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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.
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, 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.
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...
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...
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.
Plant-Fire Interactions
This book provides a unique exploration of the inter-relationships between the science of plant environmental responses and the understanding and management of forest fires. It bridges the gap between plant ecologists, interested in the functional and evolutionary consequences of fire in ecosystems, with foresters and fire managers, interested in effectively reducing fire hazard and damage. This innovation in this study lies in its focus on the physiological responses of plants that are of relevance for predicting forest fire risk, behaviour and management. It covers the evolutionary trade-offs in the resistance of plants to fire and drought, and its implications for predicting fuel moisture and fire risk; the importance of floristics and plant traits, in interaction with landform and atmospheric conditions, to successfully predict fire behaviour, and provides recommendations for pre- and post- fire management, in relation with the functional composition of the community. The book will be particularly focused on examples from Mediterranean environments, but the underlying principles will be of broader utility.
Canadian Forest Fire Behavior Prediction (FBP) System
The Canadian Forest Fire Behaviour Prediction (FBP) System provides a systematic method of assessing fire behaviour. The FBP System has 14 primary inputs that can be divided into 5 general categories: fuels, weather, topography, foliar moisture content, and type and duration of prediction. In the FBP System these inputs are used to mathematically develop 4 primary and 11 secondary outputs. Primary outputs are generally based on a fire intensity equation, and secondary outputs are calculated using a simple elliptical fire growth model. This publication provides diagrams, examples, and exercises that explain the FBP System in a user-oriented manner. This guideline delineates the interpretation of the FBP System's inputs and outputs and details how the predictions are derived.
