Potential erosion and sedimentation based on land use change by using cellular automata-artificial neural network

Potential erosion and sedimentation based on land use change by using cellular automata-artificial neural network

Erosion and sedimentation are global environmental threats that cause land degradation, reduced agricultural productivity and increased flooding risks, leading to the loss of 75 billion tons of fertile soil annually. This study employs advanced remote sensing and machine learning techniques to analy...

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Main Authors: Aditya Nugraha Putra, Istika Nita, Kurniawan Sigit Wicaksono, Novandi Rizky Prasetya, Michelle Talisia Sugiarto, Fahmi Hidayat, Zainal Alim, Sugik Edy Sartono, Pandham Giri Sasangka, Tiar Ranu Kusuma, Bilawal Abbasi, Alena Gessert, Mohd Hasmadi Ismail, Watit Khokthong
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Hydrometeorology
machine learning
remote sensing
soil degradation
soil conservation
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2025.2461058
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https://www.tandfonline.com/doi/10.1080/19475705.2025.2461058

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