## 4 Discussion
Despite the area-based procedure having been demonstrated to generate satisfactory descriptions and rankings of segmentation accuracy on a case-by-case basis, the integration of supplementary non-geometric methods, such as segment spectral and texture attributes, into multivariate analyses would allow a more comprehensive evaluation, thereby enhancing the robustness of the method for accuracy assessment. A third limitation consists of the underexploitation of PlanetScope's spectral resolution, since the study used only the red and NIR bands to calculate the Normalized Difference Vegetation Index (NDVI). A fourth limitation of the study lies in the exclusive use of the local overall accuracy metric, which is inherently area-based. This metric was deliberately selected to align with the operational priorities of LPIS maintenance, where the principal objective is to determine the eligibility of agricultural surface areas, rather than to attain submeter accuracy in delineating parcel boundaries. Although vector-based accuracy assessment methods--such as those relying on boundary displacement--are valuable tools for evaluating the geometric precision of parcel outlines, they were not implemented in this study due to the positional uncertainty of the cadastral references. This uncertainty is particularly pronounced in areas characterized by complex land-use patterns and historically defined parcel geometries, which compromise the interpretability of boundary-based deviation metrics. Nonetheless, vector-based accuracy metrics could offer valuable complementary insights, especially in contexts requiring strict topological conformity. Their incorporation into future research is strongly recommended, particularly in test areas supported by highly accurate and recently updated reference boundaries. Such an extension would enable a more comprehensive evaluation of segmentation performance, encompassing both areal and linear dimensions. Future extensions of this research should continue to improve on the following key aspects. First, automating the selection of combinations of scale level and merge level should generate more segmentation output. The selection of all possible combinations of threshold values for both Edge parameters would enhance the probability of achieving the maximum possible result based on the available data. The second crucial issue to be explored is the improvement of the segments-references association step. The automation of the establishment of the one-to-one relationship and the eventual consideration of other cardinalities such as many-to-one and one-to-many could improve the process, both in terms of efficiency and accuracy. Following these paths, this workflow would become more complex to program and manage, but faster and more reliable once established. Third, the temporal component must be subjected to further examination in order to establish a parametrized relationship between the frequency of acquisitions and the segmentation results. In this context, further studies should be conducted to deepen the relationship between the phenological cycles of the plant species under examination and the patterns detectable in the time series of vegetation indexes. This will facilitate the resolution of the issue of over or under-fitting affecting the temporal sequences, thereby determining the most appropriate number of acquisitions to employ to achieve the most efficient results. Fourth, the spectral component of parcel boundaries delineation should be improved by properly exploiting the potentialities of PlanetScope's full spectral resolution. Indeed, the availability of six additional spectral bands in PlanetScope data (including the red-edge range) presents the opportunity to consider other individual bands and to construct additional vegetation indices. These could undergo further comparison and/or combination to provide improved datasets for further segmentation, yielding more comprehensive results.