リモートセンシングとGISのジャーナル

概要

Detection of Shoreline Changes Visakhapatnam Coast, Andhra Pradeshfrom Multi-Temporal Satellite Images

Kannan R, Kanungo A, Murthy MVR

The shoreline is under several emotional threats for last few decades by some natural forces and human intervention. In this paper the beaches are analyzed to assessing their evolution (erosion/accretion) associated with human intervention and climatic condition. Coastal changes are attracting more focus since they are important environmental indicators that directly impact coastal economic development and land management. Both natural and anthropogenic processes along the coast control the erosion, and accretion activities of the coastal zones. In this study, high-resolution images taken from 1989-2015 at an interval of about 5/10 years and topographic maps were collected to determine coastline changes. The present shoreline maps illustrating the shoreline erosion accretion pattern in the coastal area of Visakhapatnam district by using different sources of remote sensing data. In the present study, Landsat 5 (1989), IRS-P6 LISS III (1999), IRS-P6 LISS III (2005, 2010), LISS IV (2012) and Landsat 8 (2015) satellite images were used. The shoreline change detection was conducted using the Digital Shoreline Analysis System (DSAS). The rate of shoreline change was assessed using Linear Regression (LRR) and End Point Rate (EPR) methods. In those methods End Point Rate (EPR) was calculated by dividing the distance of shoreline movement by the time elapsed between the earliest and latest measurements at each transect. Visakhapatnam having length of coast line is 135 km. The resultant coastal maps were used to estimate the geomorphologic changes and shifting of the shoreline position. This integrated study is found useful for exploring accretion and erosion processes in the region. About 74.6 km of coastline was found to be accreting nature with average of +1.08 m/yr followed by 38.4 km of coastal line eroding with average of -1.40 m/yr and stable coastline of 41.4 km was found. This study demonstrates that combined use of satellite imagery and statistical method such as linear regression for shoreline change analysis are helpful for erosion monitoring and preventive measure.