## 1 Introduction
In the last decade, PPP with ambiguity resolution (PPP-AR) techniques have advanced from experimental to practical solutions [14]. PPP-AR improves the convergence time by shortening it and stabilizes the result in kinematic PPP research [15]. A comprehensive range of studies has been conducted to evaluate the precision of positioning in UAV photogrammetry [8; 9; 10; 11]. These studies have revealed various findings on direct or indirect georeferencing. Current research is generally directed towards reducing dependence on GCPs. Determining the optimum GCP distribution and number is an important research area. [PERSON] et al. [16] investigated the effect of GCP number and distribution on location accuracy in UAV-based orthophoto generation. Five scenarios were produced with four GCPs in the study. However, vertical accuracy was not included in the study. [PERSON] et al. [17] analyzed the impact of the number and distribution of GCPs on the horizontal and vertical accuracy of photogrammetric products on glaciers. Different GCP distribution scenarios were used to optimize the models generated with PPK coordinates. [PERSON] et al. [18] used the RTK-UAV to examine the accuracy decrease due to the lack of RTK signal in certain areas and mentioned that if one GCP is installed at the take-off point and post-process kinematic (PPK) is applied, in the case of a ground sampling distance (GSD) of about 3 cm, there may be an error level of H = 10 cm and Z = 20 cm up to a radius of 1 km. [PERSON] et al. [19] investigated the accuracy improvement gained from using specific GCPs versus not employing any GCPs. The study by [PERSON] et al. [20] searched to assess the effectiveness of real-time and post-processed GNSS kinematic point positioning techniques in UAV-based photogrammetric mapping accuracy. The effect of adjustment with GCPs was also examined. [PERSON] et al. [21] intended to assess the effectiveness of UAV photogrammetry georeferencing in the absence of GCPs and to evaluate its feasibility for applications in the Antarctic region. [PERSON] et al. [22] introduced a novel methodology for positioning GCPs, focusing on the impact of the PPP technique on model accuracy, which significantly deviates from the current literature. Additionally, this research aims to assess how effective the PPP method is over different observation periods to determine the ideal duration for GNSS sessions. There are also studies comparing the effects of positioning techniques for UAV-based photogrammetry. [PERSON] et al. [23] evaluated the geolocation accuracy of UAV mosaicked images of an abandoned mine by comparing orthomosaics and DEMs using standalone GNSS, differential GNSS, and PPP techniques. [PERSON] et al. [24] aimed to employ simultaneous differential corrections from several GNSS fixed base stations to increase the accuracy of UAV photogrammetry projects based on onboard GNSS RTK. [PERSON] et al. [25] analyzed the data collected by UAVs in kinematic mode according to the PPP technique in open-source and web-based GNSS processing software and compared it with the results obtained from photogrammetric software. [PERSON] et al. [26] compared the results of PPP-AR and PPK processing of the collected GNSS data in photogrammetric studies performed with two different flights. The 3D positioning analyses showed a difference distribution between 0 and 6 cm for both kinematic PPP and PPK results. [PERSON] et al. [27] showed a linear correlation between the computed internal orientation parameters (focal length) variance and the systematic height inaccuracy in models that only use onboard GNSS RTK data. [PERSON] et al. [28] aim to evaluate the accuracy of UAV RTK/PPK direct georeferencing and the potential for rapid mapping in natural environments, including buildings and low vegetation. [PERSON] et al. [15] investigated the performance of PPP and PPP-AR solutions derived from kinematic GNSS data obtained from UAVs by comparing them with PPP solutions based on relative positioning.