2020
Journal article  Closed Access

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

Giano S. I., Danese M., Gioia D., Pescatore E., Siervo V., Bentivenga M.

Geomorphology  Topographic Position Index (TPI)  DEMs  GIS software  Morphometry  Southern Italy 

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.

Source: Lecture notes in computer science 12250 LNCS (2020): 709–722. doi:10.1007/978-3-030-58802-1_51

Publisher: Springer, Berlin , Germania


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BibTeX entry
@article{oai:it.cnr:prodotti:438628,
	title = {Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)},
	author = {Giano S. I. and Danese M. and Gioia D. and Pescatore E. and Siervo V. and Bentivenga M.},
	publisher = {Springer, Berlin , Germania},
	doi = {10.1007/978-3-030-58802-1_51},
	year = {2020}
}