In the last 50 years the inhabitants of the 19 municipalities along the Abruzzo coast have doubled, and a stronger impact of the activities connected with the tourism has been experienced. The area, naturally exposed to the effects of changes of the sea level, has been interested by a dramatic increase of erosion, due to the reduction of the solid transport from rivers to the sea, as a consequence of extensive works carried out on the watersheds to mitigate extreme rainfall and consequent flooding. The availability of data acquired by different sensors on the last few decades might be useful to assess overall accretion/erosion trend of coastline, whereas combination of different observations taken in a restricted timeframe may provide interesting inputs for detailed studies (e.g. about the local impact of coastline protection works). In the present paper is proposed a methodology for the coastline identification from WorldView-2 images, available in 8 spectral bands, with 0.5 m of spatial resolution for panchromatic images and 1.8 m for the multispectral channels. In particular, a pixel based multispectral classification was used to identify various types of land cover. The 8 bands allow to get good results both in the classification process and with NDVI, NDWI, SAM, FM algorithms, for the identification of various land cover and in particular to separate dry sand from wet sand. Interesting results were obtained testing an algorithm that evaluates the relative depth of the water using the “coastal blue” band. Better results can surely be obtained by using elevation data (geoid models and digital terrain models) integrated with radiometric information. Very interesting is the comparison of the estimated coastline with such methodology and a topographic map of same area. This comparison highlights the changes in the study area. The possible applications of the proposed techniques are many, such as map updates, but also coastal change monitoring.
Coastline Detection Using High Resolution Multispectral Satellite Images
BRIGANTE, RAFFAELLA;RADICIONI, Fabio
2012
Abstract
In the last 50 years the inhabitants of the 19 municipalities along the Abruzzo coast have doubled, and a stronger impact of the activities connected with the tourism has been experienced. The area, naturally exposed to the effects of changes of the sea level, has been interested by a dramatic increase of erosion, due to the reduction of the solid transport from rivers to the sea, as a consequence of extensive works carried out on the watersheds to mitigate extreme rainfall and consequent flooding. The availability of data acquired by different sensors on the last few decades might be useful to assess overall accretion/erosion trend of coastline, whereas combination of different observations taken in a restricted timeframe may provide interesting inputs for detailed studies (e.g. about the local impact of coastline protection works). In the present paper is proposed a methodology for the coastline identification from WorldView-2 images, available in 8 spectral bands, with 0.5 m of spatial resolution for panchromatic images and 1.8 m for the multispectral channels. In particular, a pixel based multispectral classification was used to identify various types of land cover. The 8 bands allow to get good results both in the classification process and with NDVI, NDWI, SAM, FM algorithms, for the identification of various land cover and in particular to separate dry sand from wet sand. Interesting results were obtained testing an algorithm that evaluates the relative depth of the water using the “coastal blue” band. Better results can surely be obtained by using elevation data (geoid models and digital terrain models) integrated with radiometric information. Very interesting is the comparison of the estimated coastline with such methodology and a topographic map of same area. This comparison highlights the changes in the study area. The possible applications of the proposed techniques are many, such as map updates, but also coastal change monitoring.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
