Utvidet returrett til 31. januar 2025

Intelligent Interpretation for Geological Disasters

Om Intelligent Interpretation for Geological Disasters

This book comprehensively utilizes the new generation of artificial intelligence and remote sensing science and technology to systematically carry out researches on high-precision recognition, monitoring, analysis, and assessment of geological disasters by using different technologies of "ground, airspace, and space-based systems" and different scales of "target-semantic-region". The main contents include: 1) Intelligent interpretation theory and methods of geological disasters, 2) Intelligent analysis of landslide based on long-term ground monitoring data, 3) Intelligent analysis of landslide evolution based on optical satellite remote sensing data, 4) Deep learning-based remote sensing detection of landslide, 5) Intelligent assessment methods of landslide susceptibility, 6) Intelligent recognition of ground figure based on airspace-based remote sensing data. The book is of interest to graduate student, scientific, and technological personnel who work in the area of geological disasters, natural hazards, remote sensing, and artificial intelligence.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9789819958214
  • Bindende:
  • Hardback
  • Sider:
  • 248
  • Utgitt:
  • 13. september 2023
  • Utgave:
  • 23001
  • Dimensjoner:
  • 160x20x241 mm.
  • Vekt:
  • 541 g.
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 19. desember 2024

Beskrivelse av Intelligent Interpretation for Geological Disasters

This book comprehensively utilizes the new generation of artificial intelligence and remote sensing science and technology to systematically carry out researches on high-precision recognition, monitoring, analysis, and assessment of geological disasters by using different technologies of "ground, airspace, and space-based systems" and different scales of "target-semantic-region". The main contents include:
1) Intelligent interpretation theory and methods of geological disasters,
2) Intelligent analysis of landslide based on long-term ground monitoring data,
3) Intelligent analysis of landslide evolution based on optical satellite remote sensing data,

4) Deep learning-based remote sensing detection of landslide,
5) Intelligent assessment methods of landslide susceptibility,
6) Intelligent recognition of ground figure based on airspace-based remote sensing data.
The book is of interest to graduate student, scientific, and technological personnel who work in the area of geological disasters, natural hazards, remote sensing, and artificial intelligence.

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