Land Use and Land Cover Mapping in Europe

Volume 18 of the series Remote Sensing and Digital Image Processing pp 411-427


Carbon Stock Estimation of Tropical Forests on Borneo, Indonesia, for REDD+

  • Sandra EnglhartAffiliated withRemote Sensing Solutions GmbH Email author 
  • , Jonas FrankeAffiliated withRemote Sensing Solutions GmbH
  • , Vanessa KeuckAffiliated withRemote Sensing Solutions GmbH
  • , Florian SiegertAffiliated withRemote Sensing Solutions GmbHBiology Department II, GeoBio Center, Ludwig-Maximilians-University

* Final gross prices may vary according to local VAT.

Get Access


Tropical peat swamp forests are among the most carbon rich ecosystems and are therefore in the focus of the program Reducing Emissions from Deforestation and Forest Degradation plus (REDD+), which requires accurate aboveground biomass (AGB) estimations for emission assessments. The present study evaluates different SAR frequencies and polarizations as well as spectral mixture analysis (SMA) of optical satellite data for estimating AGB on the basis of forest inventory data. Furthermore, two different approaches, continuous and discrete AGB estimation, were compared for their performance to retrieve large scale AGB estimations on the basis of multispectral data. The continuous approach relates satellite signals to field derived AGB values, while the discrete approach is based on a land cover classification by linking AGB values to each land cover class (stratify & multiply). Using the continuous approach, a correlation between AGB and SAR backscatter was found with TerraSAR-X HH and ALOS PALSAR HV data while no significant correlation was found with RADARSAT-2 HH, HV and ALOS PALSAR HH imagery. RapidEye matched filtering (MF) fractions derived from reference spectra of green vegetation (GV), soil and non-photosynthetic vegetation (NPV) were determined and all three MF fractions showed a correlation to AGB. The combined TerraSAR-X HH and ALOS PALSAR HV polarized AGB model was more accurate (r2 = 0.68) than the single-frequency models. Similarly, the combined multispectral MF fractions model was also more accurate (r2 = 0.92) than the single MF fractions models, while a synergistic use of SAR and multispectral data produced no improvements in AGB estimation. The comparison of the continuous and discrete approach based on multispectral imagery showed that the continuous AGB estimation approach depicted the spatial variability within one land cover class in contrast to the discrete approach, while it suffered from saturation either of the SAR backscatter or of the MF fractions in the higher biomass ranges. Such evaluation of AGB estimations using different satellite data and approaches considering the accuracy is considered as a relevant step for recommendations on defining MRV (Monitoring, Reporting and Verification) methods with regard to REDD+.