A Biomass Map of African Savannas at a Spatial Resolution of 100 meters using ALOS PALSAR Dual-Polarization Data
Bouvet, Alexandre1; Mermoz, Stéphane2; Le Toan, Thuy2
1CESBIO, FRANCE; 2Center for Spatial Studies on the Biosphere (CESBIO), FRANCE

Recently, it was recognized that Africa is a major source of interannual variability in global atmospheric CO2, although Africa contributes less than 4 % of the global fossil fuel emissions. In a review of the most recent estimates of the net long-term carbon balance of African ecosystems [1], the uncertainties associated with these estimates are rather high, as shown by the different results indicating that the carbon balance of African ecosystems varies from a sink of about 3.2 Pg.ha-1 to a small source. In Africa, savannas cover roughly 50 % of the continent and the main savanna vegetation types are woodlands, tree and shrub savannas, forest and savanna mosaic. While dense forests have been relatively spared from massive deforestation in Africa, with a deforestation rate of 0.05% per year reported in Congo for the 2005-2010 period [2], savanna woodlands, in contrast, were found to be struck by a rapid deforestation, with, for example, a rate of 2.75% reported for Uganda for the same period. The studies mentioned in [1] therefore pointed out the need to consider the contribution of savanna in the overall carbon budget when determining the direction of the African carbon budget (sink or source).
Many studies have shown that long wavelength radar data are sensitive to forest biomass, and mapping of above-ground biomass (AGB) has been demonstrated using P- and L-band backscatter data. Whereas P-band data are expected to be used for a larger range of AGB values, only spaceborne L-band data from ALOS PALSAR are currently available for studies. As a result, L-band has been extensively assessed for estimating AGB. Literature results suggest that there is an AGB saturation level (usually in the range of 75-150 Mg.ha-1) above which the L-band backscatter intensity does not increase with an increase in AGB. As a result, PALSAR data cannot be used to derive AGB of dense tropical forest (up to 300-400 Mg.ha-1), but appear well adapted to the retrieval of AGB of savanna woodlands (typically less than 100 Mg.ha-1).

In this study, ALOS PALSAR data have been used to map the above ground biomass (AGB) in savanna ecosystems in Sub-Saharan Africa. The study has been motivated by the need to have estimates of carbon in African savannas, and facilitated by the recent availability of L-band PALSAR mosaic data, suitable to the retrieval of savanna biomass (typically less than 100 Mg.ha-1) at country and continental scales.
The work is based on a mosaic of dual-polarization PALSAR data (HH and HV) covering the whole African continent, which was produced at the European Commission Joint Research Center [3] in the frame of the ALOS K&C initiative. In a previous study, the PALSAR mosaic has been transformed into a map of the percent tree cover in Sub-Saharan Africa [4], using a supervised classification based on the Vegetation Continuous Field (VCF) dataset. This map assigns each pixel to one of the seven following percent tree cover classes: 0-10%, 10-20%, 20-30%, 30-40%, 40-50%, 50-60%, and >60%. The map therefore provides an efficient way to mask out dense forests, and constitutes a first indicator of the vegetation density in savannas.
The method to transform the PALSAR mosaic into an AGB map is inspired by the recent work by Mermoz et al. [5], who developed a regression model using data from the same sensor to produce a biomass map of the savannas in Cameroon. The extension of the method to the PALSAR mosaic requires only small adjustments to be made. The regression model needs to be fitted regionally in order to account for the diversity of ecosystems and differences of seasonality in the mosaic. The model was chosen in [5] so that only a limited number of in situ plots are needed for its calibration. We use in situ data and estimates of AGB from several sources for this purpose. An emphasis is put on the uncertainties assessment, providing for each product resolution cell an uncertainty associated to the retrieved biomass.


[1] P. Ciais, A. Bombelli, M. Williams, S. Piao, J. Chave, C. Ryan, M. Henry, P. Brender, R. Valentini, ''The carbon balance of Africa: synthesis of recent research studies'', Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369, 2038-2057, 2011.

[2] FAO, '' Global forest resources assessment. Technical Report.'', Food and Agriculture Association of the United Nations, 2010

[3] GF. De Grandi, A. Bouvet, R. Lucas, M. Shimada, S. Monaco, A. Rosenqvist, ''The K&C PALSAR mosaic of the African continent: processing issues and first thematic results'', IEEE Transactions on Geoscience and Remote Sensing, vol. 49 n°10, pp. 3593-3610, October 2011

[4] A. Bouvet, G. De Grandi, ''A percent tree cover map of Sub-Saharan Africa at a spatial resolution of 100 meters using ALOS PALSAR dual-polarization data'', Remote Sensing of Environment, submitted

[5] S. Mermoz, T. Le Toan, L. Villard, M. Réjou-Méchain, J. Seifert-Granzin, ''Biomass assessment in Cameroon savanna using ALOS PALSAR data'', Remote Sensing of Environment, submitted