Shoreline mapping and change detection are critical for Integrated Coastal Zone Management (ICZM) and all that it represents. This research utilized previous studies that combined both Remote Sensing and Geographical Information System (GIS) techniques to assess, map and forecast shoreline evolution from short-term perspectives. The study area is located in the central region of Portugal, between the counties of Ovar and Marinha Grande (circa 140 km) and the time period assessed was from 1984 to 2011. Historical data were used to calculate advance and retreat rates in order to support environmental scenarios for the Portuguese Central Region’s Coastal Management Plan. To ensure accuracy, a repeatable procedure was validated using Landsat TM and ETM+ satellite images, which were subsequently enhanced and elaborated by Remote Sensing analyses to detect and extract shorelines. They were subsequently integrated within an Esri ArcGIS software application (DSAS - Digital Shoreline Analysis System) to determine and predict rates of coastline change. Graphical DSAS plots identified coastline phases and shifts and were used to simulate the 2022 coastline scenario. These results will be integrated into the Coastal Zone Management Plan (Horizon – 2022). Importantly this methodological planning approach provides visual coastline change information for regional decision-makers and stakeholders.

Cenci, L., Disperati, L., Sousa, L.P., Phillips, M., Alves, F.L. (2013). Geomatics for Integrated Coastal Zone Management: multitemporal shoreline analysis and future regional perspective for the Portuguese Central Region. JOURNAL OF COASTAL RESEARCH, 65(2), 1349-1354 [10.2112/SI65-228.1].

Geomatics for Integrated Coastal Zone Management: multitemporal shoreline analysis and future regional perspective for the Portuguese Central Region

CENCI, LUCA
Writing – Original Draft Preparation
;
DISPERATI, LEONARDO
Writing – Review & Editing
;
2013-01-01

Abstract

Shoreline mapping and change detection are critical for Integrated Coastal Zone Management (ICZM) and all that it represents. This research utilized previous studies that combined both Remote Sensing and Geographical Information System (GIS) techniques to assess, map and forecast shoreline evolution from short-term perspectives. The study area is located in the central region of Portugal, between the counties of Ovar and Marinha Grande (circa 140 km) and the time period assessed was from 1984 to 2011. Historical data were used to calculate advance and retreat rates in order to support environmental scenarios for the Portuguese Central Region’s Coastal Management Plan. To ensure accuracy, a repeatable procedure was validated using Landsat TM and ETM+ satellite images, which were subsequently enhanced and elaborated by Remote Sensing analyses to detect and extract shorelines. They were subsequently integrated within an Esri ArcGIS software application (DSAS - Digital Shoreline Analysis System) to determine and predict rates of coastline change. Graphical DSAS plots identified coastline phases and shifts and were used to simulate the 2022 coastline scenario. These results will be integrated into the Coastal Zone Management Plan (Horizon – 2022). Importantly this methodological planning approach provides visual coastline change information for regional decision-makers and stakeholders.
2013
Cenci, L., Disperati, L., Sousa, L.P., Phillips, M., Alves, F.L. (2013). Geomatics for Integrated Coastal Zone Management: multitemporal shoreline analysis and future regional perspective for the Portuguese Central Region. JOURNAL OF COASTAL RESEARCH, 65(2), 1349-1354 [10.2112/SI65-228.1].
File in questo prodotto:
File Dimensione Formato  
Cenci_et_al_2013_Paper3848_rev.pdf

non disponibili

Descrizione: Articolo principale
Tipologia: PDF editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 612.82 kB
Formato Adobe PDF
612.82 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/973631