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2025 Vol.34, Issue 4 Preview Page

Original Articles

Automated Reporting Framework for Regional Crop Conditions Using Multi-Source Data and Crop Modeling

다중출처 데이터와 작물모형을 활용한 지역 단위 작황 현황 자동 보고 서비스 개발

Solhee Kim1†
,
Jaeyoung Jung2†
,
Seungwon Seok2
,
Taegon Kim34*
김 솔희1†
,
정 재영2†
,
석 승원2
,
김 태곤34*
1Associate Research Professor, Department of Smart Farm, College of Agriculture & Life Sciences, Jeonbuk National University, Jeonju 54896, Korea
2Master’s Student, Department of Agricultural Engineering, College of Agriculture & Life Sciences, Jeonbuk National University, Jeonju 54896, Korea
3Associate Professor, Department of Smart Farm, College of Agriculture & Life Sciences, Jeonbuk National University, Jeonju 54896, Korea
4Researcher, Institute of Agricultural Science & Technology, Jeonbuk National University, Jeonju 54896, Korea
1전북대학교 농업생명과학대학 스마트팜학과 연구부교수
2전북대학교 농업생명과학대학 농공학과 석사과정
3전북대학교 농업생명과학대학 스마트팜학과 부교수
4전북대학교 농업과학기술연구소 연구원
*Corresponding Author
†These authors contributed equally to this work
31 October 2025. pp. 545-554
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Abstract

Monitoring crop conditions in open-field agriculture is increasingly important under climate variability and market uncertainty. Conventional approaches relying on either weather statistics, remote sensing indices, or crop models alone provide partial insights but lack an integrated perspective. This study aims to develop an automated reporting service for regional crop condition monitoring by integrating multi-source data and crop modeling. The framework consists of three main components: (1) weather data analysis (e.g., temperature, precipitation) for environmental characterization, (2) vegetation indices derived from satellite imagery to assess crop status, and (3) potential yield estimation using the APSIM crop model. These data streams are automatically processed and synthesized into regional-scale crop condition reports, which include spatially explicit maps, time-series trends, and yield forecasts. Validation with statistical production data demonstrated that the APSIM-based potential yield estimation has significant predictive capability at the provincial level. The proposed system highlights the potential of combining heterogeneous data sources into an automated reporting pipeline, thereby supporting agricultural decision-making, policy development, and timely responses to climate and market risks.

Keywords
APSIM
automation
crop monitoring
data integration
remote sensing

기후 변동성과 시장 불확실성이 심화되는 상황에서 노지 작물의 작황 모니터링은 점차 중요성이 커지고 있다. 기상자료 통계분석, 원격탐사기반 식생지수, 작물모형 중 하나에만 의존하는 기존 모니터링 접근법은 부분적인 정보만 제공할 뿐, 현장상황을 종합적으로 판단하여 제시하지 못하는 한계가 있다. 본 연구는 다중출처 데이터와 작물모형을 통합하여 지역 단위 작황 모니터링을 자동으로 수행하는 보고 서비스 개발을 목표로 한다. 제안하는 서비스는 (1) 기상자료 분석을 통한 환경 특성 평가, (2) 위성영상을 활용한 식생지수 산출을 통한 실시간 생육 상태 진단, (3) 작물모형을 활용한 기상환경에 따른 잠재 생산량 추정의 세 요소로 구성된다. 이러한 데이터는 파이프라인을 통해 자동으로 처리하여 그 결과가 지도, 시계열 변화, 생산량 예측을 포함한 지역 단위 작황 보고서로 생성되도록 시스템을 개발하였다. 잠재생산량은 생산량 통계 자료와의 비교 검증을 통해 작물모형(APSIM)을 활용한 잠재 생산량 추정치가 유의한 수준임을 확인하였다. 본 연구에서 제안한 체계는 다양한 출처에서 생산되는 데이터를 자동화된 보고 파이프라인으로 통합함으로써 농업 의사결정, 정책 수립, 기후 및 시장 위험에 대한 신속한 대응을 지원할 수 있는 의사지원시스템의 주요 구성요소로 기여할 것이다.

키워드
데이터 통합
원격탐사
자동화
작황모니터링
APSIM
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Information
  • Publisher :The Korean Society for Bio-Environment Control
  • Publisher(Ko) :(사)한국생물환경조절학회
  • Journal Title :Journal of Bio-Environment Control
  • Journal Title(Ko) :생물환경조절학회지
  • Volume : 34
  • No :4
  • Pages :545-554
  • Received Date : 2025-10-09
  • Revised Date : 2025-10-28
  • Accepted Date : 2025-10-29
  • DOI :https://doi.org/10.12791/KSBEC.2025.34.4.545
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