A GIS-based geostatistical approach for palaeo-environmental reconstructions of coastal areas: the case of the Cilento promontory (southern Italy)

被引:0
作者
Sorrentino, Alessia [1 ]
Maratea, Antonio [1 ]
Mattei, Gaia [1 ]
Pappone, Gerardo [1 ]
Tursi, Maria Francesca [1 ]
Aucelli, Pietro P. C. [1 ]
机构
[1] Univ Napoli Parthenope, Sci & Technol Dept, Naples, Italy
来源
2023 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR THE SEA; LEARNING TO MEASURE SEA HEALTH PARAMETERS, METROSEA | 2023年
关键词
semi-automated landform classification; geostatistical analysis; palaeo-environmental coastal reconstruction; sea level proxy; palaeo-shoreline detection; RELATIVE SEA-LEVEL;
D O I
10.1109/MetroSea58055.2023.10317359
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
This research proposes a new geostatistical approach for the GIS-aided reconstruction of environmental changes related to sea-level oscillations, applied to the Cilento coastal sector between the mouth of Solofrone River and Ogliastro Marina, located along the Tyrrhenian coast of Southern Italy. As the area can be considered tectonically stable since the Late-Pleistocene, it is ideally suitable to test palaeo-environmental reconstruction methodologies. The proposed procedure is based on the creation of a geodatabase for managing sea level data and related palaeo-environmental indicators derived from bibliographic sources and new in situ surveys. These data were loaded into a GIS in order to obtain a credible geomorphological and geoarchaeological reconstruction of the target area during the late Pleistocene through spatial analysis. We reinterpreted all the sea-level markers (SLMs) to evaluate the palaeo-shoreline position, starting from sea-level index points (SLIPs) which were considered anchor points. In the absence of SLPs, palaeo-ecological data were interpreted as additional variables to assess the possible location of the shoreline and its related uncertainty. Then we confronted our data with the results deriving from the Topographic Index Position (TPI) analysis plotting them together in ArcMap. By the inte, we understood if there were any relevant sea-level stands at the time the indicators were formed. This all-encompassing methodology allowed us to obtain multiple scenarios at various time scales for the Cilento coasts over the last millennia.
引用
收藏
页码:488 / 493
页数:6
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