Global biomass mapping for an improved understanding of the CO2 balance—the Earth observation mission Carbon-3D

Understanding global climate change and developing strategies for sustainable use of our environmental resources are major scientific and political challenges. In response to an announcement of the German Aerospace Center (DLR) for a national Earth observation (EO) mission, the Friedrich-Schiller University Jena and the JenaOptronik GmbH proposed the EO mission Carbon-3D. The data products of this mission will for the first time accurately estimate aboveground biomass globally, one of the most important parameters of the carbon cycle. Simultaneous acquisition of multiangle optical with Light Detection and Ranging (LIDAR) observations is unprecedented. The optical imager extrapolates the laser-retrieved height profiles to biophysical vegetation maps. This innovative mission will reduce uncertainties about net effects of deforestation and forest regrowth on atmospheric CO2 concentrations and will also provide key biophysical information for biosphere models.

[1]  D. Coomes,et al.  Long-Term Effects of Wildfire on Ecosystem Properties Across an Island Area Gradient , 2003, Science.

[2]  Frédéric Baret,et al.  SPECTRA - Surface Processes and Ecosystem Changes Through Response Analysis , 2004 .

[3]  I. C. Prentice,et al.  An integrated biosphere model of land surface processes , 1996 .

[4]  C. Tucker,et al.  A large carbon sink in the woody biomass of Northern forests , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Masanobu Shimada,et al.  Support to multi-national environmental conventions and terrestrial carbon cycle science by ALOS and ADEOS-II -the Kyoto & carbon initiative , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[6]  Alan H. Strahler,et al.  An algorithm for the retrieval of albedo from space using semiempirical BRDF models , 2000, IEEE Trans. Geosci. Remote. Sens..

[7]  Malcolm Davidson,et al.  Accuracy assessment of a large-scale forest cover map of central Siberia from synthetic aperture radar , 2002 .

[8]  Christopher B. Field,et al.  Initiative to quantify terrestrial carbon sources and sinks , 2002 .

[9]  Masanobu Shimada,et al.  Initiating the ALOS Kyoto & Carbon Initiative , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[10]  Maurizio Santoro,et al.  Stem volume retrieval in boreal forests from ERS-1/2 interferometry , 2002 .

[11]  I. C. Prentice,et al.  Climatic Control of the High-Latitude Vegetation Greening Trend and Pinatubo Effect , 2002, Science.

[12]  Mukunda Dev Behera,et al.  Lidar remote sensing for forestry applications: The Indian context , 2002 .

[13]  C. Tucker,et al.  Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999 , 2003, Science.

[14]  G. Roberts.  A review of the application of BRDF models to infer land cover parameters at regional and global scales , 2001 .

[15]  Jason Beringer,et al.  The use of a reduced form model to assess the sensitivity of a land surface model to biotic surface parameters , 2002 .

[16]  R. Dubayah,et al.  Above-ground biomass estimation in closed canopy Neotropical forests using lidar remote sensing: factors affecting the generality of relationships , 2003 .

[17]  G. Asner.  Contributions of multi‐view angle remote sensing to land‐surface and biogeochemical research , 2000 .

[18]  Konstantinos P. Papathanassiou,et al.  Polarimetric SAR interferometry , 1998, IEEE Trans. Geosci. Remote. Sens..

[19]  W. Cohen,et al.  Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests , 1999 .

[20]  Irena Hajnsek,et al.  Forest biomass estimation using polarimetric SAR interferometry , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[21]  W. Cohen,et al.  Integration of lidar and Landsat ETM+ data for estimating and mapping forest canopy height , 2002 .

[22]  Thuy Le Toan,et al.  Relating forest biomass to SAR data , 1992, IEEE Trans. Geosci. Remote. Sens..

[23]  Joanna Isobel House,et al.  Reconciling apparent inconsistencies in estimates of terrestrial CO2 sources and sinks , 2003 .

[24]  F. Woodward,et al.  Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models , 2001 .

[25]  Unfccc.  Kyoto Protocol to the United Nations Framework Convention on Climate Change , 1997 .

[26]  H. Zwally.  ICESat's Laser Measurements of Polar Ice and Atmospheres , 2003 .

[27]  S. Nilsson,et al.  Dynamics of Russian Forests and the Carbon Budget in 1961–1998: An Assessment Based on Long-Term Forest Inventory Data , 2002 .

[28]  Stephen Sitch,et al.  The Carbon Balance of the Terrestrial Biosphere: Ecosystem Models and Atmospheric Observations , 2000 .

[29]  W. Lucht,et al.  Terrestrial vegetation and water balance-hydrological evaluation of a dynamic global vegetation model , 2004 .

[30]  Guoqing Sun,et al.  Mapping of boreal forest biomass from spaceborne synthetic aperture radar , 1997 .

