Details zur Publikation
Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1111/2041-210X.70084
Lizenz creative commons licence
Titel (primär) Advancing plant biomass measurements: Integrating smartphone-based 3D scanning techniques for enhanced ecosystem monitoring
Autor Dietrich, P.; Elias, M.; Dietrich, P. ORCID logo ; Harpole, S. ORCID logo ; Roscher, C.; Bumberger, J. ORCID logo
Quelle Methods in Ecology and Evolution
Erscheinungsjahr 2025
Department MET; iDiv; PHYDIV
Sprache englisch
Topic T5 Future Landscapes
Daten-/Softwarelinks https://doi.org/10.5281/zenodo.14024990
Supplements https://besjournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F2041-210X.70084&file=mee370084-sup-0001-Supinfo.zip
Keywords biodiversity; photogrammetry; Scaniverse; vegetation height; vegetation structure
Abstract
  1. New technological developments open novel possibilities for widely applicable methods of ecosystem analyses. We investigated a novel approach using smartphone-based 3D scanning for non-destructive, high-resolution monitoring of above-ground plant biomass.
  2. This method leverages Structure from Motion (SfM) techniques with widely accessible smartphone apps and subsequent computing to generate detailed ecological data. By implementing a streamlined pipeline for point cloud processing and voxel-based analysis, we enable frequent, cost-effective and accessible monitoring of vegetation structure and plant community biomass.
  3. Conducted in long-term experimental grasslands, our study reveals a high correlation (R2 up to 0.9) between traditional biomass harvesting and 3D volume estimates derived from smartphone-generated point clouds, validating the method's accuracy and reliability. Additionally, results indicate significant effects of plant species richness and fertilization on biomass production and volume estimates, underscoring the potential for high-resolution temporal and spatial analyses of vegetation dynamics.
  4. This method's innovation extends beyond traditional practices with implications for future integration of AI to automate species segmentation, ecological trait extraction and predictive modelling. The simplicity and accessibility of the smartphone-based approach facilitate broader engagement in ecosystem monitoring, encouraging citizen science participation and enhancing data collection efforts. Future research will make it possible to refine the accuracy of point cloud processing, expand applications across diverse vegetation types and explore new possibilities in ecological monitoring, modelling and its application in ecosystem analyses and biodiversity research.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=30941
Dietrich, P., Elias, M., Dietrich, P., Harpole, S., Roscher, C., Bumberger, J. (2025):
Advancing plant biomass measurements: Integrating smartphone-based 3D scanning techniques for enhanced ecosystem monitoring
Methods Ecol. Evol. 10.1111/2041-210X.70084