Paper Info
Title
Estimation of Eucalyptus plantations above ground biomass in Brazil using ALOS/PALSAR L-band data
Abstract
The objective of this study was to analyze the L-band SAR backscatter sensitivity to forest biomass for Eucalyptus plantations. The results showed that the radar signal is highly dependent on biomass only for values lower than 50 t/ha, which corresponds to plantations of approximately three years of age. Next, Random Forest regressions were performed to evaluate the potential of PALSAR data to predict the Eucalyptus biomass. Regressions were constructed to link the biomass to both radar signal and age of plantations. Results showed that the age was the variable that best explained the biomass followed by the PALSAR HV polarized signal. For biomasses lower than 50 t/ha, HV signal and plantation age were found to have the same level of importance in predicting biomass. For biomasses higher than 50 t/ha, plantation age was the main variable in the random forest models. The use of PALSAR signal alone did not correctly predict the biomass of Eucalyptus plantations (R2 lower than 0.5 and RMSE higher than 46.7 t/ha). The use of plantation age in addition to the PALSAR signal improved slightly the prediction results (R2 increased from 0.88 to 0.92 and RMSE decreased from 22.7 to 18.9 t/ha).
Year
DOI
Venue
2014
10.1109/IGARSS.2014.6946525
Geoscience and Remote Sensing Symposium
Keywords
DocType
ISSN
synthetic aperture radar,vegetation,ALOS-PALSAR L-band data,Brazil,Eucalyptus plantation aboveground biomass estimation,Eucalyptus plantation biomass prediction,HV signal,L-band SAR backscatter sensitivity,PALSAR HV polarized signal,PALSAR data potential,RMSE,forest biomass,plantation age,radar signal,random forest model,random forest regression,ALOS/PALSAR,Biomass,Eucalyptus
Conference
2153-6996
Citations 
PageRank 
References 
0
0.34
0
Authors
9
Name
Order
Citations
PageRank
Nicolas Baghdadi134755.58
Guerric le Maire2316.86
Jean-Stéphane Bailly310618.29
Kenji Ose4171.75
Yann Nouvellon5233.95
Mehrez Zribi632149.20
Cristiane Lemos7142.13
Rodrigo Hakamada8142.13
le Maire, G.9213.44