The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle

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  • The BIOMASS mission: Materrestrial carbon cycle

    T. Le Toan a,, S. Quegan b, M.W.J.F. Rocca h, S. Saatchi i, H. Shugarta Centre d'Etudes Spatiales de la Biosphre, CNRS-CNES-Ub Centre for Terrestrial Carbon Dynamics (CTCD), Universc Mission Science Division, ESA-ESTEC, The Netherlandsd Centre for Environmental Research (CERES), Universitye Observatoire Aquitain des Sciences de l'Univers, Universf German Aerospace Center e.V. (DLR), Wessling, Germang IGBP-ESA Joint Projects Ofce, ESA-ESRIN, Italyh Dipartimento di Elettronica ed Informazione, Politecnico


    Remote Sensing of Environment 115 (2011) 28502860

    Contents lists available at ScienceDirect

    Remote Sensing o

    .e lsev ie locate / rseCarbon cycleP-band SARSatellite missionESA Earth Explorer

    afforestation. These science objectives require themission tomeasure above-ground forest biomass from70Nto 56 S at spatial scale of 100200 m, with error not exceeding 20% or 10 t ha1 and forest height witherror of 4 m. To meet the measurement requirements, the mission will carry a P-Band polarimetric SAR(centre frequency 435 MHzwith 6 MHz bandwidth)with interferometric capability, operating in a dawn-duskorbit with a constant incidence angle (in the range of 2535) and a 2545 day repeat cycle. During its 5-yearlifetime, the mission will be capable of providing both direct measurements of biomass derived from intensitydata andmeasurements of forest height derived from polarimetric interferometry. The design of the BIOMASSmission spins together two main observational strands: (1) the long heritage of airborne observations intropical, temperate and boreal forest that have demonstrated the capabilities of P-band SAR for measuringforest biomass; (2) new developments in recovery of forest structure including forest height from Pol-InSAR,and, crucially, the resistance of P-band to temporal decorrelation, which makes this frequency uniquelysuitable for biomass measurements with a single repeat-pass satellite. These two complementarymeasurement approaches are combined in the single BIOMASS sensor, and have the satisfying property thatincreasing biomass reduces the sensitivity of the former approach while increasing the sensitivity of the latter.This paper surveys the body of evidence built up over the last decade, from a wide range of airborneexperiments, which illustrates the ability of such a sensor to provide the required measurements.At present, the BIOMASS P-band radar appears to be the only sensor capable of providing the necessary globalknowledge about theworld's forest biomass and its changes. In addition, this rst chance to explore the Earth'senvironment with a long wavelength satellite SAR is expected to make yield new information in a range ofgeoscience areas, including subsurface structure in arid lands and polar ice, and forest inundation dynamics. Corresponding author. Tel.: +33 5 61 55 66 71; faxE-mail address: (T. Le To

    0034-4257/$ see front matter 2011 Elsevier Inc. Aldoi:10.1016/j.rse.2011.03.020improve resource assessment, carbon accounting and carbon models, and 2) to monitor and quantify changesin terrestrial forest biomass globally, on an annual basis or better, leading to improved estimates of terrestrialcarbon sources (primarily from deforestation); and terrestrial carbon sinks due to forest regrowth andKeywords:Forest biomassi Jet Propulsion Laboratory, Pasadena, USAj University of Virginia, Charlottesville, Virginia,k Department of Radar Systems, FOI, Linkoping, S

    a r t i c l e i n f o

    Article history:Received 29 April 2009Received in revised form 24 January 2011Accepted 16 March 2011Available online 1 June 2011pping global forest biomass to better understand the

    Davidson c, H. Balzter d, P. Paillou e, K. Papathanassiou f, S. Plummer g,j, L. Ulander k

    niversit Paul Sabatier-IRD, Toulouse, Franceity of Shefeld, UK

    of Leicester, UKit Bordeaux-1, Francey

    di Milano, Italy

    a b s t r a c t

    In response to the urgent need for improved mapping of global biomass and the lack of any current spacesystems capable of addressing this need, the BIOMASSmissionwas proposed to the European Space Agency forthe third cycle of Earth Explorer Coremissions andwas selected for Feasibility Study (Phase A) in March 2009.The objectives of the mission are 1) to quantify the magnitude and distribution of forest biomass globally to1. Introduction

    One of the mplanet is the co

    : +33 5 61 55 85

    l rights reserved.j ourna l homepage: wwwf Environment 2011 Elsevier Inc. All rights reserved.

