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Satellite Imagery for Classification Analysis of Abrasion Areas on Panaitan, Banten Ismail, Ghaffar; Kurniawan, Robert; Silvia Ni'matul Maula
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 17 No 2 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v17i2.850

Abstract

Introduction/Main Objectives: Abrasion causes severe environmental degradation and socio- economic losses, Waton and Karang Gundul Islands have already subsided due to erosion, posing risks to Panaitan Island, a national park that also faces deforestation, infrastructure development, and vegetation loss which may intensify abrasion. Background Problems: Limited spatial data on coastal abrasion in Panaitan Island hampers effective monitoring and management, highlighting the need for spatially explicit analysis. Novelty: This study identified and classified abrasion-prone areas on Panaitan Island (a rarely exposed island) with rarely variables which have impactful indices such as MVI, TCI, and LSWI. Research Methods: Landsat 8 and Sentinel-2 imagery from 2018 and 2023 were analyzed to assess changes in vegetation, mangroves, surface temperature, and soil moisture. Random Forest, Support Vector Machine, and Logistic Regression were employed to classify abrasion-prone areas. Finding/Results: The analysis revealed signs of abrasion covering 2.04 km², with Random Forest achieving the highest accuracy (82.23%) and NDVI as the most influential variable; abrasion was mainly associated with declining forest and mangrove cover, soil moisture showed weak correlation, while moderate surface temperature had a positive effect. Preventive measures such as reforestation and mangrove rehabilitation are recommended to mitigate risks and ensure long-term environmental sustainability.