SIGNALS AND NOISES OF REGRESSIONAL AND NON-REGRESSIONAL SHORELINE CHANGE RATE METHODOLOGIES

7th International Scientific Conference - SGEM2007, www.sgem.org, SGEM2007 Conference Proceedings/ ISBN: 954-918181-2, June 11-15, 2007

ABSTRACT

Shoreline change rate is the most critical feature of the coastal area because
it reveals future harmful impacts driven by long-term climate changes and
episodic events. Since the coastal zone is one of a nation’s greatest environmental
and economic assets, the best methodology, as far as accuracy is concerned,
estimating the rate of change of a shoreline is an open question. The accuracy
both of the geoinformation used and the computed change rate is of crucial
importance. The purpose of the present paper is to use historical shorelines
extracted from three different Greek coastal regions and estimate their shoreline
change rate.(signal). The most common and traditional statistical methods are
used, i.e. end of point rate, average of rates, linear regression and Jackknife.
The first two are the non-regressional and the last two the regressional
methodologies. The error in position (EIP) of each methodology indicates its
accuracy (noise). Since the true shoreline change rate of each coastal region is
not known, it is impossible to assess which method is the most accurate unless
the EIP is compared to the its signal. It is proved that the Jackknife method
is the most accurate to use for shoreline evolution estimations. To evaluate
further the derived conclusion, we introduce computer-derived (“synthetic”)
shorelines and compute the signal-to-noise ratio for this ideal and errorless
case. The results strengthen the main conclusion regarding the Jackknife ability
to compute shoreline change rate with the best accuracy.