Wildland Fire Danger Estimation and Mapping

The following sections are included:

• Preface

• Contents

While ‘Fire Danger’ per se cannot be measured, the physical properties of the biotic and abiotic world that relate to fire occurrence and fire behavior can. Today, increasingly sophisticated Remote Sensing methods are being developed to more accurately detect fuel properties such as species composition (fuel types), vegetation structure or plant water content — to name a few. Based on meteorological input data and physical, semi-physical or empirical model calculations, Wildland Fire Danger Rating Systems provide ‘indirect values’ — numerical indices — at different temporal scales (e.g., daily, weekly, monthly) denoting the physical conditions that may lead to fire ignition and support fire propagation. The results can be expressed as fire danger levels, ranging from ‘low’ to ‘very high’, and are commonly used in operational wildland fire management (e.g., the Canadian Fire Weather Index [FWI] System, the Russian Nesterov Index, or the U.S. National Fire Danger Rating System [NFDRS]). Today, fire danger levels are often turned into broad scale maps with the help of Geographical Information Systems (GIS) showing the areas with the different fire danger levels, and are distributed via the World Wide Web.

In this chapter we will outline some key issues dealing with Remote Sensing and GIS techniques that are covered in the following chapters, and elaborate how the Fire Danger Rating concepts could be integrated into a framework that enables comprehensive and sustainable wildland fire risk assessment. To do so, we will first raise some general thoughts about wildland fires and suggest how to approach this extremely complex phenomenon. Second, we will outline a possible fire risk analysis framework and third we will give a short overview on existing Fire Danger Rating Systems and the principles behind them.

A review of the main operational systems for fire risk/danger rating is presented in this chapter. The systems included in the revision are a European proposal based on the Fire Potential Index and a structural risk index, the US National Fire Danger Rating System, the Canadian Forest Fire Danger Rating System, the Australian and the New Zealand systems. The basis and different components of these danger rating methods are presented and commented.

The objective of this chapter is to review and discuss current methods of obtaining live fuel moisture content operationally. Methods presented include field sampling, standard fuels method, meteorological indices and remote sensing methods. Capabilities and limitations of these methods are discussed.

Different methods to estimate moisture content of dead wildland fuels are reviewed in this chapter. It is emphasized the importance of dead fuels assessment for fire danger estimation, since they are commonly drier and more flammable than live fuels. Methods presented include from meteorological indices to the use of standard fuel sticks, but the stronger emphasis is dedicated to the estimation based on remote sensing data.

Correct description of fuel properties is critical to improve fire danger assessment and fire behaviour modeling, since they guide both fire ignition and fire propagation. This chapter deals with properties of fuel that can be considered static in short periods of time: biomass loads, plant geometry, compactness, etc. Mapping these properties require a detail knowledge of vegetation vertical and horizontal structure. Several systems to classify the great diversity of vegetation characteristics in few fuel types are described, as well as methods for mapping them with special emphasis on those based on remote sensing images.

Forest fires are neither a natural disaster nor a natural calamity, with the exception of those started by natural agents, but rather an anthropogenic phenomenon, with an exclusive, direct dependence on social behaviour, whether voluntary or involuntary.

Chapter 6 provides a compelling evidence of the relationships between fire and people; reviews findings about the human dimension of wildland fires; enlists original parameters for their causal analysis and, at last, reviews the most updated tools for an in-depth geographical analysis of events, necessary to explain their distribution pattern.

This chapter proposes a framework to integrate different variables related to wildland fire ignition, propagation and effects in a synthetic wildland fire risk index, including fire danger and vulnerability assessment. Then, it focus on danger components (fire ignition and/or propagation) analyzing different spatial and temporal scales used in danger assessment. Finally, it presents several techniques to combine danger variables into synthetic danger indices.

The following sections are included:

• References

• Index