Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A web-based decision support system for slopeland hazard warning.

Fan-Chieh Yu1, Chien-Yuan Chen, Sheng-Chi Lin

  • 1National Chung Hsing University, Taichung, Taiwan.

Environmental Monitoring and Assessment
|December 16, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Clinical characteristics and outcomes of advanced EGFR-mutated NSCLC treated with 45 or 30 mg starting doses of dacomitinib: a retrospective multicenter analysis.

Therapeutic advances in medical oncology·2026
Same author

Magnetic Resonance Neurography Within a Multimodal Framework for Predicting C5 Root Graftability in Traumatic Brachial Plexus Injury.

JB & JS open access·2026
Same author

Correction: Real-World Outcomes of Sequential Afatinib and Osimertinib Versus Afatinib and Chemotherapy in EGFR-Mutant NSCLC: Taiwan Multicenter GIANT Study.

Targeted oncology·2026
Same author

Real-World Outcomes of Sequential Afatinib and Osimertinib Versus Afatinib and Chemotherapy in EGFR-Mutant NSCLC: Taiwan Multicenter GIANT Study.

Targeted oncology·2026
Same author

Epigenetic corepressor BCORL1 predominates as a driver of clonal hematopoiesis of indeterminate potential in patients undergoing chronic hemodialysis: a multicenter cohort study.

Human genomics·2026
Same author

Dacomitinib as a First-Line Therapy for Advanced EGFR-Mutated Non-Small Cell Lung Cancer Without Brain Metastases: A Multicenter Retrospective Observational Study.

Cancer medicine·2026

This study introduces a WebGIS decision support system for slopeland hazard warnings using real-time rainfall data. It aids experts in assessing debris flow and landslide risks, informing evacuation decisions.

Area of Science:

  • * Geographic Information Systems (GIS)
  • * Natural Hazard Assessment
  • * Decision Support Systems

Background:

  • * Slopeland hazards, including debris flows and landslides, pose significant risks during torrential rain.
  • * Existing systems often lack real-time data integration for immediate hazard assessment.
  • * Effective warning systems are crucial for timely disaster response and public safety.

Purpose of the Study:

  • * To introduce a WebGIS decision support system for real-time slopeland hazard warning.
  • * To present the system's framework, database, and algorithms for debris flow and landslide risk assessment.
  • * To provide a tool that assists commanders in making informed decisions regarding pre-evacuation.

Main Methods:

  • * Development of a web-based GIS framework utilizing real-time monitored rainfall data.

Related Experiment Videos

  • * Implementation of algorithms for calculating debris flow triggering thresholds and landslide initiation tendencies.
  • * Design of a system that collects information to aid expert judgment rather than automatic hazard display.

    • Main Results:

    • * A functional WebGIS decision support system capable of analyzing areas prone to debris flows and landslides.
    • * The system provides crucial information for immediate response and determination of necessary pre-evacuation measures.
    • * The system acts as a component in the expert decision-making process for hazard assessment.

    Conclusions:

    • * The developed WebGIS system enhances slopeland hazard warning capabilities by integrating real-time data.
    • * The system supports expert decision-making, improving the accuracy and timeliness of hazard response.
    • * Integration with real-time rainfall estimation systems like QPESUMS is recommended for further system enhancement.