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Evaluation of ALOS/PALSAR L-Band data for the estimation of Eucalyptus plantations aboveground biomass in Brazil
- Source :
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2015, 8 (8), pp.3802-3811. ⟨10.1109/JSTARS.2014.2353661⟩, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8 (8), pp.3802-3811. ⟨10.1109/jstars.2014.2353661⟩, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2015, 8 (8), pp.3802-3811. ⟨10.1109/jstars.2014.2353661⟩, Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual), Universidade de São Paulo (USP), instacron:USP
- Publication Year :
- 2015
-
Abstract
- [Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS; International audience; The Phased Array L-band Synthetic Aperture Radar (PALSAR-1) has provided very useful images dataset for several applications such as forestry. L-band radar measurements have been widely used but with somewhat contradictory conclusions on the potential of this radar wavelength to estimate the aboveground biomass. The first 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). PALSAR imagery does not allow a direct estimation of the planting date of Eucalyptus stands but can follow efficiently the occurrence of clear-cuts if images are acquired sequentially, therefore allowing a rough estimate of the following plantation date because a stand of Eucalyptus is generally re-planted 2 to 4 months after cutting. With a time series of radar images, it could be therefore possible to estimate the plantation age, and therefore improving the estimates of plantation biomass.
- Subjects :
- Atmospheric Science
Biomass
SILVICULTURA
law.invention
Âge
[SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry
law
K01 - Foresterie - Considérations générales
Biomasse
Radar
Eucalyptus
[SDE.IE]Environmental Sciences/Environmental Engineering
U10 - Informatique, mathématiques et statistiques
Aboveground biomass
Vegetation
fast-growing plantations
Plantation forestière
Imagerie
short-rotation plantations
Brazil
Synthetic aperture radar
Eucalyptus grandis
L band
Télédétection
Production forestière
Radar imaging
Computers in Earth Sciences
Croissance
Hydrology
Méthode statistique
Rotation de coupe
L-band ALOS/PALSAR
Sowing
Forestry
15. Life on land
Eucalyptus urophylla
K10 - Production forestière
Environmental science
Dendrométrie
U30 - Méthodes de recherche
Subjects
Details
- Language :
- English
- ISSN :
- 19391404
- Database :
- OpenAIRE
- Journal :
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2015, 8 (8), pp.3802-3811. ⟨10.1109/JSTARS.2014.2353661⟩, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8 (8), pp.3802-3811. ⟨10.1109/jstars.2014.2353661⟩, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2015, 8 (8), pp.3802-3811. ⟨10.1109/jstars.2014.2353661⟩, Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual), Universidade de São Paulo (USP), instacron:USP
- Accession number :
- edsair.doi.dedup.....375adad2d101520da54c99179838b1fd