Cross Validation Approach Using LANDSAT-8 and KOMPSAT-3 Forest Imagery in Korea for CAS500-4 Applications
Advances in Earth observation technologies have enabled mid-sized satellites to achieve high radiometric performance at relatively low cost, expanding their use to quantitative remote sensing applications.Compact Advanced Satellite 500-4 (CAS500-4), equipped with visible-to-near-infrared sensors including a red-edge band and designed to provide nearly 5-meter multispectral imagery every 3 days, requires a reliable radiometric monitoring framework.Cross-sensor comparison offers an efficient means of validating radiometric stability, particularly through reference sensors such as LANDSAT-8 Operational Land Imager (OLI), whose long-term calibration record ensures high radiometric consistency.This study evaluates whether forest-dominant regions on the Korean Peninsula, which represent the primary observation target of CAS500-4, can serve as suitable ground targets for cross-validation between LANDSAT-8 radiance and KOMPSAT-3 multispectral digital number (DN) values.Five KOMPSAT-3 scenes acquired near-nadir on 13 January 2025 were paired with the same-day Landsat-8 imagery.To mitigate geometric and spatial-resolution mismatches, zonal statistics and a pixel-based sliding-window sampling method (1,681 windows) were applied.Results showed that zonal-mean DN values from KOMPSAT-3 were highly stable across sliding windows, with standard deviations generally below 2 DN.Derived radiance conversion coefficients in the visible bands differed by less than 6% from previous KOMPSAT-3 radiometric studies, demonstrating the strong feasibility of the proposed method.Larger discrepancies in the near-infrared band were attributed to water-dominant landcover and nonlinear sensor response at low DN levels.Overall, forest regions exhibited stable reflectance characteristics suitable for radiometric comparison, suggesting that Korean forests provide a practical and effective foundation for CAS500-4 radiometric validation after launch.
Authors
- Byung Oh Yoo (ORCID: https://orcid.org/0000-0002-3778-5185)
- Chi-Ho Lee
- Minji Seo (ORCID: https://orcid.org/0000-0003-4883-9289)
- Joongbin Lim
- Cheonggil Jin
Institutions
- Korea Forest Service (KR)
- Institute of Forest Science (RU)
Publication Details
- Journal
- Korean Journal of Remote Sensing
- Published
- 2026-02-28
- DOI
- https://doi.org/10.7780/kjrs.2026.42.1.7
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute of Forest Science
- Korea Aerospace Research Institute