As satellite launching increases worldwide, uncertainty quantification for satellite data becomes essential. Misunderstanding satellite data uncertainties can lead to misinterpretations of natural phenomena, emphasizing the importance of validation. In this study, we established a tower-based network equipped with multispectral sensors, SD-500 and SD-600, to validate the satellite-derived NDVI product. Multispectral sensors were installed at eight long-term ecological monitoring sites managed by NIFoS. High correlations were observed between both multispectral sensors and a hyperspectral sensor, with correlations of 0.76 and 0.92, respectively, indicating that the calibration between SD-500 and SD-600 was unnecessary. High correlations, 0.8 to 0.96, between the tower-based NDVI with Sentinel-2 NDVI, were observed at most sites, while lower correlations at Anmyeon-do, Jeju, and Wando highlighting challenges in evergreen forests, likely due to shadows in complex canopy structures. In future research, we aim to analyze the uncertainties of surface reflectance in evergreen forests and develop a biome-specific validation protocol starting from site selection. Especially, the integration of tower, drone, and satellite data is expected to provide insights into the effect of complex forest structures on different spatial scales. This study could offer insights for CAS500-4 and other satellite validations, thereby enhancing our understanding of diverse ecological conditions.
Keywords: NDVI; multispectral sensor network; sentinel-2; validation practice.