용하였으며, 수문·기상, 식생, 탄소 관련 인자 총 13개를 활용하여 하천습지의 다양한 생태 환경적 특징을 고려하였다. 학습된 XGBoost 기반 모형에 2023년 1월부터 12월까지의 월별 원격탐사 및 재분석자료를 평균한 연간 대표자료를 적용한 결과, 전국 면적의 약 1.2%에 해당하는 451,373개의 픽셀이 기존 하천습지와 99% 이상의 유사도를 가지는 것으로 확인되어, 잠재적으로 하천습지의 대체습지로 지정될 가능성이 있는 것으로 나타났다. 모형의 결과 중 하천습지로 지정되지 않은 5곳(여주, 선산읍, 용담호, 소양호, 파로호 부근)을 무작위로 선정하여 분석한 결과, 공통적으로 습지의 기본 요건이 되는 수역, 지형, 수원을 확인할 수 있었다. 원격탐사 및 재분석자료를 활용한 본 연구는 기존 현장 중심의 습지 조사를 위한 사전 조사에 활용되어, 효율적인 하천습지 발굴에 기여할 수 있을 것으로 생각되며 개발과 환경 보존 간의 균형 확립에 일조할 수 있을 것으로 사료된다.

키워드
하천습지
대체습지
XGBoost
원격탐사자료
재분석자료
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Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 58
  • No :7
  • Pages :593-604
  • Received Date : 2025-02-06
  • Revised Date : 2025-04-29
  • Accepted Date : 2025-05-13
  • DOI :https://doi.org/10.3741/JKWRA.2025.58.7.593
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