Advancing forest biodiversity visualisation through mixed reality.

Area of Science:

• Forestry
• Ecology
• Computer Science

Background:

• Forest biodiversity is crucial for ecosystem health and essential services.
• Pollution and climate change necessitate improved biodiversity assessment methods.
• Traditional visual assessment methods for forest biodiversity are limited.

Purpose of the Study:

• To develop and evaluate an interactive Mixed Reality (MR) application for visualizing forest biodiversity indicators.
• To assess the accuracy and usability of MR technology in complex forest environments.
• To explore the potential of MR for enhancing forest management and public awareness.

Main Methods:

• Development of HoloFlora, an interactive MR application for digital tree stem visualization.
• Geometric accuracy assessment of the MR application.
• Expert evaluations of the application's design, functionality, and potential for integration into forestry practices.

Main Results:

• HoloFlora achieved a geometric accuracy of 1.4 cm, setting a new benchmark for MR methods.
• The application demonstrated precise spatial information delivery in complex forest settings.
• Expert evaluations confirmed the intuitive design and functionality, with high acceptance of MR technology.

Conclusions:

• Mixed Reality technology, exemplified by HoloFlora, offers a transformative potential for forest biodiversity monitoring.
• The application's accuracy and usability support its integration into existing forest management practices.
• MR can significantly enhance biodiversity data contextualization and public engagement with conservation issues.