Terrestrial Laser Scanning for Estimating the Volume and Biomass of Coniferous Stems in the Mariposa Monarca Biosphere Reserve, Mexico
The accurate estimation of tree volume and biomass is necessary for forest ecosystems management. However, traditional estimation methods are expensive, require a large amount of labor and materials, and may involve destructive sampling. In this study, a terrestrial laser scanner (TLS) and free software were used to estimate the volume and biomass of the stems of individual trees from two coniferous species, Abies religiosa (Kunth) Schltdl. & Cham and Pinus pseudostrobus Lindl, in the Monarch Butterfly Biosphere Reserve (MBBR), Michoacan, Mexico. TLS is an alternative to traditional measurement methods, which allows tree measurements to be extracted from a point cloud, opening up new opportunities to characterize the volume and biomass of standing trees. The simple linear regression analysis comparing stem volume and biomass estimates from different methods shows that the Vol_TLS and Vol_TModel relationship provides a better fit (R2 = 0.97, RMSE = 0.351 m3) compared to the Vol_TLS and Vol_OModel relationship (R2 = 0.93, RMSE = 0.537 m3). However, comparisons between measurements with predictive models (from destructive methods) and TLS (a non-destructive method) did not show significant differences. The results show that this increasingly accessible technology can be used to adequately estimate forest biomass and volume in a non-destructive manner, which is particularly important in places such as the MMBR.
Authors
- Diego R. Pérez‐Salicrup (ORCID: https://orcid.org/0000-0002-7024-9042)
- Alejandro Velázquez‐Martínez (ORCID: https://orcid.org/0000-0001-5560-9292)
- Felipe Bravo (ORCID: https://orcid.org/0000-0001-7348-6695)
- José Antonio Hernández Moreno (ORCID: https://orcid.org/0000-0002-1009-4595)
- Valentín José Reyes-Hernández (ORCID: https://orcid.org/0000-0002-1804-412X)
- David W. MacFarlane (ORCID: https://orcid.org/0000-0001-7781-3390)
Institutions
- Universidad de Valladolid (ES)
- Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (MX)
- Colegio de Postgraduados (MX)
- Michigan State University (US)
- Universidad Nacional Autónoma de México (MX)
Publication Details
- Journal
- Forests
- Published
- 2025-02-13
- DOI
- https://doi.org/10.3390/f16020334
- Citations
- 3
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.40
Funders
- Universidad de Valladolid