# Evaluating the Supplementary Role of Photogrammetry in Insect Taxonomy: Applications and Limitations of 3D Scanning Technology

## TL;DR

This study explores how 3D scanning can help identify insects, showing it works well for larger specimens but has limits for smaller ones.

## Contribution

The study introduces a cost-effective 3D scanning method for insect taxonomy with potential for education and conservation.

## Key findings

- Six of ten insect specimens were identified to species level using 3D scans.
- Thresholds of 10.7 mm body length and 4.4 mm width determine reliable feature resolution.
- 3D scanning supports traditional taxonomy but has limitations for small specimens.

## Abstract

The integration of high‐resolution 3D photogrammetry in insect taxonomy offers potential enhancements to traditional classification methods, particularly in educational and resource‐limited settings. This study assesses the Artec Micro scanner's capability to capture detailed external phenotypic features of insects across a size spectrum from 1.63 to 33.49 mm. Ten samples from unique species were mounted and scanned. The model outputs were evaluated against an identification key, which compiled diagnostic features for the specimens from the wider literature, to describe the specimens to the lowest taxonomic level possible. The results showed that six of the ten specimens could be identified to species level using the scans. Threshold values for body length and width were 10.7 and 4.4 mm, respectively. Below these body dimensions, important diagnostic features of specimens could not be resolved reliably. This result outlines the limitations of this technology and highlights the supportive role that this approach can provide when integrated with traditional taxonomic methods. This approach opens up novel applications for species identification and data sharing among taxonomists, international field research, conservation efforts and entomological outreach. However, the limitations of this approach to taxonomic identification must be considered depending upon the size of the specimen and its diagnostic features. Future developments could enhance this technology's application in routine taxonomic work, particularly through integration with artificial intelligence platforms.

Our study presents a cost‐effective 3D scanning approach to enhance taxonomic identification, particularly for archival and educational applications. By allowing the scanning of pinned specimens without damage, this method supplements traditional taxonomy while promoting accessibility and conservation efforts.