Geomorphic evidence of Quaternary tectonics within an underlap fault zone of southern Apennines, Italy

Giano, Salvatore Ivo; Pescatore, Eva; Agosta, Fabrizio; Prosser, Giacomo

doi:10.1016/j.geomorph.2017.11.020

Cited by 26 publications

(10 citation statements)

References 73 publications

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“…A complex geomorphic analysis may include computation of indices such as mountain front of water divide sinuosity, asymmetry, drainage basin elongation, relief ratio, hypsometry, normalized steepness, and concavity, integrated with geomorphological analysis (Giano et al, 2018). This study presents the most important geomorphic features that are often included in geographic education curriculum and also embedded in R algorithms: computation and mapping of slope steepness, aspect orientation, visualization hillshade and DEM elevation.…”

Section: Calculate Terrain Characteristics: Slope and Aspectmentioning

confidence: 99%

Using R packages 'tmap', 'raster' and 'ggmap' for cartographic visualization: An example of dem-based terrain modelling of Italy, Apennine Peninsula

Lemenkova¹

2020

Zb PMF Geog inst Beograd

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The main purpose of this article is to present the use of R programming language in cartographic visualization demonstrating using machine learning methods in geographic education. Current trends in education technologies are largely influenced by the possibilities of distance-learning, e-learning and selflearning. In view of this, the main tendencies in modern geographic education include active use of open source GIS and publicly available free geospatial datasets that can be used by students for cartographic exercises, data visualization and mapping, both at intermediate and advanced levels. This paper contributes to the development of these methods and is fully based on the datasets and tools available for every student: the R programming language and the free open source datasets. The case study demonstrated in this paper show the examples of both physical geographic mapping (geomorphology) and socio-economic geography (regional mapping) which can be used in the classes and in self-learning. The objective of this research includes geomorphological modelling of the terrain relief in Italy and regional mapping. The data include dem SRTM90 and datasets on regional borders of Italy embedded in R packages 'maps' and 'mapdata'. Modelling references to the characteristics of slope, aspect, hillshade and elevation, their visualization using R packages: 'raster' and 'tmap'. Regional mapping of Italy was made using main package 'ggmap' with the 'ggplot2' as a wrapper. The results present five thematic maps (slope, aspect, hillshade, elevation and regions of Italy) created in R language. Traditionally used in statistical analysis, R is less known as a perfect tool in geographic education. This paper contributes to the development of methods in geographic education by presenting new technologies of the machine learning methods of mapping.

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Section: Calculate Terrain Characteristics: Slope and Aspectmentioning

confidence: 99%

Using R packages 'tmap', 'raster' and 'ggmap' for cartographic visualization: An example of dem-based terrain modelling of Italy, Apennine Peninsula

Lemenkova¹

2020

Zb PMF Geog inst Beograd

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“…The average direction of the chain axis is approximately N150°, corresponding to the strike of both the main thrusts and younger coaxial normal faults. Extensional tectonics is still active along the axis of the chain deforming Pleistocene sediments [17][18][19][20][21][22]. Such a complex structural setting produced a mountain chain over 2000 m high and a regional divide oriented NW-SE that separates the drainage network towards south-west in the Tyrrhenian Sea, northeast in the Adriatic Sea, and east in the Ionian Sea.…”

Section: Geology and Geomorphology Of The Study Areamentioning

confidence: 99%

Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)

Giano

Danese²,

Gioia³

et al. 2020

Lecture Notes in Computer Science

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Recent advances in spatial methods of digital elevation model (DEMs) analysis have addressed many research topics on the assessment of morphometric parameters of the landscape. Development of computer algorithms for calculating the geomorphometric properties of the Earth's surface has allowed for expanding of some methods in the semi-automatic recognition and classification of landscape features. In such a way, several papers have been produced, documenting the applicability of the landform classification based on map algebra. The Topographic Position Index (TPI) is one of the most widely used parameters for semi-automated landform classification using GIS software. The aim was to apply the TPI classes for landform classification in the Basilicata Region (Southern Italy). The Basilicata Region is characterized by an extremely heterogeneous landscape and geological features. The automated landform extraction, starting from two different resolution DEMs at 20 and 5 m-grids, has been carried out by using three different GIS software: Arcview, Arcmap, and SAGA. Comparison of the landform maps resulting from each software at a different scale has been realized, furnishing at the end the best landform map and consequently a discussion over which is the best software implementation of the TPI method.

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“…The most recent shortening occurred on the front range of the chain deforming the Pleistocene sediments and volcanics [29,31,32]. Moreover, extensional tectonics displacing the orogeny is still active along the axis of the Apennines chain [26][27][28][29][30][31][32][33][34][35][36][37][38][39]. The average direction of the chain axis is approximately N150 • , which corresponds to the strike of both the main thrusts and the coaxial normal faults.…”

Section: Regional Geology and Geomorphologymentioning

confidence: 99%

“…Many mountain tops of the axial belt correspond to the remnants of Pliocene-Pleistocene erosional land surfaces uplifted and dismembered by Quaternary faults [28]. The landscape of the axial zone includes block-faulted ridges and massifs, bounded by high-angle fault scarps retreated by slope-replacement processes [44] and displaced by active faults [38]. The intermontane basins filled with Pliocene-Quaternary fluvial and lacustrine deposits [36,45] are also present.…”

Section: Regional Geology and Geomorphologymentioning

confidence: 99%

Development of Pleistocene Fluvial Terraces on the Eastern Frontal Sector of the Southern Apennines Chain, Italy

Giannandrea

Giano

Sulpizio

2019

Water

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The investigation of Pleistocene fluvial terraces in the small river valley of the Pescogrosso Stream and surrounding areas has shown a complex and positive location for the study of a fluvial catchment development. The Pescogrosso Stream is a left tributary of the Sinni River and is placed on the eastern front of the fold-and-thrust belt of the southern Apennine chain of Italy. Sedimentological and geomorphological analyses of eight fluvial terraced units revealed that their formation and evolution were strictly controlled by regional tectonic uplift of the Ionian arc, by climatic changes, and by sea-level variations. In particular, the Ionian sea-level oscillations, as a factor in controlling the short-term fluvial terrace development, was the main factor responsible for the three older terraces’ evolutions. Conversely, the evolution of the five younger terraces seems to have been controlled by the base-level variations of the Sinni River. Finally, the matching of much information derived from regional and local tectonics, the plot of longitudinal terrace profiles, and the application of a sequence-stratigraphic approach to fluvial depositional sequences allowed the recognition of three evolutionary stages of development in the Pescogrosso fluvial incised-valley system during Pleistocene times.

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Geomorphic evidence of Quaternary tectonics within an underlap fault zone of southern Apennines, Italy

Cited by 26 publications

References 73 publications

Using R packages 'tmap', 'raster' and 'ggmap' for cartographic visualization: An example of dem-based terrain modelling of Italy, Apennine Peninsula

Using R packages 'tmap', 'raster' and 'ggmap' for cartographic visualization: An example of dem-based terrain modelling of Italy, Apennine Peninsula

Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)

Development of Pleistocene Fluvial Terraces on the Eastern Frontal Sector of the Southern Apennines Chain, Italy

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