The precise delineation of coastal areas subject to past, present, and future erosive processes plays a fundamental role in coastal risk management. Within this framework, satellite data represent a valuable synoptic and multi-temporal information source. Therefore, this research integrated remote sensing and GIS techniques for mapping and modeling shoreline evolution through time. Long-term shoreline's proxy rates of advance and retreat were determined using Landsat data from the mid-1980s to 2011 and subsequently, a short-term scenario (3 years) was predicted and validated. Two different coastal environments, Oceanic and Mediterranean, were investigated. In the first, different proxies were analyzed, thereby enabling a multi-proxy analysis. Findings showed that the method provided more accurate results in higher energy environments (Oceanic) and where the coastline is not urbanized. Results also highlighted the importance of performing multi-proxy analyses in given study areas, to more reliably define shoreline modeling. Importantly, during the analyses, particular attention was given to assessing uncertainty, which is crucial when outcomes of scientific research are considered for management.

Cenci, L., Disperati, L., Persichillo, M.G., Oliveira, E.R., Alves, F.L., & Phillips, M. (2018). Integrating remote sensing and GIS techniques for monitoring and modeling shoreline evolution to support coastal risk management. GISCIENCE & REMOTE SENSING, 55(3), 355-375 [10.1080/15481603.2017.1376370].

Integrating remote sensing and GIS techniques for monitoring and modeling shoreline evolution to support coastal risk management

Cenci, Luca
Writing – Original Draft Preparation
;
Disperati, Leonardo
Writing – Review & Editing
;
2018

Abstract

The precise delineation of coastal areas subject to past, present, and future erosive processes plays a fundamental role in coastal risk management. Within this framework, satellite data represent a valuable synoptic and multi-temporal information source. Therefore, this research integrated remote sensing and GIS techniques for mapping and modeling shoreline evolution through time. Long-term shoreline's proxy rates of advance and retreat were determined using Landsat data from the mid-1980s to 2011 and subsequently, a short-term scenario (3 years) was predicted and validated. Two different coastal environments, Oceanic and Mediterranean, were investigated. In the first, different proxies were analyzed, thereby enabling a multi-proxy analysis. Findings showed that the method provided more accurate results in higher energy environments (Oceanic) and where the coastline is not urbanized. Results also highlighted the importance of performing multi-proxy analyses in given study areas, to more reliably define shoreline modeling. Importantly, during the analyses, particular attention was given to assessing uncertainty, which is crucial when outcomes of scientific research are considered for management.
Cenci, L., Disperati, L., Persichillo, M.G., Oliveira, E.R., Alves, F.L., & Phillips, M. (2018). Integrating remote sensing and GIS techniques for monitoring and modeling shoreline evolution to support coastal risk management. GISCIENCE & REMOTE SENSING, 55(3), 355-375 [10.1080/15481603.2017.1376370].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11365/1039985