Fire Arrival Research Articles

STUDY OF FIRE LOCATION TIME IN HIGH-STORY BUILDINGS IN CITIES OF UKRAINE

The effectiveness of extinguishing a fire depends on the speed of arrival of fire and rescue units at the scene and the time it will take to deliver the "first" barrel (extinguishing agent) to the location. The rapid supply of fire extinguishing agent gives a chance to localize and then eliminate the fire in the initial phase, although the result depends significantly on the action in the "first minutes of the fire". The urban settlements into appropriate groups based on population and territory using methods of cluster analysis were divided. One settlement was selected from each group of cities, and then data on fires for the period of 2020 was processed. The statistical data obtained from the operational coordination centers of the State Emergency Service of Ukraine in the cities of Kyiv, Kharkiv, Poltava, and Berdyansk, which characterize the process of extinguishing fires, namely the time of arrival of fire and rescue units at the scene of the fire, the time of localization of the fire and the area of the fire, were analyzed. Statistical data were selected only for high-rise buildings. The interrelationship of the following parameters was established: burning area, building floor, time of fire localization. The obtained static data indicate that the area of fire and the time of localization increases on average from 3.5 to 6 times. The result of the data analysis provides a clear understanding of the need to improve the available means and methods (tactics) of extinguishing fires in multi-story buildings. We proposed to use the Typhoon-10 impulse fire extinguisher, which has been converted into a pneumatic gun for the discrete delivery of fire extinguishing substances placed in a special container, as the basis of firefighting tactics in multi-story buildings. Discrete delivery of fire-extinguishing substances in a container allows to reduce the time of localization of fires in multi-story buildings due to the efficiency of deployment of the installation and accurate delivery through the window opening directly to the center of the fire.

It’s about Time: A Method for Estimating Wildfire Arrival and Weather Conditions at Field-Sampled Locations

Weather conditions at the time of wildfire front arrival strongly influence fire behavior and effects, yet few methods exist for estimating weather conditions more spatio-temporally resolved than coarse-grain (e.g., 4 km) daily averages. When a fire front advances rapidly and weather conditions are heterogeneous over space and time, greater spatio-temporal precision is required to accurately link fire weather to observed fire effects. To identify the influence of fire weather on fire effects observed across a sample of existing forest inventory plots during a wind-driven megafire event in the US Pacific Northwest, we explored and compared three methods for estimating time of fire arrival and the wind speed at that arrival time for each plot location. Two methods were based on widely used, remotely sensed active fire data products with dissimilar spatial and temporal resolutions. The third and preferred method, Modeled-Weather Interpolated Perimeters (MoWIP), is a new approach that leveraged fine-grained (1.3 km, hourly) wind speed and direction from modeled fire weather to guide interpolation of aerial infrared-detected (IR) operational perimeters, subdividing the time intervals defined by sequential IR perimeters into quartile intervals to enhance temporal resolution of predicted fire arrival times. Our description of these fire arrival “time stamp” methods and discussion of their utility and shortcomings should prove useful to fire scientists, ecologists, land managers, and future analyses seeking to link estimated fire weather and observed fire effects.

Better bushfire safety decision‐making: Making sense of complexities and challenges surrounding ‘Stay or Go’ and the Australian Fire Danger Rating System

AbstractIn the context of bushfires (and other emergencies), state agencies should avoid developing policy and/or advice that locks people into rigid binary choices. In Victoria, Australia post‐fire inquiries have found the bushfire safety advice often referred to as ‘Stay (and defend your property) or Go (early before the fire arrives)’ to be contradictory and competing in its logic. However, this advice continues to provide a basis for positive community safety outcomes. It can still be used effectively by policy makers and practitioners within emergency management agencies to inform and educate a highly urbanised society that has become experientially detached from bushfire. With the introduction of the Australian Fire Danger Ratings System and climate challenges ahead, it appears that logics at the core of ‘Stay or Go’ will continue to offer communities located alongside complex bushfire risk in urban, regional, and rural areas a basis for appropriate safety decisions using the best available information.Points for practitioners Provides guidelines for ways in which ‘Stay or Go’ advice can continue to be used by emergency management policy makers and practitioners as a basis for positive community safety outcomes from bushfire risk. Challenges suggestions from significant bushfire inquiries that the logics at the core of ‘Stay or Go’ contradict each other. Staying and defending a home or leaving early offer a basis for surviving bushfire depending on individual circumstances—practitioners should ensure that this is a key message of bushfire education campaigns. Provides pathways for practitioners and the community to work together and co‐create collaborative bushfire plans whereby preparing for bushfire risk is a shared responsibility.

