Harmonized Planet Scope and Sentinel-2 Data for Agricultural Monitoring in Gimje Paddy Area

This study presents a prototype harmonized surface reflectance dataset generated by integrating PlanetScope (SuperDove) and Sentinel-2 (MSI) imagery following the NASA-ESA Harmonized Landsat-Sentinel-2 (HLS) framework.Atmospheric correction of PlanetScope imagery using the Land Surface Reflectance Code (LaSRC) algorithm effectively reduced scene-to-scene variability and improved aerosol retrieval, resulting in more stable surface reflectance.PlanetScope reflectance was then normalized to the HLS standard, yielding substantial improvements in radiometric consistency, with regression slopes approaching one and coefficients of determination (R) increasing to 0.91-0.93 for the Red and Near-Infrared (NIR) bands.Time-series evaluation using Normalized Difference Vegetation Index (NDVI) demonstrated that the harmonized PlanetScope NDVI closely reproduced the phenological trajectory observed in HLS, confirming the potential of high-resolution, high-frequency imagery for agricultural monitoring.The findings provide an important technical foundation for applying similar harmonization strategies to the upcoming Korean agricultural satellite, the Compact Advanced Satellite 500-4 (CAS500-4).Further research is required to expand validation across seasons, crop types, and diverse observation conditions.In addition, the prototype results suggest that the integration of satellite data can substantially enhance temporal continuity during cloud-affected seasons.These outcomes highlight the need to expand validation across broader spatial domains and crop systems to further generalize the harmonization framework.