## 5 Conclusions and Future Prospects  
The analysis of the results comparing olive tree heights calculated using the proposed methodology with those obtained from the drone 3D model indicates that the differences are within the decimetric range, aligning with expectations given the satellite image resolution. The primary advantage of this method over drone usage lies in its greater efficiency over large areas, as drones are typically limited to a few hectares per flight due to battery constraints. Therefore, for areas larger than a few hectares, the method proposed here is faster and more cost-effective, especially when using archived satellite imagery. Furthermore, as is well known, drone flights are subject to regulatory constraints regarding operator permits and specific areas. The proposed methodology is therefore preferable for large-scale applications and can be advantageous anyway in cases where high-resolution monoscopic satellite images are already available. It is worth emphasizing that the achieved accuracy was made possible by the careful orthorectification of the satellite image, ensuring full utilization of its intrinsic accuracy. Summarizing the results of the standard deviation analysis from the comparisons between the two datasets (drone heights and shadow-based heights), three factors were tested for their influence on the final results:  
* The ease or difficulty of identifying specific points on the canopy and shadow;
* The choice of measuring from the canopy's apex or the most recognizable point;
* The effect of terrain morphology by comparing flat and sloped areas. In all three cases, these parameters appear to have no significant influence on the final results, which are highly accurate overall. To streamline and expedite operations, the development of a specific tool, such as a plugin for an open GIS platform like QGIS, is under consideration. The experimentation conducted so far has focused exclusively on olive trees, which have a distinct canopy structure. Trees with different canopy shapes may behave differently, and the proposed method might show variations in accuracy for denser trees or asymmetrical canopies. To address this, further experimentation is needed, involving other tree species with different morphologies than those of olive trees, to more thoroughly evaluate the method's general reliability. Furthermore, additional tests will be performed to account for the multispectral characteristics of WV3 images in the classification of different land cover types, a methodology that could enhance the automatic recognition of shadows. The proposed methodology offers an innovative approach for measuring tree heights, providing a significant advantage in speed and cost-effectiveness compared to traditional techniques, such as UAV surveys, over large areas. It also benefits from the widespread availability of archived VHR monoscopic satellite images and their metadata, which are often more affordable than new acquisitions. Furthermore, this approach is particularly well suited for remote or inaccessible regions, including developing countries, where traditional methods may be limited. Conceptualization, V.B. and R.B. ; methodology, R.B., V.B. and L.M. ; software, R.B., L.M. and V.B. ; validation, R.B., V.B., L.M. and A.V. ; formal analysis, R.B., V.B., L.M. and A.V. ; resources, R.B., V.B., F.R., L.M., A.V., P.P., L.R. and R.C. ; data curation, R.B. and V.B. ; writing--original draft preparation, R.B., V.B. and L.M. ; writing--review and editing, R.B., V.B., F.R., L.M., A.V., P.P., L.R. and R.C. ; visualization, R.B., V.B., F.R., L.M. and A.V. ; supervision, V.B. ; project administration, V.B. ; funding acquisition, P.P., L.R., R.C. and A.V. All authors have read and agreed to the published version of the manuscript. This research was financially supported by the project \"PRECISOLIVO\" under the 2014-2022 Rural Development Programme of the Umbria Region, Italy. Not applicable.