The paper deals with evaluation and mapping of landslide hazard of an area located in the Archaeological Historic and Natural Park of the Rupestrian Churches in Matera. This park and old urban area of Matera town (“Sassi di Matera”) were recognized by the UNESCO World Heritage list since 1993. The studied site, named “Balvedere Chiese Rupestri” is to be found along the top of a deep canyon (“Gravina di Matera”) and contains many, valuable full hand-hewn, rupestrian churches. For its lithological, structural and geomorphological features, this area is affected by a widespread and by an intense slope instability, this phenomenas lead large and rapid falls, toppling and sliding of rock blocks. This geomorphological structure causes diffuse and significant structural-failures processes that involve most of the precious rock heritages. The evaluation and mapping of landslide susceptibility have been assessed using an artificial neural network (ANN), this system employing a back propagation-learning algorithm. This method requires the definition of appropriate thematic layers, that allow to parameterize the area under study. The parameters adopted in this study are: lithology, elevation, angle and aspect of the slope, hillshade, fracture density, kinematic hazard index of planar and wedge sliding and toppling. The results show that most of investigated area is characterized by a high landslide hazard.

Landslide Susceptibility in Archaeological and Natural Historic Park of Rupestrian Churches

PASCALE, STEFANIA;SDAO, Francesco;SOLE, Aurelia
2013-01-01

Abstract

The paper deals with evaluation and mapping of landslide hazard of an area located in the Archaeological Historic and Natural Park of the Rupestrian Churches in Matera. This park and old urban area of Matera town (“Sassi di Matera”) were recognized by the UNESCO World Heritage list since 1993. The studied site, named “Balvedere Chiese Rupestri” is to be found along the top of a deep canyon (“Gravina di Matera”) and contains many, valuable full hand-hewn, rupestrian churches. For its lithological, structural and geomorphological features, this area is affected by a widespread and by an intense slope instability, this phenomenas lead large and rapid falls, toppling and sliding of rock blocks. This geomorphological structure causes diffuse and significant structural-failures processes that involve most of the precious rock heritages. The evaluation and mapping of landslide susceptibility have been assessed using an artificial neural network (ANN), this system employing a back propagation-learning algorithm. This method requires the definition of appropriate thematic layers, that allow to parameterize the area under study. The parameters adopted in this study are: lithology, elevation, angle and aspect of the slope, hillshade, fracture density, kinematic hazard index of planar and wedge sliding and toppling. The results show that most of investigated area is characterized by a high landslide hazard.
2013
9783642313189
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/21590
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