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Biomass estimation of wetlands plays a role in understanding dynamic changes of the wetland ecosystem. Poyang Lake is the largest freshwater lake in China, with an area of about 3000     km 2 . The lake’s wetland ecosystem has a significant impact on leveraging China’s environmental change. Synthetic aperture radar (SAR) data are a good choice for biomass estimation during rainy and dry seasons in this region. In this paper, we discuss the neural network algorithms (NNAs) to retrieve wetland biomass using the alternating-polarization ENVISAT advanced synthetic aperture radar (ASAR) data. Two field measurements were carried out coinciding with the satellite overpasses through the hydrological cycle in April to November. A radiative transfer model of forest canopy, the Michigan Microwave Canopy Scattering (MIMICS) model, was modified to fit to herbaceous wetland ecosystems. With both ASAR and MIMICS simulations as input data, the NNA-estimated biomass was validated with ground-measured data. This study indicates the capability of NNA combined with a modified MIMICS model to retrieve wetland biomass from SAR imagery. Finally, the overall biomass of Poyang Lake wetland vegetation has been estimated. It reached a level of 1.09 × 10 9 , 1.86 × 10 8 , and 9.87 × 10 8     kg in April, July, and November 2007, respectively.

Biomass estimation of wetland vegetation in Poyang Lake area using ENVISAT advanced synthetic aperture radar data