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Geo-information for Disaster Monitoring and Management [electronic resource] / edited by Prem C. Pandey, Rajesh Kumar, Manish Pandey, Gregory Giuliani, R. K. Sharma, Prashant K. Srivastava.

Contributor(s): Material type: TextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XXXVII, 517 p. 203 illus., 192 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031510533
Subject(s):
Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • GB5000-5030
Online resources:
Contents:
Introduction -- Landslide/ Slope failures/ Flood and glacial lake outburst floods (GLOFS) /Drought/ Desertification status mapping/ Tsunami/ Lightening/ Forest Fire/ Earthquake / Volcanic eruptions -- Statistical, multi-criteria decision making (MCDM), machine learning models (spatial prediction models) -- Challenges and future needs.
In: Springer Nature eBookSummary: The objective of this publication is to provide insight into advancing remote sensing techniques dealing with floods, droughts, landslides, earthquakes, permafrost-related hazards, glacial lake outburst floods, forest fires, droughts, tropical cyclones, climate resilience and COVID-19. This publication will incorporate the latest technologies and techniques to illustrate disaster monitoring for acquiring information and dissemination of technological results and outcomes for the betterment of society. This publication would be of immense importance for earth scientists, policymakers and professionals working in the field of disaster risk reduction. .
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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Introduction -- Landslide/ Slope failures/ Flood and glacial lake outburst floods (GLOFS) /Drought/ Desertification status mapping/ Tsunami/ Lightening/ Forest Fire/ Earthquake / Volcanic eruptions -- Statistical, multi-criteria decision making (MCDM), machine learning models (spatial prediction models) -- Challenges and future needs.

The objective of this publication is to provide insight into advancing remote sensing techniques dealing with floods, droughts, landslides, earthquakes, permafrost-related hazards, glacial lake outburst floods, forest fires, droughts, tropical cyclones, climate resilience and COVID-19. This publication will incorporate the latest technologies and techniques to illustrate disaster monitoring for acquiring information and dissemination of technological results and outcomes for the betterment of society. This publication would be of immense importance for earth scientists, policymakers and professionals working in the field of disaster risk reduction. .

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