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Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks
To understand the catastrophic processes of forest fire danger, different deterministic, probabilistic, and empiric models must be used. Simulating various surface and crown forest fires using predictive information technology could lead to the improvement of existing systems and the examination of the ecological and economic effects of forest fires in other countries. Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks provides innovative insights into forestry management and fire statistics. The content within this publication examines climate change, thermal radiation, and remote sensing. It is designed for fire investigators, forestry technicians, emergency managers, fire and rescue specialists, professionals, researchers, meteorologists, computer engineers, academicians, and students invested in topics centered around providing conjugate information on forest fire danger and risk.
Wildland Fire Danger Estimation and Mapping
The book presents a wide range of techniques for extracting information from satellite remote sensing images in forest fire danger assessment. It covers the main concepts involved in fire danger rating, and analyses the inputs derived from remotely sensed data for mapping fire danger at both the local and global scale. The questions addressed concern the estimation of fuel moisture content, the description of fuel structural properties, the estimation of meteorological danger indices, the analysis of human factors associated with fire ignition, and the integration of different risk factors in a geographic information system for fire danger management.
Forest Fire Risk Prediction
Globally, fire regimes are being altered by changing climatic conditions and land use changes. This has the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Accurate prediction of the risk of forest fires over short timescales (weeks or months) is required for land managers to target suppression resources in order to protect people, property, and infrastructure, as well as fire-sensitive ecosystems. Over longer timescales, prediction of changes in forest fire regimes is required to model the effect of wildfires on the terrestrial carbon cycle and subsequent feedbacks into the climate system. This was the motivation...
How to Predict the Spread and Intensity of Forest and Range Fires
This manual documents procedures for estimating the rate of forward spread, intensity, flame length, and size of fires burning in forests and rangelands. Contains instructions for obtaining fuel and weather data, calculating fire behavior, and interpreting the results for application to actual fire problems.
Predicting the Daily Occurrence of Lightning-caused Forest Fires
This paper describes the method currently used to predict the daily number and location of lightning-caused fires, including the various components of the model that predict occurrence, ignition, smouldering fires, and detectable fire. Evaluation results are given and discussed.
Modelling, Monitoring and Management of Forest Fires
At present there is insufficient knowledge of the behavior of fires and how they propagate. This lack of information makes it very hard to control these phenomena and is one of the biggest obstacles to the development of a reliable decision support system. Public concern regarding this topic is increasing as uncontrolled fires may lead to major ecological disasters, and usually result in negative economic and health implications for the region. Containing papers presented at the First International Conference on Modelling, Monitoring and Management of Forest Fires, this book addresses the latest research and applications of available computational tools to analyse and predict the spread of f...
Field Procedures for Verification and Adjustment of Fire Behavior Predictions
The problem of verifying predictions of fire behavior, primarily rate of spread, is discussed in terms of the fire situation for which predictions are made, and the type of fire where data are to be collected. Procedures for collecting data and performing analysis are presented for both readily accessible fires where data should be complete, and for inaccessible fires where data are likely to be incomplete. The material is prepared for use by field units, with no requirements for special equipment or computers. Procedures for selecting the most representative fuel model, for overall evaluation of prediction capability, and for developing calibration coefficients to improve future predictions are presented. Illustrated examples from several fires are included. The material is a companion publication to the fire prediction manual titled, 'INT-GTR-143: How to predict the spread and intensity of forest and range fire' by R. C. Rothermel.
2021 2nd International Conference for Emerging Technology (INCET).
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Standard Fire Behavior Fuel Models
This report describes a new set of standard fire behavior fuel models for use with Rothermels surface fire spread model and the relationship of the new set to the original set of 13 fire behavior fuel models. To assist with transition to using the new fuel models, a fuel model selection guide, fuel model crosswalk, and set of fuel model photos are provided.
Statistical Postprocessing of Ensemble Forecasts
Statistical Postprocessing of Ensemble Forecasts brings together chapters contributed by international subject-matter experts describing the current state of the art in the statistical postprocessing of ensemble forecasts. The book illustrates the use of these methods in several important applications including weather, hydrological and climate forecasts, and renewable energy forecasting. After an introductory section on ensemble forecasts and prediction systems, the second section of the book is devoted to exposition of the methods available for statistical postprocessing of ensemble forecasts: univariate and multivariate ensemble postprocessing are first reviewed by Wilks (Chapters 3), the...
