Skip to Main Content
Mapping aboveground carbon stocks using LiDAR data in Eucalyptus spp. plantations in the state of Sao Paulo, BrazilAuthor(s): Carlos Alberto Silva; Carine Klauberg; Samuel de Padua Chaves e Carvalho; Andrew T. Hudak; e Luiz Carlos Estraviz Rodriguez
Source: Scientia Forestalis. 42(104): 591-604.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
PDF: Download Publication (918.74 KB)
DescriptionFast growing plantation forests provide a low-cost means to sequester carbon for greenhouse gas abatement. The aim of this study was to evaluate airborne LiDAR (Light Detection And Ranging) to predict aboveground carbon (AGC) stocks in Eucalyptus spp. plantations. Biometric parameters (tree height (Ht) and diameter at breast height (DBH)) were collected from conventional forest inventory sample plots. Regression models predicting total aboveground carbon (AGCt), aboveground carbon in commercial logs (AGCc), and aboveground carbon in harvest residuals (AGCr) from LiDAR-derived canopy structure metrics were developed and evaluated for predictive power and parsimony. The best models from a family of six models were selected based on corrected Akaike Information Criterion (AICc) and assessed by the root mean square error (RMSE) and coefficient of determination (R²-adj). The best three models to estimate AGC stocks were AGCt: R²-adj = 0.81, RMSE = 7.70 Mg.ha-1; AGCc: R²-adj = 0.83, RMSE = 5.26 Mg.ha-1; AGCr: R²-adj = 0.71, RMSE = 2.67 Mg.ha-1. This study showed that LiDAR canopy structure metrics can be used to predict AGC stocks in Eucalyptus spp. plantations in Brazil with high accuracy. We conclude that there is good potential to monitor growth and carbon sequestration in Eucalyptus spp. plantations using LiDAR.
- You may send email to firstname.lastname@example.org to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationSilva, Carlos Alberto; Klauberg, Carine; Carvalho, Samuel de Padua Chaves e; Hudak, Andrew T.; Rodriguez, e Luiz Carlos Estraviz. 2014. Mapping aboveground carbon stocks using LiDAR data in Eucalyptus spp. plantations in the state of Sao Paulo, Brazil. Scientia Forestalis. 42(104): 591-604.
KeywordsAirborne Laser Scanning ALS, LiDAR metrics, C stock, fast growing plantation
- Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast‑growing Eucalyptus forest plantation using airborne LiDAR data
- Eucalyptus Forest Information System for the Portuguese pulp and paper industry
- A principal component approach for predicting the stem volume in Eucalyptus plantations in Brazil using airborne LiDAR data
XML: View XML