Delineation of Shoreline and Associated Land Use/Land Cover Changes along the Coast of Chattogram, Bangladesh Based on Remote Sensing and GIS Techniques

Abstract

This study aimed at delineating the shoreline by using the Digital Shoreline Analysis System (DSAS 5.0) tool and detected the changes of land use/land cover (LULC) by Google Earth Engine (GEE) platform. The shoreline is divided into two zones, whereas Zone I covered 87.12[Formula: see text]km and Zone II possessed 168.05[Formula: see text]km. According to End Point Rate (EPR), the mean shoreline change rate of Zone I is 3.55[Formula: see text]m/year and Zone II is [Formula: see text]6.84[Formula: see text]m/year. Likewise, based on Linear Regression Rate (LRR), the mean shoreline change rate of Zone I is 5.46[Formula: see text]m/year and Zone II is [Formula: see text]4.71[Formula: see text]m/year, respectively. Apart from that, the Net Shoreline Movement (NSM) recorded in Zone I is 109.42[Formula: see text]m as well as Zone II is [Formula: see text]213.25[Formula: see text]m, which also revealed how much the shoreline has changed during the last 32 years. This study also used the Kalman filter model to forecast the shoreline positions for 20 years. The most destructive signal is that more than 70% of the coastline is vulnerable due to erosion, whereas 6% is highly vulnerable. By contrast, the results of LULC changes demonstrated the increasing trend of water bodies, built up, and agricultural land while vegetation along with bare land is reduced continuously. The overall accuracy is recorded above 88%, and the kappa co-efficient is found above 0.87 for all three years. The outcome of this study will provide fruitful insight into coastal land use management and adaptation measures against the ongoing along with future threats of shoreline changes to coastal ecosystems and livelihoods.

Keywords

• Digital Shoreline Analysis System (DSAS)
• land use/land cover (LULC)
• Google Earth Engine (GEE)
• Kalman filter model
• kappa co-efficient