The analysis of terraced heritage has implications in many different fields of study, as it is shaped itself by natural, socioeconomic, and cultural dynamics. Given that their abandonment impoverishes territories and communities and raises natural, especially hydrogeological hazards, and that their deactivation leads to a loss of cultural identity, this paper aims to study rapid mapping systems for their detection. Since a deep relation between high land division and the use of terraces for the exploitation of territories has been recognized, a first detection method is based on cadastral maps. The joint use of regional-scale digital elevation models (DEMs) and cadastral dataset polygons, based on a model that typically uses GIS analyses, identifies areas with a high probability of terracing. A second method is based on the use of new technologies for very high-scale data collection. The DEM models derived from UAV (unmanned aerial vehicle) photogrammetry, given their ability to determine the microtopographical characterization of the terrain as well as the most expensive on-site techniques, can be considered an excellent low-cost means by which to locate terraced heritage. The proposed work includes comparative testing between methods implying GIS-based analysis of slope models. It aims to highlight the effectiveness of using both methods: regional-scale DEMs and cadastral maps to detect a high probability of terrace localization, and DEMs derived from the use of low-altitude aerial data and structure from motion (SfM) algorithms, which have greatly and effectively increased the use of aerial drone photogrammetry
GIS-based detection of terraced landscape heritage: comparative tests using regional DEMs and UAV data / Spanò, Antonia; Sammartano, Giulia; Calcagno Tunin, Francesca; Cerise, Sylvie; Possi, Giulia. - In: APPLIED GEOMATICS. - ISSN 1866-9298. - STAMPA. - 10:2(2018), pp. 77-97.
|Titolo:||GIS-based detection of terraced landscape heritage: comparative tests using regional DEMs and UAV data|
|Data di pubblicazione:||2018|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1007/s12518-018-0205-7|
|Appare nelle tipologie:||1.1 Articolo in rivista|