Using Satellite‐Derived Fire Arrival Times for Coupled Wildfire‐Air Quality Simulations at Regional Scales of the 2020 California Wildfire Season

AbstractWildfire frequency has increased in the Western US over recent decades, driven by climate change and a legacy of forest management practices. Consequently, human structures, health, and life are increasingly at risk due to wildfires. Furthermore, wildfire smoke presents a growing hazard for regional and national air quality. In response, many scientific tools have been developed to study and forecast wildfire behavior, or test interventions that may mitigate risk. In this study, we present a retrospective analysis of 1 month of the 2020 Northern California wildfire season, when many wildfires with varying environments and behavior impacted regional air quality. We simulated this period using a coupled numerical weather prediction model with online atmospheric chemistry, and compare two approaches to representing smoke emissions: an online fire spread model driven by remotely sensed fire arrival times and a biomass burning emissions inventory. First, we quantify the differences in smoke emissions and timing of fire activity, and characterize the subsequent impact on estimates of smoke emissions. Next, we compare the simulated smoke to surface observations and remotely sensed smoke; we find that despite differences in the simulated smoke surface concentrations, the two models achieve similar levels of accuracy. We present a detailed comparison between the performance and relative strengths of both approaches, and discuss potential refinements that could further improve future simulations of wildfire smoke. Finally, we characterize the interactions between smoke and meteorology during this event, and discuss the implications that increases in regional smoke may have on future meteorological conditions.

Fire favors sexual precocity in a Mediterranean pine

Wildfires are a natural disturbance in many ecosystems. Consequently, plant species have acquired traits that allow them to resist and regenerate in an environment with recurrent fires. A key trait in fire‐prone ecosystems is the age at first reproduction (maturity age); populations of non‐resprouting species cannot persist when the fire interval is shorter than this age. Maturity age is variable among individuals, so we hypothesized that short fire intervals select for early seed production (precocity). We selected 13 plots with different fire regimes in eastern Spain, all dominated by Pinus halepensis (a non‐resprouting serotinous pine species). Then, we evaluated the age at first reproduction and the size of the canopy seed bank of each individual tree. Our results show a significant effect of fire regime on the onset of reproduction in this species, suggesting a selection towards higher precocity in populations subject to shorter fire intervals. Due to this higher precocity, pines stored more cones and therefore, increased their potential for reproduction post‐fire. We provide the first field evidence that fire can act as a driver of precocity. Being precocious in fire‐prone environments is adaptive because it increases the probability of having a significant seed bank when the next fire arrives.

Abstract 9873: Comparing Base Locations for Drone-Delivered Defibrillators

Introduction: Drone-delivered defibrillators may improve response for out-of-hospital cardiac arrest (OHCA). Prior studies have assumed that drones may be stationed at any police, fire, or paramedic station; however, cross-service implementation may not be logistically feasible. We sought to compare estimated response times by drone base location type. Methods: We included OHCAs (Jan. 2014 to Dec. 2020) in southern Vancouver Island, British Columbia, Canada where OHCA response includes fire and paramedic services. We created four models with candidate drone base locations at: police stations, fire stations, paramedic stations, and on a grid with 1 km sides as an optimistic model. We used mathematical optimization to select 1-5 drone bases for each model. Assuming a drone system had been in place during the study period and accounting for drone availability, we estimated 9-1-1 call-to-defibrillator intervals (measured to either drone, paramedic, or fire arrival) and calculated the proportion of OHCAs where a drone would arrive prior to fire and paramedic for each model. Median response times were compared to historical response using one-sided sign tests. Results: We included 1,610 OHCAs with a median historical response time of 6.4 mins (IQR 5.0-8.6). We identified 21 police stations, 59 fire stations, 21 paramedic stations, and 7,008 grid locations in the study area. Median 9-1-1 call-to-defibrillator intervals ranged from 4.3-5.3 mins for police, 4.3-5.3 mins for fire, 4.5-5.4 mins for paramedic, and 4.2-5.4 mins for grid locations (all P<0.001). Drones arrived prior to fire and paramedics in 36.6-65.4% of cases for police, 38.1-66.2% for fire, 37.3-63.2% for paramedic, and 35.7-66.8% for grid locations. Conclusion: Locating drone bases at different types of emergency service stations significantly decreases 9-1-1 call-to-defibrillator intervals, while resulting in similar response intervals to those achieved using optimistic grid-optimal locations.

