## 2 Methodology
### Photogrammetry Approach  
Photogrammetry uses contact-free sensors, which makes it possible to create three-dimensional models of objects that are expensive, fragile, toxic, or visible but inaccessible. It also allows to document the changes of an object or area, such as a building construction.  
Photogrammetry suffers from a number of shortcomings such as sensitivity to light conditions. The light source can be optimized for small objects but in the case of outdoor objects and environments, optimization of lighting conditions remains a challenge.  
To create a three-dimensional model with high precision, a large number of images are needed. In general, to create an initial three-dimensional model of a single object, a minimum of two planar images with a known offset is necessary [7]. A functional and affordable method for taking thousands of images of a wide area (including tall structures such as buildings) is the use of Unmanned Aerial Vehicles (UAVs) [51, 52]. Assisted by UAVs, photogrammetry can be extended to cover areas in the scale of square kilometers.  
Figure 2 presents a procedure for using photogrammetry to create a three-dimensional model of an area/object.  
Images taken by a camera  
Calibration  
Measurement of the interior orientation  
Measurement of the exterior orientation  
As Figure 2 illustrates, obtained images should be calibrated to calculate the distance between the camera and the object [53]. In the figure, exterior orientation means calculation of the exterior coordinates, which are the location of the projection center and the rotation angles of the object with respect to the considered global coordinate system. Surface modeling can be applied to the object to visualize the texture. In the final step, postprocessing is done to create a three-dimensional model of the object.  
To put it simply, photogrammetry creates three-dimensional models out of planar images. To this end, postprocessing software compares two images taken of an object or area and recognizes identical points, see Figure 3. \"Overlapping\" between images helps to simplify the identical point recognition process and increases the quality of the object's texture. In addition, \"shape matching\" can be assisted to match corresponding points in two overlapping images. Shape matching technique has different varieties. One common technique compares the shape of objects in two images without color consideration. This simplifies the process and reduces computational time. By considering corresponding points and the orientation of the cameras, the location of points in the three-dimensional environment can be estimated.  
Even though the photogrammetry approach is extensively used to generate virtual realistic environments, it still faces some barriers and limitations. In most cases, the geometry and exact location of the object under investigation should be estimated. Transparent and dark colored objects, as well as tiny objects, pose challenges for photogrammetry [27, 54, 55]. Furthermore, there are some limitations when using photogrammetry and laser scanning procedures. Objects that are small, shiny, and transparent cannot be accurately captured in photogrammetry and laser scanning procedures. In addition, materials that absorb or diffuse the laser beams, are barriers to accurately collecting point cloud data during the laser scanning procedure.  
Figure 2: Overview of the photogrammetry procedure.