Estimating aboveground biomass in forest and oil palm plantation in Sabah, Malaysian Borneo using ALOS PALSAR data

Alexandra C. Morel* (Corresponding Author), Sassan S. Saatchi, Yadvinder Malhi, Nicholas J. Berry, Lindsay Banin, David Burslem, Reuben Nilus, Robert C. Ong

*Corresponding author for this work

Research output: Contribution to journalArticle

137 Citations (Scopus)

Abstract

Conversion of tropical forests to oil palm plantations in Malaysia and Indonesia has resulted in large-scale environmental degradation, loss of biodiversity and significant carbon emissions. For both countries to participate in the United Nation's REDD (Reduced Emission from Deforestation and Degradation) mechanism, assessment of forest carbon stocks, including the estimated loss in carbon from conversion to plantation, is needed. In this study, we use a combination of field and remote sensing data to quantify both the magnitude and the geographical distribution of carbon stock in forests and timber plantations, in Sabah, Malaysia, which has been the site of significant expansion of oil palm cultivation over the last two decades. Forest structure data from 129ha of research and inventory plots were used at different spatial scales to discriminate forest biomass across degradation levels. Field data was integrated with ALOS PALSAR (Advanced Land-Observing Satellite Phased Array L-band Synthetic Aperture Radar) imagery to both discriminate oil palm plantation from forest stands, with an accuracy of 97.0% (κ=0.64) and predict AGB using regression analysis of HV-polarized PALSAR data (R2=0.63, p<.001). Direct estimation of AGB from simple regression models was sensitive to both environmental conditions and forest structure. Precipitation effect on the backscatter data changed the HV prediction of AGB significantly (R2=0.21, p<.001), and scattering from large leaves of mature palm trees significantly impeded the use of a single HV-based model for predicting AGB in palm oil plantations. Multi-temporal SAR data and algorithms based on forest types are suggested to improve the ability of a sensor similar to ALOS PALSAR for accurately mapping and monitoring forest biomass, now that the ALOS PALSAR sensor is no longer operational.

Original languageEnglish
Pages (from-to)1786-1798
Number of pages13
JournalForest Ecology and Management
Volume262
Issue number9
Early online date3 Sep 2011
DOIs
Publication statusPublished - 1 Nov 2011

Keywords

  • Aboveground biomass
  • ALOS-PALSAR
  • Borneo
  • Land-cover monitoring
  • Oil palm

ASJC Scopus subject areas

  • Forestry
  • Nature and Landscape Conservation
  • Management, Monitoring, Policy and Law

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