Automatic Shoreline Detection and Change Detection Analysis of Netravati-GurpurRivermouth Using Histogram Equalization and Adaptive Thresholding Techniques

Abstract

The shoreline change extraction and change detection analysis is an important task that has application in different fields such as development of setback planning, hazard zoning, erosion-accretion studies, regional sediment budgets and conceptual or predictive modeling of coastal morphodynamics. Shoreline delineation is difficult, time consuming, and sometimes impossible for entire coastal system when using traditional ground survey techniques. Recent advances in remote sensing and geographical information system (GIS) techniques are overcoming the difficulties in extraction of shoreline position and detection of shoreline changes. In the present paper, an automatic shoreline detection method using histogram equalization and adaptive thresholding techniques is developed. The shoreline of Netravati-Gurpur rivermouth area along Mangalore coast, West Coast of India have been extracted from Indian Remote Sensing Satellite (IRS P6) LISS-III (2005, 2007 and 2010) and IRS R2 LISS-III (2013) satellite images using developed automatic shoreline detection method. The delineated shorelines have been analyzed using Digital Shoreline Analysis System (DSAS), a GIS Software tool for estimation of shoreline change rates through two statistical techniques such as, End Point Rate (EPR) and Linear Regression Rate (LRR). The Bengre spit, Northern sector of Netravati-Gurpur river mouth is under accretion an average of 2.95 m/yr (EPR) and 3.07 m/yr (LRR) and maximum accretion obtained is 8.51 m/yr (EPR) and 8.69 m/yr (LRR). Southern sector, the Ullal spit is under erosion an average of -0.56 m/yr (EPR) and -0.59 m/yr (LRR).