Focusing on woody vegetation in Queensland, Australia, the study aimed to establish whether the relationship between Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) HH and HV backscattering coefficients and above ground biomass (AGB) was consistent within and between structural formations (forests, woodlands and open woodlands, including scrub). Across these formations, 2781 plot-based measurements (from 1139 sites) of tree diameters by species were collated, from which AGB was estimated using generic allometric equations. For Queensland, PALSAR fine beam dual (FBD) 50 m strip data for 2007 were provided through the Japanese Space Exploration Agency's (JAXA) Kyoto and Carbon (K&C) Initiative, with up to 3 acquisitions available for each Reference System for Planning (RSP) paths. When individual strips acquired over Queensland were combined, `banding' was evident within the resulting mosaics, with this attributed to enhanced L-band backscatter following rainfall events in some areas. Reference to Advanced Microwave Scanning Radiometer-EOS (AMSR-E) data indicated that strips with enhanced L-band backscatter corresponded to areas with increased effective vegetation water content (kg m ^-2 ) and, to a lesser extent, soil moisture (g cm ^-3 ). Regardless of moisture conditions, L-band HV topographically normalized backscattering intensities backscatter (σ _f ^o ) increased asymptotically with AGB, with the saturation level being greatest for forests and least for open woodlands. However, under conditions of relative maximum surface moisture, L-band HV and HH σ _f ^o was enhanced by as much as 2.5 and 4.0 dB respectively, particularly for forests of lower AGB, with this resulting in an overall reduction in dynamic range. The saturation level also reduced at L-band HH for forests and woodlands but remained similar for open woodlands. Differences in the rate of increase in both L-band HH and HV σ _f ^o with AGB were observed between forests and the woodland categories (for both relatively wet and dry conditions) with these attributed, in part, to differences in the size class distribution and stem density between non-remnant (secondary) forests and remnant woodlands of lower AGB. The study concludes that PALSAR data acquired when surface moisture and rainfall are minimal allow better estimation of the AGB of woody vegetation and that retrieval algorithms ideally need to consider differences in surface moisture conditions and vegetation structure.

The magnitude of the global terrestrial carbon pool and related fluxes to and from the atmosphere are still poorly known. The European Space Agency P-band radar BIOMASS mission will help to reduce this uncertainty by providing unprecedented information on the distribution of forest above-ground biomass (AGB), particularly in the tropicswhere the gaps are greatest and knowledge ismost needed.Mission selection wasmade in full knowledge of coverage restrictions over Europe, North and Central America imposed by the US Department of Defense Space Objects Tracking Radar (SOTR) stations. Under these restrictions, only 3% of AGB carbon stock coverage is lost in the tropical forest biome,with this biome representing 66% of global AGB carbon stocks in 2005. The loss is more significant in the temperate (72%), boreal (37%) and subtropical (29%) biomes, with these accounting for approximately 12%, 15% and 7%, respectively, of the global forest AGB carbon stocks. In terms of global carbon cycle modelling, there is minimal impact in areas of high AGB density, since mainly lower biomass forests in cooler climates are affected. In addition, most areas affected by the SOTR stations are located in industrialized countries with well-developed national forest inventories, so that extensive information on AGB is already available. Hence the main scientific objectives of the BIOMASS mission are not seriously compromised. Furthermore, several space sensors that can estimate AGB in lower biomass forests are in orbit or planned for launch between now and the launch of BIOMASS in 2021, which will help to fill the gaps in mission coverage

Fire frequency in 21 forest planning regions of Portugal during the period 1975–2005 was estimated from historical burnt area maps generated with semi-automatic classification of Landsat Thematic Mapper (TM) satellite imagery. Fire return interval distributions were modelled with the Weibull function and the estimated parameters were used to calculate regional mean, median and modal fire return intervals, as well as regional hazard functions. Arrangement of the available data into three different time series allowed for assessment of the effects of minimum mapping unit, time series length and use of censored data on the Weibull function parameter estimates. Varying the minimum mapping unit between 5 and 35 ha had a negligible effect on parameter estimates, whereas changing the time series length from 22 to 31 years substantially affected the estimates. However, the strongest effect was caused by censored data. Its exclusion led to substantial overestimation of fire frequency and of burning probability dependence on fuel age. We estimated a country-wide mean fire interval of 36 years and an annual burnt area of 1.2%. Regional variations in fire frequency descriptors were interpreted in terms of land cover and land use practices that affect the contemporary fire regime in Portugal.