    Biomass and the global carbon cycle

    ost unequivocal indications of man's effect on ourntinual and accelerating growth of carbon dioxide

  • (CO2) in the atmosphere. A central concern is the climate-changeimplication of increasing atmospheric CO2. The principal contributionto this growth is emissions from fossil fuel burning. However, the rateof growth is substantially less and much more variable than theseemissions because of a net ux of CO2 from the atmosphere to theEarth's surface. This net ux can be partitioned into atmosphere-ocean and atmosphere-land components, whose mean values for the1990s are 2.20.4 GtC yr1 and 1.00.6 GtC yr1 respectively(International Panel on Climate Change (IPCC), 2007). As in mostcarbon cycle calculations, CO2 uxes are reported in this paper interms of carbon units; 1 GtC=1 Pg or 1015 g of carbon.

    This simple description of the overall carbon balance concealssome major scientic issues, which we illustrate by Fig. 1:

    1. Although fossil fuel emissions, the atmospheric CO2 increase andthe net atmosphere-ocean ux are well constrained by measure-ments (IPCC, 2007), this is not true of the atmosphere-land ux. Itsvalue is estimated simply as the residual needed to close the carbonbudget after subtracting the atmospheric growth in CO2 and the netamount transferred into the oceans from the emissions. Hence itsvariance is determined indirectly as the sum of the variances of theother uxes.

    2. Fossil fuel burning forms only part of the total anthropogenic CO2

    2851T. Le Toan et al. / Remote Sensing of Environment 115 (2011) 28502860loading of the atmosphere,with anothermajor contribution comingfrom land use change. The size of this ux is poorly known, and isreported in IPCC (2007) simply as a range, shown in Fig. 1 as a lowand high value about a central value of 1.6 GtC yr1. (It is worthnoting that the lastest value put it to 1.4 GtC yr1 (Le Qur et al.,2009)).

    3. In order to balance the carbon budget, any value of land-use-changeuxmust have an associated land uptakeux, indicated in Fig. 1 as aresidual ux, since its value is derived purely as a difference ofother terms.

    Marked on Fig. 1 are the uncertainties in the well-constrainedterms; it can be seen that the uncertainties in both emissions anduptake by the land dominate the overall error budget. Fundamental tobetter quantication of these land uxes is accurate knowledge aboutthe magnitude, spatial distribution and change of forest biomass.

    More than 98% of the land-use-change ux is caused by tropicaldeforestation (IPCC, 2007), which converts carbon stored as woodybiomass (which is approximately 50% carbon) into emissions. Themost basic methods of calculating this ux simply multiply the area

    Fossil fuelemissions

    Atmospheric increase

    Fossil fuelemissions

    Atmospheric increase

    Fossil fuelemissions

    Atmospheric increase



    Fossil fuelemissions

    Atmospheric increase


    Fossil fuelemissions

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    Changes in C pools

    Fossil fuelemissions

    Atmospheric increase




    Low Low

    HighLand use

    change flux

    HighResidualland sink

    Net oceansink

    Fig. 1. Bar chart showing the anthropogenic carbon sources and the associated annualnet uxes to the carbon pools for the 1990s, with units given as GtC yr1. Theuncertainties in the well-constrained terms (fossil fuel emissions, the atmosphericincrease in CO2 and the net ocean sink) are indicated by the error bars. The land usechange ux is poorly constrained and the chart indicates the range of estimates, fromlow to high, of this quantity. In order to achieve carbon balance, there must be take-upof CO2 by the land surface, and the corresponding low and high estimates of this

    residual land sink are indicated. The data for this gure are taken from IPCC (2007).deforested (derived from national statistics or remote sensing) by theaverage biomass of the deforested area, expressed in carbon units(IPCC, 2003). More complete methods of carbon accounting wouldinclude carbon uxes from the soil, differential decay rates of carbondepending on how the biomass is used, and regrowth uxes (DeFrieset al., 2002; Houghton, 2003a, 2003b). However, both approaches areseverely compromised by lack of reliable information on the levels ofbiomass actually being lost in deforestation. This uncertainty aloneaccounts for a spread of values of about 1 GtC yr1 in different esti-mates of carbon emissions due to tropical deforestation (Houghton,2005).

    The residual land ux is of major signicance for climate, since itreduces the build-up of CO2 in the atmosphere. If we assume a landuse change ux of 1.6 GtC yr1, the total anthropogenic ux to theatmosphere in the 1990s was 8 GtC yr1. Of this, around 32.5% wasabsorbed by the land (see Fig. 1), but this value has very largeuncertainties arising from the uncertainties in the land use changeux. The uptake is highly variable from year to year, for reasons thatare poorly understood. Similar trends are seen since 2000 (Canadellet al., 2007). A key question is howmuch of this residual sink is due toxing of carbon in forest biomass.

