## 4 Discussion  
The primary aim of this experiment was to evaluate whether and with what level of accuracy olive tree heights can be estimated from high-resolution and very-high-resolution monoscopic satellite images, i.e., without employing stereoscopy. The reference data in this case consisted of the heights of the same olive trees measured using three-dimensional models derived from photogrammetric surveys conducted via drone, almost concurrently with the satellite image acquisition. The three-dimensional drone data serve as a reliable reference due to their higher accuracy, provided that the following points are clarified:  
* The satellite image was orthorectified using a photogrammetrically rigorous model [40], 20 ground control points (GCPs) measured with GNSS RTK receivers, and a digital elevation model (DEM) derived from 1:5000 scale vector cartography. The estimated planimetric accuracy of this orthorectification, based on independent check points (CPs), is approximately 20 cm. It should be noted that such planimetric accuracy cannot be achieved with raw satellite images or without the use of GCPs acquired via differential GPS/GNSS;
* The two drones used are equipped with GNSS/GPS RTK receivers, enabling a planimetric accuracy of a few centimeters and an altimetric accuracy of about one decimeter. Most drones currently in use do not employ RTK technology but rely solely on autonomous GNSS positioning, with accuracies of approximately 10 m planimetrically and 15 m in height. The accuracy of the drone-derived models was anyway further validated through comparisons with additional GCPs;  
Figure 15: Box plot of the differences between heights calculated using Equation (1) and those measured via UAV for Tests 1a, 1b, 2, and 3.  
* The coordinates of the two surveys are compatible and comparable, as both are referenced to the same realization of the WGS84 datum (EPSG:6708 RDN2008/UTM zone 33N (N-E)) materialized by the same Continuously Operating Reference Station Network (CORSN) managed by the Umbria region [31];
* The respective planimetric accuracies of the two methods, with expected maximum deviations of a few decimeters, ensure the consistency of the comparative test, as they prevent the possibility of confusing one olive tree with another within the same row. The use of differential GNSS positioning technologies (here employed in RTK mode) is crucial for avoiding such misidentifications.  
After verifying that the planimetric and altimetric accuracies in the current configuration were sufficient to render the comparison with the drone data meaningful, subsequent tests were conducted to separately assess specific factors that could potentially reduce the accuracy and significance of the proposed methodology's results.  
The three primary challenges identified during the experimentation were as follows:  
* The difference between measurements at the tree's apex and those at the most easily recognizable point on its shadow;
* The influence of the recognizability of the measured points on the shadow and the corresponding olive tree canopy image;
* The impact of terrain slope, which, for simplicity, is considered constant over the length of the shadow. For this purpose, an average value derived from the reference DEM is used.