## 5 Conclusions  
This study demonstrated the feasibility and effectiveness of integrating PlanetScope multitemporal imagery into a segmentation-based workflow aimed at enhancing the delineation of land parcels for the Land Parcel Identification System (LPIS). By leveraging the dense temporal frequency and high geometric resolution of PlanetScope data, the proposed method successfully generated segmentation outputs that approached the accuracy levels of outputs derived from conventional aerial orthophotos.  
The results underscore the value of transitioning from a static, mono-temporal LPIS model to a dynamic, multitemporal paradigm that accounts for the phenological evolution of vegetation. This temporal enrichment enables more robust and contextually accurate delineation of parcel boundaries, especially in cases in which single-date acquisitions may fail to capture representative land conditions. Moreover, the inclusion of tailored geometric metrics in the accuracy-assessment framework--alongside the introduction of a nuanced error-type identification based on area differences--has provided a replicable and informative methodology for assessing segmentation performance.  
Nonetheless, the study identifies several avenues for refinement. Future work should explore automated parameter optimization for segmentation, as well as the development of objective, scalable methods for associating segmented parcels with reference data. Additionally, integrating spectral- and texture-based accuracy metrics and fully exploiting PlanetScope's spectral resolution could further improve segmentation accuracy. Comparative evaluations with other high-resolution (HR) and VHR optical missions would also help to contextualize the operational advantages and trade-offs of PlanetScope imagery within CAP monitoring frameworks. Additionally, future research should explore the integration of machine and deep learning techniques for improving parcel delineation from spaceborne imagery, leveraging their strengths and considering current limitations. Additionally, future work should tackle the challenge of extracting parcel boundaries in fragmented agricultural areas, requiring refined segmentation strategies to enhance performance in complex, low-contrast landscapes and support broader LPIS modernization.  
In conclusion, while preliminary, this research supports the hypothesis that satellite data with very high geometric and temporal resolution, when processed through appropriate segmentation workflows, holds substantial potential to improve LPIS practices. The integration of multitemporal VHR spaceborne observations may represent a critical step toward more efficient, accurate, and scalable monitoring systems to support the disbursal of agricultural subsidies across the European Union.  
Conceptualization, P.B. and M.O.; methodology, P.B. and M.O.; software, M.O.; validation, M.O.; formal analysis, M.O.; investigation, P.B. and M.O.; resources, P.B.; data curation, M.O.; writing--original draft preparation, M.O.; writing--review and editing, P.B. and M.O.; visualization, M.O.; supervision, P.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.