## 2 Forest biophysical Properties
### Above Ground Biomass  
A number of approaches have been used to estimate the spatial distribution of biomass in Amazonia, ranging from the development of allometric equations [25, 29, 30], local and large scale forest inventories [1, 28, 31, 32, 33, 34] to a methodology using only remote sensing or combined with field data [2, 35, 36, 37]. [PERSON] _et al._[38] compared several biomass estimates for the Brazilian Amazon, and found very low agreement across estimates. Differences in biomass estimates based on field measurements arise from differences in measurement methods in individual plots, extrapolation of the data from individual plots for the region, and the heterogeneity of the forests [38, 39]. Remote sensing-based estimates are usually restricted either to a small area of coverage with high spatial resolution (e.g., Landsat, IKONOS, Japanese Earth Resources Satellite (JERS) or airborne laser data ([40, 41] and others) or else to sensorswith a higher area of coverage, but with low spatial resolution [42] which implies a loss of accuracy to detect variations in forest physiognomy. Direct estimates of biomass based solely on optical or radar data derived from satellites present inconsistencies in forests with moderate and high biomass, and new technologies are being developed, such as the BIOMASS mission from the European Space Agency (ESA) [43]. Recent studies based entirely on field data [1] or on field data merged with a remote sensing dataset [2], suggest high biomass (300-400 Mg\(\cdot\)ha\({}^{-1}\)) in north-eastern Amazonia and central areas west of the Trombetas river to the west of the Rio Negro river, lower biomass (250-300 Mg\(\cdot\)ha\({}^{-1}\)) in the main channel of the Amazon River, Igapo and Varzea floodplains and between 200-300 Mg ha\({}^{-1}\) in western and southern Amazonia (Figure 1(a,b)). At a global scale, AGB has been recently estimated by using a combination of remote sensing and field data: the global forest height data measured by the Geoscience Laser Altimeter System (GLAS), onboard the Ice, Cloud, and land Elevation Satellite (ICESat), the moderate resolution imaging spectroradiometer (MODIS), the shuttle radar topography mission (SRTM), and quick scatterometer (QSCAT) [44]. The comparison of this global AGB with the map produced by [2] revealed in this new dataset lower biomass in the Rio Negro Basin, central region, and higher biomass in western Amazonia. Western Amazonia is a region that presents lower biomass then central regions [1, 23, 27, 45] and it could be speculated that the bamboo forests, present in this region, could have effects on Lidar measurements. Figure 1: Biomass and canopy height estimates for Amazonia. (**a**) Interpolations of biomass calculated by overlaying basal area estimate with maps of the structure and wood density function (Adapted from [1]); (**b**) 1 km spatial resolution map derived from combined remote sensing and field data through a decision tree method and regression analysis with 11 biomass classes and overall accuracy of 88% (Adapted from [2]); (**c**) 1 km spatial resolution canopy height data from [53], available online: [[http://lidarradar.jpl.nasa.gov](http://lidarradar.jpl.nasa.gov)]([http://lidarradar.jpl.nasa.gov](http://lidarradar.jpl.nasa.gov)). The use of RADAR for biomass estimation in dense canopy forests is still limited. At a local scale, Synthetic Aperture Radar (SAR) has been used to map and estimate biomass on different land covers. By analyzing SIR-C data in C- and L-bands in a region in central Brazilian Amazonia, [46] noted a visual discrimination of the main regenerating classes, indicating a potentiality for biomass estimation, although the analysis of the six bands separately produced no significant relationships between SAR backscatter and forest biomass.