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2025 Vol.25, Issue 2

Research Article

A Quantitative Comparison of Raster Data Using Various Types of Disagreement Components

불일치 요소 분해 방법론을 통한 래스터 자료의 정량적 비교 분석

김정민1 · 김오석2†

Jeongmin Kim1 ⋅ Oh Seok Kim2†

1고려대학교 지리교육과 지리학과 학석사연계과정
2고려대학교 지리학과, 지리교육과, 미래국토연구소 부교수
1Bachelor-Master Degree Bridging Program Student, Department of Geography Education and Department of Geography, Korea University
2Associate Professor, Department of Geography, Department of Geography Education, and Institute of Future Land, Korea University
31 August 2025. pp. 1~12
PDF Citation
Abstract
Raster is an important spatial data structure and visualization method that, together with vector, forms one pillar of geographic information science. However, research on raster comparison is limited in Korean academia, despite quantitatively comparing and analyzing raster maps is fundamental in geographic research. Results of such comparisons must be accurate and objective, as they determine the validity and credibility of research. Traditionally, Kappa coefficient has been widely used to evaluate an agreement between two raster layers, where it also has been criticized for its unrealistic assumptions and reliance on a single indicator. In this study, we examined various types of disagreement components proposed by Pontius, which has been designed as an alternative to Kappa, and applied to virtual raster data to compare and evaluate their differences and usefulness. Specifically, we applied each methodology to the identical dataset and discussed their results’ differences. As a result, while Kappa derived an ambiguous conclusion, namely “substantial agreement” using a single numerical value, the methodology of Pontius demonstrated more sophisticated evaluation—whether the primary cause of discrepancy between two raster layers is a disagreement in the total number of pixels (“Quantitative Disagreement”) or a disagreement due to the spatial arrangement of pixels (“Allocation Disagreement”). In particular, allocation disagreement can be further subdivided into “Exchange” and “Shift,” allowing for a more detailed examination of spatial inconsistency patterns, making it more useful than Kappa.
Keywords
Quantity Disagreement
Allocation Disagreement
Kappa Coefficient
Raster
Remote Sensing
래스터(Raster)는 벡터(Vector)와 함께 지리정보과학의 주된 축을 이루는 공간자료 구조이자 시각화 방법임에도 불구하고 국내 학계에서는 이에 대한 연구가 제한적이다. 특히, 두 도엽의 래스터 지도를 정량적으로 비교 분석하는 것은 래스터 분석에 있어 기초가 되며, 래스터 자료 활용 및 분석에 근거한 연구의 타당성과 신뢰도에 영향을 미치므로 래스터 간 비교 결과는 정확성과 객관성 담보가 필수적이다. 전통적으로는 두 래스터가 얼마나 일치 또는 불일치하는지를 평가하기 위해 카파계수(Kappa Coefficient)가 널리 사용되고 있다. 동시에 카파계수는 비현실적인 가정과 단일 지표만 제시한다는 한계를 지적받고 있기도 하다. 본 연구에서는 지리정보과학과 원격탐사 분야에서 카파계수의 대안으로 제시되어 온 ‘불일치 요소 분해’ 방법론을 고찰하고, 이를 가상 래스터 자료에 적용해 카파계수와의 차별성 및 유용성을 비교·평가하였다. 즉, 동일한 자료에 각각의 방법론을 적용하여 그들의 차이를 해석하고 논의하였다. 그 결과, 카파계수는 단일 수치로 ‘상당한 일치’라는 모호한 결과를 도출하는데 반해, 불일치 요소 분해 방법론은 두 래스터 불일치의 주된 원인이 전체 픽셀 개수의 불일치(‘양적 불일치’)인지, 아니면 픽셀의 공간적 배치에 의한 불일치(‘위치적 불일치’)인지를 양분해 평가하는 정교함을 보여주었다. 더 나아가, 위치적 불일치는 ‘교환’와 ‘이동’ 등으로 더욱 세분할 수 있는바 보다 체계적으로 위치적 불일치의 패턴을 정량화할 수 있어 카파계수보다 더 투명하고 정확한 결과를 도출함을 확인할 수 있었다.
키워드
양적 불일치
위치적 불일치
카파계수
래스터
원격탐사
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Information
  • Publisher :The Korean Cartographic Association
  • Publisher(Ko) :한국지도학회
  • Journal Title :Journal of the Korean Cartographic Association
  • Journal Title(Ko) :한국지도학회지
  • Volume : 25
  • No :2
  • Pages :1~12
  • DOI :https://doi.org/10.16879/jkca.2025.25.2.001
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