[31]  Michael T. Coe,et al.  Testing the performance of a dynamic global ecosystem model: Water balance, carbon balance, and vegetation structure , 2000 .

[32]  J. Townshend,et al.  A new global 1‐km dataset of percentage tree cover derived from remote sensing , 2000 .

[33]  F. Veroustraete,et al.  Estimation of carbon mass fluxes over Europe using the C-Fix model and Euroflux data , 2002 .

[34]  R. Dubayah,et al.  Estimation of tropical forest structural characteristics using large-footprint lidar , 2002 .

[35]  J. Muller,et al.  New directions in earth observing: Scientific applications of multiangle remote sensing , 1999 .

[36]  Heiko Balzter,et al.  Biomass estimation of Thetford forest from L-band SAR data: potential and limitations , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[37]  D. Diner,et al.  Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere‐corrected MISR data , 1998 .

[38]  Pang-Ning Tan,et al.  Continental-scale comparisons of terrestrial carbon sinks estimated from satellite data and ecosystem modeling 1982–1998 , 2003 .

[39]  W. Cohen,et al.  Surface lidar remote sensing of basal area and biomass in deciduous forests of eastern Maryland, USA , 1999 .

[40]  David G. Victor,et al.  Increased Carbon Sink in Temperate and Boreal Forests , 2003 .

[41]  Masanobu Shimada,et al.  The ALOS Kyoto & Carbon Initiative , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[42]  I. C. Prentice,et al.  Carbon balance of the terrestrial biosphere in the Twentieth Century: Analyses of CO2, climate and land use effects with four process‐based ecosystem models , 2001 .

[43]  Christian Wirth,et al.  Seasonal and annual variations in the photosynthetic productivity and carbon balance of a central Siberian pine forest , 2002 .

[44]  R. Valentini,et al.  A new assessment of European forests carbon exchanges by eddy fluxes and artificial neural network spatialization , 2003 .

[45]  C. Field,et al.  Temporal evolution of the European forest sector carbon sink from 1950 to 1999 , 2003 .

[46]  M. Hofton,et al.  LAND SURFACE CHARACTERIZATION USING LIDAR REMOTE SENSING , 2001 .

[47]  I. C. Prentice,et al.  Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model , 2003 .

[48]  Ranga B. Myneni,et al.  Remote sensing estimates of boreal and temperate forest woody biomass: carbon pools, sources, and sinks , 2003 .

[49]  Pekka E. Kauppi,et al.  Biomass and Carbon Budget of European Forests, 1971 to 1990 , 1992, Science.

[50]  R. Dubayah,et al.  Sensitivity of large-footprint lidar to canopy structure and biomass in a neotropical rainforest , 2002 .

[51]  Philip Lewis,et al.  On the information content of multiple view angle (MVA) images , 1997 .

[52]  Changhui Peng,et al.  From static biogeographical model to dynamic global vegetation model: a global perspective on modelling vegetation dynamics , 2000 .

[53]  M. Hill,et al.  Spatial information for land use management , 2000 .

[54]  W. Wagner,et al.  Evaluation of the agreement between the first global remotely sensed soil moisture data with model and precipitation data , 2003 .

[55]  C. Schmullius,et al.  Quantification of full terrestrial biota major greenhouse gases budget at a regional scale: a combination of modeling systems, geographical information systems and remotely sensed data , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[56]  Konstantinos Papathanassiou,et al.  Single-baseline polarimetric SAR interferometry , 2001, IEEE Trans. Geosci. Remote. Sens..

[57]  Michel M. Verstraete,et al.  Potential and limitations of information extraction on the terrestrial biosphere from satellite remote sensing , 1996 .

[58]  Philip Lewis,et al.  On the potential of CHRIS/PROBA for estimating vegetation canopy properties from space , 2000 .

[59]  Thuy Le Toan,et al.  Dependence of radar backscatter on coniferous forest biomass , 1992, IEEE Trans. Geosci. Remote. Sens..

[60]  Christiane Schmullius,et al.  Large-scale mapping of boreal forest in Siberia , 2003 .

[61]  Pete Smith,et al.  Europe's Terrestrial Biosphere Absorbs 7 to 12% of European Anthropogenic CO2 Emissions , 2003, Science.

[62]  Christiane Schmullius,et al.  Multitemporal JERS repeat-pass coherence for growing-stock volume estimation of Siberian forest , 2003, IEEE Trans. Geosci. Remote. Sens..

[63]  Corinne Le Quéré,et al.  Regional changes in carbon dioxide fluxes of land and oceans since 1980. , 2000, Science.

[64]  A. Bondeau,et al.  Comparing global models of terrestrial net primary productivity (NPP): overview and key results , 1999 .