Sagung Putri Chandra Astiti
Master Program of Environmental Science Udayana University

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

IDENTIFICATION OF SHORELINE CHANGES USING SENTINEL 2 IMAGERY DATA IN CANGGU COASTAL AREA Sagung Putri Chandra Astiti; Takahiro Osawa; I Wayan Nuarsa
ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) Vol 13 No 2 (2019)
Publisher : Master Program of Environmental Science, Postgraduate Program of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (655.628 KB) | DOI: 10.24843/EJES.2019.v13.i02.p07

Abstract

Coastal areas in the Canggu and Seminyak areas located in Badung Regency, Bali Province are very attractive tourism. The development of tourism has an impact on coastal conditions. The coastal conditions analyzed are changes in coastline that occurred during 2015-2019 using remote sensing. The satellite image data used in the analysis is Sentinel 2A image data that can be accessed for free with a spatial resolution of 10 meters. Image data processing is divided into three stages, namely preprocessing, processing, and post processing using Sentinel Application Platform (SNAP) software. The preprocessing stage includes the resampling, masking, and subset areas. The processing stage includes digitizing the coastal area, digitizing accuracy analysis using the Support Vector Machine (SVM) method, and the post processing stage including correction of shoreline changes. Bands in image data used for detection of coastal areas are band 8 (NIR), 8A (narrow NIR), 11 (SWIR), and 12 (SWIR). Based on the results of the analysis of shoreline changes carried out during 2015-2019, it was found that the average shoreline changes were 1.42 m / year with erosion conditions in which the dominant wind direction originated from the southwest towards the northeast coast of the sea of ??Bali. The results of digitizing the coastal area using the Fine Gaussian SVM method with the greatest accuracy value is 87.8%. Keywords: Shoreline Change, Remote Sensing, Sentinel 2A, SVM, Wind Direction