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This paper presents and assesses spatially explicit estimates of forest growing stock volume (GSV) of the northern hemisphere (north of 10 degrees N) from hyper-temporal observations of Envisat Advanced Synthetic Aperture Radar (ASAR) backscattered intensity using the BIOMASAR algorithm. Approximately 70,000 ASAR images at a pixel size of 0.01 degrees were used to estimate GV representative for the year 2010. The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest ( 30 m^3/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE betwen ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%).

Aboveground dry biomass was estimated for the 1.3 M km 2 forested area south of the treeline in the eastern Canadian province of Quebec by combining data from an airborne and spaceborne LiDAR, a Landsat ETM+ land cover map, a Shuttle Radar Topographic Mission (SRTM) digital elevation model, ground inventory plots, and vegetation zone maps. Plot-level biomass was calculated using allometric relationships between tree attributes and biomass. A small footprint portable laser profiler then flew over these inventory plots to develop a generic airborne LiDAR-based biomass equation ( R 2 = 0.65, n = 207). The same airborne LiDAR system flew along four portions of orbits of the ICESat Geoscience Laser Altimeter System (GLAS). A square-root transformed equation was developed to predict airborne profiling LiDAR estimates of aboveground dry biomass from GLAS waveform parameters combined with an SRTM slope index ( R 2 = 0.59, n = 1325). Using the 104,044 quality-filtered GLAS pulses obtained during autumn 2003 from 97 orbits over the study area, we then predicted aboveground dry biomass for the main vegetation areas of Quebec as well as for the entire Province south of the treeline. Including cover type covariances both within and between GLAS orbits increased standard errors of the estimates by two to five times at the vegetation zone level and as much as threefold at the provincial level. Aboveground biomass for the whole study area averaged 39.0 ± 2.2 (standard error) Mg ha − 1 and totalled 4.9 ± 0.3 Pg. Biomass distributions were 12.6% northern hardwoods, 12.6% northern mixedwood, 38.4% commercial boreal, 13% non-commercial boreal, 14.2% taiga, and 9.2% treed tundra. Non-commercial forests represented 36% of the estimated aboveground biomass, thus highlighting the importance of remote northern forests to C sequestration. This study has shown that space-based forest inventories of northern forests could be an efficient way of estimating the amount, distribution, and uncertainty of aboveground biomass and carbon stocks at large spatial scales.

We have developed and tested a method for mapping above-ground forest biomass of black spruce (Picea mariana (Mill.) B.S.P.) stands in northern boreal forests of eastern Canada. The method uses QuickBird images and applies image processing algorithms to extract tree shadow fraction (SF) as a predictive variable for estimating biomass. Three QuickBird images acquired over three test sites and 108 ground sample plots (GSP) were used to develop and test the method. SF was calculated from the fraction of tree shadow area over the area of a reference square overlaid on the images. Linear regressions between biomass of GSP and SF from the images for each test site resulted in R 2 in the range from 0.85 to 0.87 (except one case at 0.41), RMSE of 11 to 18 t/ha and bias of 2 to 5 t/ha. Statistical tests demonstrated that local regressions for the three test sites were not statistically significantly different. Consequently, a global regression was calculated with all GSP and produced R 2 , RMSE, and bias of 0.84, 14.2 t/ha and 4.2 t/ha, respectively. While generalization of these results to extended areas of the boreal forest would require further assessment, the SF method provided an efficient means for mapping biomass of black spruce stands for three test areas that are characteristic of the northern boreal forest of eastern Canada (boreal and taiga shield ecozones).

International audience; Space-borne Synthetic Aperture Radar (SAR) data and the plant architectural model AMAP are new tools, currently under development and validation, for the retrieval and mapping of forest parameters through a Geographical Information System (GIS). On one hand, L-band SAR data are useful for the retrieval of some forest attributes such as age and woody volume. On the other hand, validated growth model of tree architecture allows retrieval of many forest parameters at tree level and simulation of virtual 3-D views both at the tree and stand levels. To this aim, a methodology is proposed using L-HV SIR-C SAR data or AMAP alone or their coupling through a GIS for forest attributes retrieval and 3-D stand simulation. This approach is illustrated on a simple forest ecosystem, an Austrian pine forest over hilly terrain in southern of France. Results show the potentialities and interests in using such tools when retrieval bole volume is limited to 300 m3/ha; AMAP allowed estimation according to tree (compartment) partitioning as a function of growth stage. The coupling approach gives realistic 3-D stand visualization when it is exercised with GIS data sets and error sources are pointed out toward future improvement and generalization.

A microwave polarimetric scattering model for a forest canopy is developed based on the iterative solution of the vector radiative transfer equations up to the second order. The forest canopy constituents (branches, leaves, stems, and trunks) are embedded in a multi-layered medium over a rough interface. The branches, stems, and trunks are modeled as finite randomly oriented cylinders. Deciduous leaves are modeled as randomly oriented discs and coniferous leaves are modeled as randomly oriented needles. The vector radiative transfer equations contain non-diagonal extinction matrices that account for the difference in propagation constants and the attenuation rates between the vertical and horizontal polarizations. For a plane wave exciting the canopy, the average Mueller matrix is formulated, and then used to determine the linearly polarized backscattering coefficients including both the copolarized and cross-polarized power returns. Comparisons of the model with measurements from Les Landes Forest of France showed good agreements over a wide frequency band and gave a quantitative understanding of the relation between the backscattering coefficients and the age of the trees in the forest and forest biomass.