## 1 Introduction  
### Background  
The introduction of virtual reality and augmented reality technologies has increased the demand for three-dimensional (3D) models [1; 2; 3; 4; 5; 6; 7; 8]. Among the various 3D modeling techniques, unmanned aerial vehicle (UAV) photogrammetry has the advantages of time and cost efficiency [1; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13]. The 3D modeling procedure using UAVs can be divided into the following three main parts: Flight planning, flight and image acquisition, and image processing. Several studies on each process have been conducted to obtain a low-cost, high-precision 3D model [1; 4; 14; 15]. Studies on optimal path planning to obtain a high-quality 3D model have been conducted in the flight planning section [16; 17; 18; 19; 20; 21; 22]. For image acquisition, optimal imaging techniques have been developed [4; 11; 23; 24]. Furthermore, concerning image processing, studies have been conducted to improve the image registration accuracy [11; 25; 26; 27]. In the process of 3D modeling using UAVs, the efficiency of both image acquisition and image processing closely depends on the flight planning stage, including path planning [11; 18; 22]. The optimal flight path of a UAV varies depending on the object's structural characteristics and the surrounding environment [1; 19; 20; 21; 22]. As a result, the optimal flight path cannot be applied to all target objects, and path planning remains dependent on the operators' skill level. While operators cannot check the quality of the 3D model during the flight path-planning process, they can create a 3D model through image processing after acquiring an image along the planned flight path. If the quality of the 3D model does not satisfy the requirements, the operator should repeat the same process of flight planning, aerial image acquisition, and image processing until the model quality is satisfactory. This entails the repeated expenditure of time and money. A simulator that allows the operator to estimate the quality of the model in advance during the planning stage is required to reduce these unnecessary expenses. While various simulators have been developed for UAV aerial photogrammetry, they still have some limits. Some, for example, support only nadir photogrammetry above the object, but not oblique photogrammetry alongside the object [28; 29]. Others can plan the path automatically but cannot check the quality of the outcome without real flight [16; 29; 30; 31; 32]. Most of the simulators are in this category, such as Pix4D, Map Pilot, Atlas Flight, Tap2 Map, UgCS, Mission Planner, APM Planner as well as MAVProxy. These simulators are incapable of detecting shaded areas or need a real flight to detect shaded areas. Some are limited in their ability to secure exact spatial objects for simulation [4; 33; 34]. DJI GS Pro and Drone Harmony are in this category. Therefore, it is difficult to find a simulator that can automatically design the path and check the quality of the 3D model from the planning step without actual flight [35]. To overcome these limitations, [PERSON] et al. developed a simulator that can plan the flight path and check the shading area of a 3D model in advance [36; 37]. The simulator can check the quality of the 3D model before flying and supports both nadir and oblique shooting. Its efficacy has also been reported in a previous study [37]. This study focused on the developed simulator's operational algorithm and the implementation of its functions. However, the validation was limited to its implementation; an examination of the algorithm, a mathematical model that serves as the simulation's foundation, or its proper operation was not included. Therefore, the performance of the simulator was not evaluated. As a result, despite the increasing demand for 3D modeling and need for UAV photogrammetry for efficient 3D modeling, the lack of development and verification of an appropriate simulator greatly hinders the utilization and advancement of UAV photogrammetry.