Abstract:The inclusion of functional approaches on wetland characterizations and on biodiversity assessments improves our understanding of ecosystem functioning. In the Lower Paraná River floodplain, we assessed the ability of C-band polarimetric SAR data of contrasting incidence angles to discriminate wetland areas dominated by different plant functional types (PFTs). Unsupervised H/α and H/A/α Wishart classifications were implemented on two RADARSAT-2 images differing in their incidence angles (FQ24 and FQ08). Obtained classes were assigned to the information classes (open water, bare soil and PFTs) by a priori labeling criteria that involved the expected interaction mechanisms between SAR signal and PFTs as well as the relative values of H and α. The product obtained with the shallow incidence angle scene had a higher accuracy than the one obtained with the steep incidence angle product (61.5% vs. 46.2%). We show how a systematic analysis of the H/A/α space can be used to improve the knowledge about the radar polarimetric response of herbaceous vegetation. The map obtained provides novel ecologically relevant information about plant strategies dominating the floodplain. Since the obtained classes can be interpreted in terms of their functional features, the approach is a valuable tool for predicting vegetation response to floods, anthropic impacts and climate change.

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Unplanned urbanization increases the exposure of people to environmental hazards. Within a landscape ecology framework, this study is a diagnosis of human health risk in San Martín, an urban district of Buenos Aires, Argentina. Risk was estimated by combining four hazard indexes (water and air pollution, and mosquito and rodent infestation) and a vulnerability index. Each index was obtained by integrating environmental and socio-demographic layers in a Geographic Information System. Spatial autocorrelation was assessed for each hazard, vulnerability and risk indexes using Moran's tests. Also, spatial associations between pairs of variables were addressed by means of Geographically Weighted Regressions. The robustness of hazard and vulnerability indexes was checked by a sensitivity analysis. In General San Martín district, 83.3% of the population is exposed to relatively high levels of at least one hazard; 7.4% is exposed to relatively high levels of all hazards (11.5% of the total area) and only 16.7% lives in areas of relatively low levels of all hazards (15.4% of the total area). Areas where hazard intensity was relatively high corresponded to those areas where the most vulnerable population lives, enhancing human health risk. The models for hazards and vulnerability were reasonably robust to changes in the weights of the variables considered. Our results highlight the spatially heterogeneous nature of human health risk in an urban landscape, and reveal the location of critical risk hotspots where reduction or mitigation actions should be focused.

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