Accuracy Analysis of Photogrammetry and LiDAR Point Clouds Using an iPhone 13 Pro Max

Subsidence is a geological phenomenon that continuously affects Mexico City. Over time, the impact of this phenomenon has been extensively studied using various methodologies, primarily at a regional scale. In recent years, efforts have shifted toward mapping subsidence at a local scale using technologies such as photogrammetry and LiDAR. These studies aim to establish a reference database to validate or complement regional-scale initiatives.

Field-based studies on subsidence often involve identifying problematic areas and analyzing topographical changes and structural damage over time. However, it is crucial to quantify and understand the limitations and capabilities of these techniques to establish a reference framework and ensure the reliability of the obtained data. Currently, precision methodologies are within everyone's reach thanks to technologies like photogrammetry and LiDAR from smartphones.

To achieve this, two controlled experiments (one conducted in the field and one in a laboratory setting) were carried out, in which 3D reconstructions of a box with known dimensions were made. Ten photogrammetry and ten LiDAR surveys were performed to compare the measurements obtained from the digital model with those taken from the physical object.

In the laboratory experiments, the average percentage error using photogrammetry was 1.03% (0.20 cm). Specifically, the error for a 16-cm-tall box was 1.44% (0.27 cm), while for a 20-cm-tall box, it was 0.61% (0.12 cm). For LiDAR, the average percentage error was 1.51% (0.27 cm), with errors of 1.50% (0.26 cm) for the 16-cm box and 1.52% (0.27 cm) for the 20-cm box. In field experiments, photogrammetry yielded an average percentage error of 0.88% (0.3 cm), whereas LiDAR showed an average error percentage of 2.17% (0.62 cm).

These findings confirm LiDAR and photogrammetry's potential for high-precision subsidence monitoring, providing a robust and accessible validation method. Utilizing mobile devices such as the iPhone 13 Pro Max extends the reach of these methodologies, enabling more accessible and practical research in urban contexts where subsidence poses significant challenges to infrastructure and quality of life.