Use of LiDAR data during multi-annual periods for estimating forestry variables
- Valbuena, Manuel A. 1
- Mateos, Esperanza 2
- Rodríguez, Francisco 3
- 1 Education Department of the Basque Government, IES Murguia (Araba-Álava)
- 2 University of the Basque Country UPV/EHU, Department of Chemical and Environmental Engineering
- 3 Fora Forest Technologies SLL. Soria, Spain
ISSN: 2171-5068
Any de publicació: 2017
Volum: 26
Número: 3
Tipus: Article
Altres publicacions en: Forest systems
Resum
Aim of study: To test the use of LiDAR data from a single acquisition in order to estimate volume overbark variations ina 5-yr period of Pinus radiata D. Don.Area of study: Province of Bizkaia in the Autonomous Community of the Basque Country (Spain).Material and methods: Two field plot measurements were made in 2011 and 2015 and two wood volume models (one for each year) were fitted using the metric variables of the 2012 LiDAR points cloud. The models were applied to a 26.59 m raster covering the study area and the increase in volume at each pixel was calculated by subtraction.Main results: The increase in estimated wood volume, when added to the volume of timber extracted in the area during the 5-yr period under consideration, yielded an average increase of 13.74 m3 ha-1 yr-1, which corresponds to the average growth of the P. radiata in that area. The harvest area estimated using this procedure largely coincides with the actual harvest area in the same period. The value of R2 (85%) of the wood volume model for 2011 is similar to that obtained in other studies. However, as expected, the one obtained for the wood volume model for 2015 (80%) is significantly lower.Research highlights: The increase in wood volume can be estimated using a single LiDAR flight and field data from the 5-yr period provided that data from plots subjected to this kind of harvest is included in the models.
Informació de finançament
Area of study: Province of Bizkaia in the Autonomous Community of the Basque Country (Spain). Material and methods: Two field plot measurements were made in 2011 and 2015 and two wood volume models (one for each year) were fitted using the metric variables of the 2012 LiDAR points cloud. The models were applied to a 26.59 m raster covering the study area and the increase in volume at each pixel was calculated by subtraction. Main results: The increase in estimated wood volume, when added to the volume of timber extracted in the area during the 5-yr period under consideration, yielded an average increase of 13.74 m3 ha-1 yr-1, which corresponds to the average growth of the P. radiata in that area. The harvest area estimated using this procedure largely coincides with the actual harvest area in the same period. The value of R2 (85%) of the wood volume model for 2011 is similar to that obtained in other studies. However, as expected, the one obtained for the wood volume model for 2015 (80%) is significantly lower. Research highlights: The increase in wood volume can be estimated using a single LiDAR flight and field data from the 5-yr period provided that data from plots subjected to this kind of harvest is included in the models. Additional keywords: LiDAR forest inventory; wood volume increase; wood volume LiDAR model. Abbreviations used: CCF (Canopy Cover Fraction); CV (Coefficient of Variation); Dm (Mean Diameter); G (basal area, m2 ha-1); Hm (mean height, m); Ho (top height, m); IFN4 (4th National Forest Inventory); LiDAR (Light Detection and Ranging); MAE (Mean Absolute Error); ME (Mean Error); RMSE (Root Mean Square Error); Vob (stem volume over bark, m3 ha-1). Authors´ contributions: MAV conceived and designed the experiments and contributed to writing, data production, and analysis. EM wrote the introduction and reviewed the work. FR revised the statistical calculations and fitted models. Citation: Valbuena, M. A.; Mateos, E.; Rodríguez, F. (2017). Use of LiDAR data during multi-annual periods for estimating forestry variables. Forest Systems, Volume 26, Issue 3, e019. https://doi.org/10.5424/fs/2017263-11468 Received: 28 Mar 2017. Accepted: 10 Jan 2018. Copyright © 2017 INIA. This is an open access article distributed under the terms of the Creative Commons Attribution (CC-by) Spain 3.0 License. Funding: Gobierno Vasco (Projects SAI10/147-SPE10UN90); Vicerrectorado de Investigación de la Universidad del País Vasco-Euskal Herriko Unibertsitatea (UPV/EHU) (Project NUPV14/11). Competing interests: The authors have declared that no competing interests exist. Correspondence should be addressed to Manuel A. Valbuena: mavalbuena66@gmail.com; valbuena@irakasle.eusFinançadors
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- NUPV14/11
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