Raffaella Brigante

Automatic three-dimensional features extraction: The case study of L'Aquila for collapse identification after April 06, 2009 earthquake

Abstract This paper illustrates an innovative methodology for post-earthquake collapsed building recognition, based on satellite-image classification methodologies and height variation information. Together, the techniques create a robust classification that seems to yield good results in this application field. In the first part of this study, two different feature extraction methodologies were compared, based respectively on pixel-based and object-oriented approaches. Then the classification results of the most accurate classification methodology. obtained on an eight band WorldView-2 monoscopic image, were completed with height variation information before and after the event. The height difference is calculated, comparing a photogrammetric DSM, obtained using a photogrammetric rigorous orbital model on some EROS-B 0.7 metre across-track stereopairs with a ‘roof model’ before the earthquake.

Use of aerial multispectral images for spatial analysis of flooded riverbed-alluvial plain systems: the case study of the Paglia River (central Italy)

ABSTRACT Image processing and classification techniques are widely used for land use definition. They can also provide interesting applications in fluvial geomorphology, for outlining morpho-sedimentary features (bars, channels, banks and floodplain) at various temporal stages, in order to monitor the evolution of river systems. Frequent monitoring is especially important for streams, in terms of flood risk in urban areas. This study shows how techniques of supervised analysis can be applied to river systems, also under particular conditions, like after flood events (when large portions of riverbed and alluvial plain are covered with mud). The procedure starts from the classical photogrammetric techniques, based on multispectral classification, and goes on with post processing operations of pixel aggregation and shadow treatment. The classification also uses the elevation information provided by Digital Surface Model produced by photogrammetry. This paper introduces a new technique of remote sensing in fluvial areas that allows for both the identification and classification of the fluvial features in a post flooding condition. Application of the procedure over time permits the evolution of the fluvial dynamics to be monitored in an accurate and inexpensive way, particularly for flood event conditions which lead to major changes in the dynamics of riverbeds.