The overall goal of this paper is to assess the potential of fully polarimetric SAR data for land-use mapping in the field of ecosystem monitoring. State of the art ecosystems' studies aim at integrating in-situ measurements acquired by smart sensor networks with Earth observation data analysis to ensure data quality services to multiple applications. The near real time observation using optical and SAR data contributes to evaluation of biodiversity threats in a very dynamic environment, Danube floodplain and inland delta. This paper addresses the need for consolidated approaches to extract biodiversity features from polarimetric SAR data. Two overlapping PolSAR images (L-band PALSAR and C-band RadarSAT 2) were classified in an unsupervised manner using the Entropy\AnisotropyΑ-Wishart algorithm in order to differentiate between various types of vegetation in the region of Braila Island, Romania, and then the results were assessed in a scientific manner, as a function of the acquisition sensors characteristics.