Provide a New Computational Module for Digital Shoreline Analysis System to Detect Uncertain Data in the Shoreline Change Data

• Main Authors: kumars Mahmoodi, Mesbah Saybani, Abbas moradi
• Format: Article
• Language: fas
• Published: Iranian Association of Naval Architecture and Marine Engineering 2015-09-01
• Series: نشریه مهندسی دریا
• Subjects: souza; shoreline changes; digital shoreline analysis system (dsas); error data; statistical methods.
• Online Access: http://marine-eng.ir/article-1-358-en.html

Digital Shoreline Analysis System (DSAS) is the most widely used tool by researchers and experts to shoreline change rate measurements. Several factors may cause uncertain data in the measured values by this tool. Understanding these errors and fix them if possible, improve the accuracy of the results. The DSAS does not have this capability. The purpose of this paper is to present a new computational module for DSAS to identify suspected data errors. This module is an executable file that is written using MATLAB software and communicate through XML files with DSAS. Suspected data error detection is performed using statistical methods include: Box plot, Hampel’s test, Median Absolute Deviation (MAD) and Z-score test. The results show the good performance of this module to identify possible errors in data.