Shoreline variability via empirical orthogonal function analysis: Part I temporal and spatial characteristics [An article from: Coastal Engineering] Buy on Amazon

https://www.ebooknetworking.net/books_detail-B000PC0JMW.html

Shoreline variability via empirical orthogonal function analysis: Part I temporal and spatial characteristics [An article from: Coastal Engineering]

10.95 USD
Buy New on Amazon 🇺🇸

Available for download now

Book Details

PublisherElsevier
ISBN / ASINB000PC0JMW
ISBN-13978B000PC0JM2
AvailabilityAvailable for download now
Sales Rank99,999,999
MarketplaceUnited States  🇺🇸

Description

This digital document is a journal article from Coastal Engineering, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Empirical orthogonal functions (EOFs) or principal components were used to extract the significant modes of shoreline variability from several data sets collected at three very different locations. Although EOFs have proven to be a valuable tool in the analysis of nearshore data, most applications have focused on the ability of the technique to describe cross-shore or profile variability. Here however, EOFs were used to help identify the dominant modes of longshore shoreline variability at Duck, North Carolina, the Gold Coast, Australia, and at several locations within the Columbia River Littoral Cell in the U.S. Pacific Northwest. In part one of this analysis, characteristic patterns of shoreline variability identified by the EOF analysis are described in detail. At each site, the dominant modes consisting of the first four eigenfunctions were found to describe nearly 95% of the total shoreline variability. At both Duck and the Gold Coast, several interesting longshore periodic features suggestive of sand waves were identified, while boundary effects related to natural headlands and navigational structures/entrances dominated the Pacific Northwest data sets.
Donate to EbookNetworking
Prev
Next