The cutting-edge PlanetScope CubeSat constellation provides unprecedented high spatial and temporal resolutions (3-m., daily) to facilitate vegetation monitoring. However, its data quality is usually limited by radiometric inconsistencies resulted from sensor degradation and spectral configuration differences. The existing harmonization methods often rely on internal or external references, limiting harmonization to four of the eight spectral bands or restricting applicability to localized spatiotemporal scales. To address these limitations, we proposed a novel harmonization method, namely Harmoni-Planet, that leverages graph-based greedy optimization to achieve holistic radiometric consistency across all PlanetScope bands without requiring reference data. Validated across four geographically diverse regions (the Nile, Beijing, Indonesia, and Greenland), Harmoni-Planet achieves substantial mean absolute error (MAE) reductions of 45%, 48%, 39%, and 26%, respectively, compared with smaller improvements obtained with the official algorithm (14%, 18%, 3%, and 10%, respectively). In addition to facilitating enhanced spatial and temporal comparability of PlanetScope imagery, Harmoni-Planet supports seamless integration with standard third-party reflectance products such as Landsat and Sentinel-2. Furthermore, it enables real-time harmonization for newly acquired imagery to accommodate the rapidly expanding data volume of PlanetScope constellation. Harmoni-Planet provides a practical solution to address cross-sensor radiometric inconsistencies, substantially improving the quality and reliability of PlanetScope data for diverse Earth observation applications. In addition to the proposed Harmoni-Planet method, applications of the newly harmonized PlanetScope data to monitor vegetation phenology and wild fires will also be introduced in this presentation.