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Analysis of the Rockfall Phenomena Contributing to the Evolution of a Pocket Beach Area Using Traditional and Remotely Acquired Data (Lo Zingaro Nature Reserve, Southern Italy)
- Source :
- Remote Sensing, Volume 15, Issue 5, Pages: 1401
- Publication Year :
- 2023
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2023.
-
Abstract
- The coastal domain of central western Sicily is characterized by the presence of rocky coasts, which mainly consist of pocket beaches situated between bedrock headlands that constitute ecological niches of great touristic and economic value. In this peculiar morphodynamic system, the sedimentary contributions are mainly derived from the rockfall that affects the back of nearby cliffs or the sediment supply of small streams that flow into it. In this study, we investigated the geomorphological processes and related landforms that contribute to the evolution of a pocket beach area located in a coastal sector of NW Sicily Island. The cliffs in this are affected by several rockfalls, and deposits from these rockfalls also add to the rate of sedimentary contribution. The analysis was conducted through the application of traditional approaches and contemporary methods that have previously been used to forecast the collection of input data in the field, often under difficult conditions due to the accessibility of the sites, and which have been supported by UAV surveys. Through the analysis of the digital models of terrain and orthophotos, geometrical and multitemporal analyses of landforms were carried out. A dedicated software was utilized for the detection of rockfall runout zones and block trajectories and for defining the automatic extraction of rock mass discontinuities. The data were compared with those derived from traditional geomechanical surveys. The availability of the existing and acquired remote sensing data proved essential for this study for both defining the reference geological model and for performing the site-specific analysis of rockfall.
Details
- Language :
- English
- ISSN :
- 20724292
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....95599a973f6adc976f626af2a1ed7864
- Full Text :
- https://doi.org/10.3390/rs15051401