The Canadian Forest Fire Behavior Prediction (FBP) System is a systematic method for assessing wildland fire behavior potential. This field guide provides a simplified version of the system, presented in tabular format.

The Canadian Forest Fire Behavior Prediction (FBP) system is a systematic method for assessing wildland fire behaviour potential. Presented in tabular format, this guide provides a simplified version of the system and is designed to assist field staff in making approximations of FBP System outputs.

The Canadian Forest Fire Behavior Prediction (FBP) System is a systematic method for assessing wildland fire behavior potential. This field guide provides a simplified version of the system, presented in tabular format. It was prepared to assist field staff in making first approximations of FBP System outputs when computer-based applications are not available. Quantitative estimates of head fire spread rate, fire intensity, type of fire, and spread distance, elliptical fire area, perimeter, and perimeter growth rate are provided for eighteen fuel types within five broad groupings (coniferous, deciduous, and mixedwood forests, logging slash, and grass), covering most of the major wildland fuel types found in Canada. The FBP System is intended to supplement, not replace, the experience and judgment of fire personnel.

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.

The Canadian Forest Fire Behaviour System is a systematic methodfor assessing wildland fore behaviour potential. The guide provides a simplified version of the system, presented in tabular format. It was prepared to assist staff in making first approximations of FBP system outputs when computer-based applications arenot available. Quantitative estimates of head fire spread rate, fire intensity, type of fire, and elliptical fire area, perimeter, and perimeter growth rate are provided for sixteen discrete fuel types within five broad groupings (coniferous, deciduous, and mixedwood forests, logging slash, and hrass), covering mostof the major forest fuel types found in Canada. The FBP system is intended to supplement the experience and judgment of fire managers.

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.

The Canadian Forest Fire Behavior Prediction (FBP) System is a subsystem of the larger Canadian Forest Fire Danger Rating System, which also includes the Canadian Forest Fire Weather Index (FWI) System. The FBP system provides quantitative estimates of head fire spread rate, fuel consumption, fire intensity and fire description and gives estimates of fire area, perimeter, perimeter growth rate and flank and back fire behaviour. This report describes the structure and content of the system and its use with forest fire characteristics.

The book on ‘Forest Fire: Characteristics and Management’ embodies seven chapters providing an updated comprehensive information on history, causes & types, characteristics & behaviour, effects of fire on ecosystem dynamics i.e., plant, community, ecosystem, wildlife and soils, damaging & beneficial effects, prediction & management and, prevention & control of forest fires. In each chapter the readers will find complete information aptly backed by authentic data, examples and illustrations. Chapter eight is dedicated to bibliography. This book will be useful to students and researchers as a part of their curriculum and for forest managers/officials and planners as an important guide for managing forest fires.

Scientists and managers alike need timely, cost-effective, and technically appropriate fire-related information to develop functional strategies for the diverse fire communities. "Remote Sensing Modeling and Applications to Wildland Fires" addresses wildland fire management needs by presenting discussions that link ecology and the physical sciences from local to regional levels, views on integrated decision support data for policy and decision makers, new technologies and techniques, and future challenges and how remote sensing might help to address them. While creating awareness of wildland fire management and rehabilitation issues, hands-on experience in applying remote sensing and simulation modeling is also shared. This book will be a useful reference work for researchers, practitioners and graduate students in the fields of fire science, remote sensing and modeling applications. Professor John J. Qu works at the Department of Geography and GeoInformation Science at George Mason University (GMU), USA. He is the Founder and Director of the Environmental Science and Technology Center (ESTC) and EastFIRE Lab at GMU.