    As a result, biomass is identied by the United Nations FrameworkConvention on Climate Change (UNFCCC) as an Essential ClimateVariable (ECV) needed to reduce uncertainties in our knowledge of theclimate system (GCOS, 2003; Sessa & Dolman, 2008). Further strongimpetus to improvemethods for measuring global biomass comes fromthe Reduction of Emissions due toDeforestation and Forest Degradation(REDD)mechanism,whichwas introduced in theUNFCCCCommitteeofthe Parties (COP-13) Bali Action Plan. Its implementation reliesfundamentally on systems to monitor carbon emissions due to loss ofbiomass from deforestation and forest degradation.

    Concerns about climate change provide a compelling reason foracquiring improved information on biomass, but biomass is alsoprofoundly important as a source of energy and materials for humanuse. It is a major energy source in subsistence economies, contributingaround 913% of the global supply of energy (i.e. 35551018 Jyr1;Haberl & Erb, 2006). The FAO provides the most widely usedinformation source on biomass harvest (FAO, 2001, 2006), but otherstudies differ from the FAO estimates of the wood-fuel harvest andforest energy potential by a factor 2 or more (Krausmann et al., 2008;Smeets & Faaij, 2007; Whiteman et al., 2002). Reducing these largeuncertainties requires frequently updated information on woodybiomass stocks and their change over time, to be combinedwith otherdata on human populations and socio-economic indicators.

    Biomass and biomass change also act as indicators of otherecosystem services. Field studies have shown how large-scale andrapid change in the dynamics and biomass of tropical forests lead toforest fragmentation and increase in the vulnerability of plants andanimals to res (Malhi & Phillips, 2004). Bunker et al. (2005) alsoshowed that above-groundbiomasswas strongly related to biodiversity.Regional to global information on human impacts on biodiversitytherefore requires accurate determination of forest structure and forestdegradation, especially in areas of fragmented forest cover. This is alsofundamental for ecological conservation. The provision of regular,consistent, high-resolution mapping of biomass and its changes wouldbe a major step towards meeting this information need.

    Despite the obvious need for biomass information, and in contrastwith most of the other terrestrial ECVs for which programmes areadvanced or evolving, there is currently no global observationprogramme for biomass (Herold et al., 2007). Until now, the onlysources of gridded global biomass (i.e. typically above-ground biomass,which is the dry weight of woody and foliar tree elements) are maps atvery coarse spatial resolutions (1/2 to 1) based largely on ground dataof unknownaccuracy (Kindermannet al., 2008;Olson et al., 1983, 2001).At regional scale, various approaches have been used to produce

    biomassmaps.Houghton et al. (2003) compared sevenbiomassmapsof

  • 2852 T. Le Toan et al. / Remote Sensing of Environment 115 (2011) 28502860the Brazilian Amazon forest produced by different methods, includinginterpolation of in situ eld measurements, modelled relationshipsbetween above-ground biomass and environmental parameters, andthe use of optical satellite data to guide biomass estimates. In thesemaps, estimates of the total amount of carbon in the Brazilian Amazonforests varied from 39 to 93 Gt of carbon, and the correlation betweenthe spatial distributions of biomass in the variousmapswas only slightlybetter than would be expected by chance (Houghton et al., 2003).

    Currently, there are severe limitations on the use of remote sensingtomeasure biomass. Optical data are not physically related to biomass,although estimates of biomass have been obtained from Leaf AreaIndex (LAI) derived fromoptical greenness indices. However, these areneither robust nor meaningful above a low value of LAI. For example,Myneni et al. (2001) used optical data from the Advanced Very HighResolution Radiometer (AVHRR) sensors to infer biomass changes innorthern forests over the period 19811999, and concluded thatEurasia was a large sink. However, both eld data and vegetationmodels indicate that the Eurasian sink is much weaker (Beer et al.,2006). Radar measurements, resulting from the interaction of theradar waveswith tree scattering elements, aremore physically relatedto biomass, but their sensitivity to forest biomass depends on the radarfrequency. C-band (ERS, Radarsat and ENVISAT ASAR) backscatter ingeneral shows little dependence on forest biomass. C-band interfer-ometric measurements do better; for example, ERS Tandem data werecombined with JERS L-band data to generate a map of biomass up to4050 t ha1with 50 mpixels covering 800,000 km2 of central Siberia(Schmullius et al., 2001). From the more recent Advanced LandObserving Satellite (ALOS) mission, launched by the Japan AerospaceExploration Agency (JAXA) in 2006, Phased Array L-band SAR(PALSAR) data are being systematically collected to cover the majorforest biomes. Recent results ( have shown PALSAR's abilityto map forest (e.g. in the Amazon and Siberia) but retrieval of forestbiomass is still typically limited to values less than 50 t ha1, whichexcludes most temperate and tropical forests. Furthermore, loss oftemporal coherence over the PALSAR repeat interval of 45 d...


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