Calon Promotor Program Padjadjaran Excellence Fastrack Scholarship Tahun 2026

 

Nama Lengkap : Subiyanto, S.Si., M.Sc., Ph.D.

E-mail : [email protected]

Bidang Keahlian : Pemodelan Pesisir dan Laut

Prodi S2 Calon Mahasiswa: Konservasi Laut

Prodi S3 Calon Mahasiswa: Perikanan dan Kelautan Berkelanjutan

Judul Penelitian yang Ditawarkan:

Pemodelan Stabilitas Garis Pantai Berbasis Dinamika Mangrove Menggunakan Penginderaan Jauh Multitemporal dan Deep Learning di Pesisir Cirebon, Jawa Barat

Coastal Shoreline Stability Modeling Based on Mangrove Dynamics Using Multitemporal Remote Sensing and Deep Learning in Cirebon, West Java

 

Abstrak:

Wilayah pesisir tropis menghadapi tekanan yang semakin meningkat akibat perubahan iklim, kenaikan muka air laut, serta intensifikasi aktivitas manusia, yang berdampak pada meningkatnya kerentanan terhadap abrasi dan perubahan garis pantai. Ekosistem mangrove berperan penting sebagai pelindung alami pesisir melalui kemampuannya meredam energi gelombang, menangkap sedimen, dan menstabilkan substrat. Namun, degradasi mangrove akibat konversi lahan dan pembangunan pesisir telah mengurangi fungsi protektif tersebut. Kondisi ini juga terjadi di wilayah pesisir Cirebon, West Java, yang menunjukkan dinamika abrasi dan akresi yang kompleks. Penelitian ini bertujuan untuk mengembangkan model stabilitas garis pantai berbasis dinamika mangrove dengan memanfaatkan penginderaan jauh multitemporal dan pendekatan deep learning guna memahami hubungan kuantitatif antara perubahan tutupan mangrove dan stabilitas pesisir. Metodologi penelitian dilaksanakan selama empat tahun, meliputi: (1) pengolahan citra satelit multitemporal (Landsat dan Sentinel) untuk ekstraksi mangrove dan garis pantai serta analisis perubahan menggunakan Digital Shoreline Analysis System (DSAS); (2) analisis parameter morfologi dan hidrodinamika pesisir serta pemodelan menggunakan One-Line Shoreline Model; (3) pengembangan model deep learning berbasis semantic segmentation (U-Net dan DeepLabV3+) untuk ekstraksi otomatis; dan (4) integrasi seluruh pendekatan guna menghasilkan model stabilitas garis pantai serta sistem monitoring pesisir berbasis geospasial.

 

Abstract:

Tropical coastal regions are increasingly under pressure due to climate change, sea-level rise, and the intensification of human activities, leading to heightened vulnerability to coastal erosion and shoreline changes. Mangrove ecosystems play a crucial role as natural coastal protectors by dissipating wave energy, trapping sediments, and stabilizing coastal substrates through their complex root systems. However, mangrove degradation caused by land conversion and coastal development has reduced these protective functions. This condition is also observed in the coastal area of Cirebon, West Java, which exhibits complex dynamics of erosion and accretion. This study aims to develop a shoreline stability model based on mangrove dynamics by utilizing multitemporal remote sensing and deep learning approaches to understand the quantitative relationship between changes in mangrove cover and coastal stability. The research is conducted over four years and consists of several main stages: (1) processing multitemporal satellite imagery (Landsat and Sentinel) to extract mangrove cover and shorelines, as well as analyzing shoreline changes using the Digital Shoreline Analysis System (DSAS); (2) analyzing coastal morphological and hydrodynamic parameters and modeling shoreline changes using the One-Line Shoreline Model; (3) developing deep learning models based on semantic segmentation (U-Net and DeepLabV3+) for automated extraction; and (4) integrating all approaches to produce a mangrove-based shoreline stability model and a geospatial-based coastal monitoring system.