## 1 Introduction
The connection between shadow length and tree height has also been explored in studies like the one by [PERSON] [15], which focused on Eucalyptus trees and accounted for terrain slope and aspect; this is one of the few studies examining tree heights estimation in contrast to the predominance of building-focused research. By using orthorectified images and photogrammetric data from the ADS40 airborne digital scanner, [PERSON] analyzed shadows cast by 180 Eucalyptus trees with varying canopy conditions on farmland in southeastern Australia. The study utilized 50 cm resolution multispectral aerial imagery and developed a geometric shadow model incorporating local ground slope and aspect from a Digital Elevation Model (DEM). The model calculates a \"local tree time\" to deduce the sun elevation angle, making it applicable to single-scene images and mosaicked imagery where acquisition times may be unknown. The study highlighted that accuracy depends on precise shadow azimuth and shadow length measurements. Errors arise due to the off-nadir displacement of tree canopies and shadow projection distortions. A correction factor, derived from a geometric model assuming circular canopy profiles, was introduced to improve height estimates. For accurate tree height estimation, understanding tree shape is crucial. For example, olive trees, with their broad and open canopy, cast distinctive shadows, unlike trees with central, symmetrical high points like conifers, which create different shadow patterns (Figure 1). The canopies of olive trees are typically broad and irregular, characterized by twisted branches that form an expansive, structured arrangement. Canopy density varies depending on the cultivar, training system, tree age, and cultivation practices with reference to frequency and intensity of pruning, with managed trees often pruned to optimize light exposure and fruit production. In natural settings, the canopy can appear denser and more intricate. For precise shadow identification of the tree canopy, high-resolution images, such as those from UAVs or satellites, are essential for reliable measurements. WorldView-3 (WV3) is a high-resolution Earth observation satellite known for its advanced capabilities in capturing detailed imagery [16]. It is equipped with eight spectral bands, including visible (coastal blue, blue, green, yellow, and red) and near-infrared (NIR1 and NIR2). WV3 offers a panchromatic and multispectral resolution of up to 0.31 m per pixel and 1.24 m per pixel, respectively, allowing for accurate feature identification and detailed analysis. The satellite can revisit the same location every 1 to 3 days, enabling change detection examinations. Thanks to its high spatial resolution and multispectral capabilities, WV3 imagery has proven to be a valuable tool for a wide range of applications, including environmental monitoring, agricultural management, and ecological studies. It enables the detailed analysis of vegetation patterns, species diversity, and crop characteristics, making it particularly well suited for precision agriculture and sustainable land management, as well as establishing itself as a powerful asset for remote sensing. [PERSON] et al. [17] demonstrate how WV3 imagery aids in mapping tree diversity in semi-arid environments. By leveraging the satellite's high spatial and spectral resolution, the study successfully classifies tree species and analyzes distribution patterns, highlighting the role of WV3 in supporting biodiversity and land management. In temperate montane forests, [PERSON] et al. [18] use stereo WV3 imagery along with a fusion method to improve the mapping of standing dead trees, enhancing ecological monitoring. Similarly, [PERSON] et al. [19] employ advanced image processing techniques to delineate tree crowns, demonstrating the capability of WV3 in precision forestry, urban management, and biodiversity studies. [PERSON] et al. [20] utilize WV3 imagery to remotely sense coconut trees across Tonga, contributing to agricultural monitoring and resource management. [PERSON] et al.