Extraction of Cabedelo sand spit area (Douro estuary) from satellite images through image processing techniques

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Teodoro, AC (Author) FCUP; Pais Barbosa, J (Author) FEUP; Goncalves, H (Author) FCUP; Veloso Gomes, F (Author) FEUP; Taveira Pinto, F (Author) FEUP

Journal

Title: Journal of Coastal Research

No. SI 39

Pages: 1740-1744

ISSN: 0749-0208

Publisher: Coastal Education & Research Foundation, Inc.

Indexing

ISI Web of Knowledge - 10 Citations

ISI Web of Science

Scopus - 10 Citations

Scientific classification

FOS: Natural sciences > Earth and related Environmental sciences

Other information

Authenticus ID: P-002-WFE

Abstract (EN): Teodoro et al., 2011. Extraction of a sand spit (Cabedelo - Douro estuary) from IKONOS-2 satellite images through image processing techniques. Journal of Coastal Research, SI 64 (Proceedings of the 11th International Coastal Symposium), 1740 - 1744. Szczecin, Poland, ISSN 0749-0208 The Cabedelo sand spit, located at the Douro river mouth estuary in Porto, Portugal, is a very dynamic morphologic system. Until now, the Cabedelo sand spit had been monitored using several Differential Global Positioning System field surveys. However, this monitoring program involves in situ collection data and several associated post-processing procedures. The main objective of this work was to explore and establish an effective and accurate methodology, able to extract the Cabedelo area from IKONOS-2 data through image processing techniques. The extraction of the shape of this estuarine body is mainly based on the concept of identifying the boundaries between sea/river and the Cabedelo sand spit body, allowing for a further characterization of the Cabedelo morphology. Three different image processing techniques were employed: pixel-based classification algorithms; object-oriented classification algorithms; and a segmentation approach consisting on histogram thresholding through the Otsu method. These methods were applied to six IKONOS-2 images (visible and near-infra-red bands), between 2001 and 2007. The results of the pixel-based and object-based classification procedures were very similar. However, the results regarding the application of the maximum likelihood classifier were slightly better. The segmentation approach for the extraction of the sand spit, presented a slightly better performance than the pixel-based and object-based classification approaches. Moreover, it presents the advantage of being a fast procedure and with a high potential for a fully automation. This research allows for obtaining data in a simple way, currently nonexistent for the Cabedelo sand spit and offered an effective and accurate methodology for monitoring the sand spit morphology.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 5