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/https://libri-media.knygos-static.lt/8c88d99d-6e2f-48dd-96c6-fcf08b4ecdc1/1)
- Leidėjas: Elsevier Science
- Metai: 2026
- Puslapiai: 270
- ISBN-10: 0443214654
- ISBN-13: 9780443214653
- Kalba: Anglų
Gnss Applications to Monitor Natural Hazards (el. knyga) (skaityta knyga) | knygos.lt
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Aprašymas
Global Navigation Satellite Systems (GNSS) are a cornerstone of modern geodetic positioning, but their true potential extends far beyond traditional applications. GNSS Applications to Monitor Natural Hazards presents a systematic, step-by-step methodology for leveraging satellite-based positioning to detect, analyze, and mitigate environmental threats-from floods and droughts to seismic shifts and landslides. As climate change intensifies natural hazards, this book bridges the gap between theory and practice, offering researchers, engineers, and policymakers reproducible techniques to enhance early-warning systems. For the first time, it also explores AI-enhanced GNSS, demonstrating how machine learning can unlock real-time hazard prediction and adaptive monitoring. Designed for both experts and newcomers, this work translates cutting-edge research into actionable strategies, empowering readers to harness GNSS technology for a more resilient future. Whether optimizing disaster response or decoding subtle environmental changes, this book is an essential guide to reducing the impact of catastrophic events through innovation.
- Leidėjas: Elsevier Science
- Metai: 2026
- Puslapiai: 270
- ISBN-10: 0443214654
- ISBN-13: 9780443214653
- Kalba: Anglų
Global Navigation Satellite Systems (GNSS) are a cornerstone of modern geodetic positioning, but their true potential extends far beyond traditional applications. GNSS Applications to Monitor Natural Hazards presents a systematic, step-by-step methodology for leveraging satellite-based positioning to detect, analyze, and mitigate environmental threats-from floods and droughts to seismic shifts and landslides. As climate change intensifies natural hazards, this book bridges the gap between theory and practice, offering researchers, engineers, and policymakers reproducible techniques to enhance early-warning systems. For the first time, it also explores AI-enhanced GNSS, demonstrating how machine learning can unlock real-time hazard prediction and adaptive monitoring. Designed for both experts and newcomers, this work translates cutting-edge research into actionable strategies, empowering readers to harness GNSS technology for a more resilient future. Whether optimizing disaster response or decoding subtle environmental changes, this book is an essential guide to reducing the impact of catastrophic events through innovation.
Atsiliepimai