[1] The lack of global soil moisture data has spurred research in the field of microwave remote sensing. Both passive (radiometers) and active (scatterometer) microwave data are very sensitive to the moisture content of the surface soil layer. To retrieve soil moisture, the effects of vegetation, surface roughness, and heterogeneous land cover must be taken into account. Field experiments have shown that passive microwave data at long wavelengths (L-band) are best suited for soil moisture retrieval. Nevertheless, the first global, multiannual soil moisture data set (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000) has been derived from active microwave data acquired by the European Remote Sensing Satellites (ERS) ERS-1 and ERS-2 scatterometer (C-band). The retrieval algorithm is based on a change detection approach that naturally accounts for surface roughness and heterogeneous land cover. In this paper the scatterometer-derived soil moisture data are compared to gridded precipitation data and soil moisture modeled by a global vegetation and water balance model. The correlation between soil moisture and rainfall anomalies is observed to be best over areas with a dense rainfall gauge network. Also, the scatterometer-derived and modeled soil moisture agree reasonably well over tropical and temperate climates. The fact that the algorithm performs equally well for regions with summer rain and Mediterranean areas indicates that dynamic vegetation effects are correctly represented in the retrieval. More research is needed to better understand the backscattering behavior over dry (steppe, deserts) and cold (boreal zone, tundra) climatic regions. The scatterometerderived soil moisture data are available to other research groups at http:// www.ipf.tuwien.ac.at/radar/ers-scat/home.htm.

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Abstract:The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this

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This paper elaborates on recent advances in the use of ScanSAR technologies for wetland-related research. Applications of active satellite radar systems include the monitoring of inundation dynamics as well as time series analyses of surface soil wetness. For management purposes many wetlands, especially those in dry regions, need to be monitored for short and long-term changes. Another application of these technologies is monitoring the impact of climate change in permafrost transition zones where peatlands form one of the major land cover types. Therefore, examples from boreal and subtropical environments are presented using the analysed ENVISAT ASAR Global mode (GM, 1 km resolution) data acquired in 2005 and 2006. In the case of the ENVISAT ASAR instrument, data availability of the rather coarse Global Mode depends on request priorities of other competing modes, but acquisition frequency may still be on average fortnightly to monthly depending on latitude. Peatland types covering varying permafrost regimes of the West Siberian Lowlands can be distinguished from each other and other land cover by multi-temporal analyses. Up to 75% of oligotrophic bogs can be identified in the seasonal permafrost zone in both years. The high seasonal and inter-annual dynamics of the subtropic Okavango Delta can also be captured by GM time series. Response to increased precipitation in 2006 differs from flood propagation patterns. In addition, relative soil moisture maps may provide a valuable data source in order to account for external hydrological factors of such complex wetland ecosystems.

Permanent water bodies not oniy store dissolved CO2 but are essential for the maintenance of wetlands in their proximity. From the viewpoint of greenhouse gas (GHG) accounting wetland functions comprise sequestration of carbon under anaerobic conditions and methane release. The investigated area in central Siberia covers boreal and sub-arctic environments. Small inundated basins are abundant on the sub-arctic Taymir lowlands but also in parts of severe boreal climate v^fhere permafrost ice content is high and feature important freshwater ecosystems. Satellite radar imagery (ENVISAT ScanSAR), acquired in summer 2003 and 2004, has been used to derive open water surfaces v*/ith i50m resolution, covering an area of approximately 3Mkm^. The openwater surface maps were derived using a simple threshold-based classification method. The results were assessed with Russian forest inventory data, which includes detailed information about water bodies. The resulting classification has been further used to estimate the extent of tundra wetlands and to determine :heir importance for methane emissions. Tundra wetlands cover 7% (400 000 km^) of the study region and methane emissions from hydromorphic soils are estimated to be 45000td '' for the Taymir peninsula.

ABSTRACT1. Knowledge about the distribution and types of wetlands is in high demand by ecosystem modellers for full greenhouse gas accounting. The scope of this paper is to demonstrate the suitability of satellite radar data for the delineation of wetlands in the tundra and boreal forest biomes of central Siberia.2. An area of more than 3 million km 2 in central Siberia was investigated using satellite data. It covers freshwater ecosystems of the tundra and non-forested peatlands in tundra and boreal forest biomes. The satellite data represent the growing seasons of 2003/2004. 3. Microwave data were acquired by the Advanced Synthetic Aperture Radar (ASAR) instrument onboard ENVISAT. The multi-temporal capabilities and resolution (150 m  150 m in WS mode) of the ASAR wide swath mode enabled the detection of dynamic features >2 ha over this vast area. Scatterometer (QuikScat) data could be employed to distinguish hydro-periods.4. Wetland types have been identified on the basis of seasonal changes in backscatter. In a first step scatterometer data were used to identify the transition period from frozen to unfrozen conditions over a range of 158 latitude. Inundation patterns and soil moisture changes could be identified for the different hydro-periods and used to classify wetlands. Results for peatlands have been compared with Russian forest inventory data which contain information on wetland distribution.5. The database of permanently inundated areas is an intermediate product which enables the mapping of wetlands in two ways: (1) identification of seasonal inundation in relation to snowmelt and high permafrost tables and (2) input for density analysis of permanent small and shallow lakes in tundra areas which are important freshwater ecosystems as well as a methane source. Differences in intensity and duration of soil moisture conditions allow the identification of peatlands.