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Related Concept Videos

Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
Hazard Ratio01:12

Hazard Ratio

The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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Design Consideration01:22

Design Consideration

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Related Experiment Video

Updated: Jun 22, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Fire risk evaluation using multicriteria analysis--a case study.

Krishna Prasad Vadrevu1, Anuradha Eaturu, K V S Badarinath

  • 1Agroecosystem Management Program, Ohio Agricultural Research and Development Center (OARDC), The Ohio State University, 201 Thorne Hall, 1680 Madison Avenue, Wooster, OH 44691, USA. krisvkp@yahoo.com

Environmental Monitoring and Assessment
|May 28, 2009
PubMed
Summary

This study maps forest fire risk in South India

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Last Updated: Jun 22, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Area of Science:

  • Ecology and Environmental Science
  • Geographic Information Systems (GIS)

Background:

  • Forest fires are significant ecological disturbances in tropical deciduous forests.
  • Assessing and predicting fire risk is crucial for effective conservation and management.

Purpose of the Study:

  • To develop a spatial model for mapping forest fire risk.
  • To identify key causative factors influencing fire occurrence in South India.

Main Methods:

  • Integration of fuzzy set theory and decision-making algorithms within a GIS framework.
  • Utilized satellite remote sensing, topographic, vegetation, climate, and socioeconomic data.
  • Employed a participatory multicriteria decision-making approach (Analytical Hierarchy Process).

Main Results:

  • Successfully mapped forest fire risk, identifying high-risk 'hotspots'.
  • Demonstrated the effectiveness of the integrated fuzzy-GIS approach for risk assessment.
  • Identified key biophysical and socioeconomic drivers of forest fires.

Conclusions:

  • The developed methodology provides a robust tool for predicting forest fire occurrence.
  • Findings aid in proactive forest fire protection and management strategies.
  • Highlights the synergy of multicriteria analysis and GIS for environmental risk assessment.