Benchmarking data handling strategies for landslide susceptibility modeling u…
Machine learning (ML) algorithms are frequently used in landslide susceptibility modeling. Different data handling strategies may generate variations in landslide susceptibility modeling, even when…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 16 hlm PDF, 33.426 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Rapid mapping of landslides using satellite SAR imagery: A progressive learni…
Rapid detection of landslides after an exceptional event is critical for planning effective disaster management. Previous works have typically used machine learning-based methods, including the rec…
- Edisi
- Vol.25, February 2025
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 5.502 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Advanced AI techniques for landslide susceptibility mapping and spatial predi…
Landslides, a global phenomenon, significantly impact economies and societies, especially in densely populated areas. Effective mitigation requires awareness of landslide risks, yet temporal links …
- Edisi
- Vol.25, February 2025
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 11 hlm PDF, 3.550 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Construction and application of a multilevel geohazard domain ontology: A cas…
The occurrence of geohazards entails sudden, unpredictable, and cascading effects, with numerous conceptual frameworks and intricate spatiotemporal relationships existing between hazard events. Pre…
- Edisi
- Vol.20, December 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 3.645 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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