RIP CURRENTS SIGNATURES ZONE DETECTION on ALOS PALSAR IMAGE at PARANGTRITIS BEACH

• Main Authors: , ARRY RETNOWATI, , Prof. Dr. SuratMan, M.Sc.
• 格式: Theses and Dissertations NonPeerReviewed
• 出版: [Yogyakarta] : Universitas Gadjah Mada 2011
• 主題: ETD
• 在線閱讀: https://repository.ugm.ac.id/88746/; http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=50772
• 機構: Universitas Gadjah Mada

Coastal area is dynamic system contain important natural environments whilst used intensively and exploited by mankind. South Coastal Area of Bantul, Yogyakarta special region in Indonesia, particularly Parangtritis coastal area, posses multiple potential threat of disaster resulting from the processes of multiple physical and dynamic coastal area. Having bay and gulf morphology as crescentic beach, Parangtritis coast has been known potentially threat by rip currents hazard, which drowned many visitors. This research was conducted on ALOS PALSAR images to extract rip currents zone at Parangtritis beach. In-situ measurement of rip current remains challenging and left signatures on remotely sensed data. No weather condition hampering SAR data acquisition, thus utilized in this study since rip current commonly related to weather. This study aims to identify and detect breaking waves region and surf zone on ALOS PALSAR images, and identify and extract the cove shape shoreline morphology of Parangtritis beach. ALOS PALSAR Fine Beam Single (FBS) HH polarization acquired on 2nd May 2007 and 17th June 2007, off nadir angle 34.3º, and in descending mode level 1.0 were utilized to derive amplitude information using SIGMASAR. Breaking waves region and surf zone which associated with rip currents was identified using edge detection operator. Shoreline morphology with cove shape as rip currents mark was extracted under series of image processing based on pixel and edge tracing approach. Radar in remote sensing carries its own illumination. Its changes contribute to increasing of images intensity variances. Ripples and plumes reflect on the backscattering due to roughness of nearshore water region increase amplitude of the small-scale waves within breaking regions. This implied to bright radar cross section for breaking waves regions. Detection of breaking waves region and surf zone on PALSAR images (microwave) were compared to AVNIR-2 image (optic). Edge detection and speckle filtering algorithm applied in this study were capable to extract breaking waves region and surf zone. To further extract cove shape shoreline based on gray scale and texture on ALOS PALSAR, refinement still need to be enhanced further more. Shoreline morphology detection showed that the cusps system has not changed much during May to June 2007 when PALSAR images acquired, but might have shifted individually. The use of optical sensor with the same spatial resolution, ALOS AVNIR-2, supports to distinguish the boundary and determine the shoreline morphology of Parangtritis beach.