Machine Learning Estimation of Fire Arrival Time from Level-2 Active Fires Satellite Data

Producing high-resolution near-real-time forecasts of fire behavior and smoke impact that are useful for fire and air quality management requires accurate initialization of the fire location. One common representation of the fire progression is through the fire arrival time, which defines the time that the fire arrives at a given location. Estimating the fire arrival time is critical for initializing the fire location within coupled fire-atmosphere models. We present a new method that utilizes machine learning to estimate the fire arrival time from satellite data in the form of burning/not burning/no data rasters. The proposed method, based on a support vector machine (SVM), is tested on the 10 largest California wildfires of the 2020 fire season, and evaluated using independent observed data from airborne infrared (IR) fire perimeters. The SVM method results indicate a good agreement with airborne fire observations in terms of the fire growth and a spatial representation of the fire extent. A 12% burned area absolute percentage error, a 5% total burned area mean percentage error, a 0.21 False Alarm Ratio average, a 0.86 Probability of Detection average, and a 0.82 Sørensen’s coefficient average suggest that this method can be used to monitor wildfires in near-real-time and provide accurate fire arrival times for improving fire modeling even in the absence of IR fire perimeters.

РЕЗУЛЬТАТИ АНАЛІЗУ ОСНОВНИХ ПОКАЗНИКІВ СТАТИСТИКИ ПОЖЕЖ В УКРАЇНІ ПО ВІДНОШЕННЮ ДО ЧАСУ ПРИБУТТЯ ПЕРШОГО ПІДРОЗДІЛУ ПОЖЕЖНОЇ ОХОРОНИ

Проаналізовано основні показники статистики пожеж в Україні, як в цілому, так і у містах та сільській місцевості України окремо, за нормативним часом прибуття першого підрозділу пожежної охорони до місця виклику за довгостроковий період.

Stochastic decision trigger modelling to assess the probability of wildland fire impact

The ability to estimate both the time and probability of a wildfire reaching an area to be protected is critically important to preventing loss of human life and property, and damage to ecological and economic assets. Wildfire decision trigger modelling has been used to assess fire exposure and create evacuation trigger buffers around the communities providing a specific amount of warning time. This approach has been applied in multiple scenarios including household-level and community-level evacuation planning and during suppression operations. However, little attention has been paid to input data uncertainty using this modelling approach. This study presents an innovative stochastic fire simulation decision trigger modelling method that produces a probability map of the fire arrival to areas to be protected by simulating (n) wildfire decision trigger buffers with varied input data according to a potential range of deviations. The Tubbs fire (USA) was used as case study to show the applicability of this approach to estimate the probability of wildland fire impact. Our results highlighted the importance of considering input data uncertainty in operational environments to estimate fire progression and decision trigger buffers to better develop suppression tactic and strategy. The method presented may be solved in real-time and used with any empirical fire propagation model as a core engine. Practical real-time implications of this fire simulation mode are discussed.

Designing Operationally Relevant Daily Large Fire Containment Strategies Using Risk Assessment Results

In this study, we aim to advance the optimization of daily large fire containment strategies for ground-based suppression resources by leveraging fire risk assessment results commonly used by fire managers in the western USA. We begin from an existing decision framework that spatially overlays fire risk assessment results with pre-identified potential wildland fire operational delineations (PODs), and then clusters PODs into a response POD (rPOD) using a mixed integer program (MIP) model to minimize expected loss. We improve and expand upon this decision framework through enhanced fire modeling integration and refined analysis of probabilistic and time-sensitive information. Specifically, we expand the set of data inputs to include raster layers of simulated burn probability, flame length probability, fire arrival time, and expected net value change, all calculated using a common set of stochastic weather forecasts and landscape data. Furthermore, we develop a secondary optimization model that, for a given optimal rPOD, dictates the timing of fire line construction activities to ensure completion of containment line prior to fire arrival along specific rPOD edges. The set of management decisions considered includes assignment of PODs to be included in the rPOD, assignment of suppression resources to protect susceptible structures within the rPOD, and assignment of suppression resources to construct fire lines, on specific days, along the perimeter of the rPOD. We explore how fire manager risk preferences regarding firefighter safety affect optimal rPOD characteristics, and use a simple decision tree to display multiple solutions and support rapid assessment of alternatives. We base our test cases on the FSPro simulation of the 2017 Sliderock Fire that burned on the Lolo National Forest in Montana, USA. The overarching goal of this research is to generate operationally relevant decision support that can best balance the benefits and losses from wildfire and the cost from responding to wildfire.

The Generation and Forecast of Extreme Winds during the Origin and Progression of the 2017 Tubbs Fire

On 8–9 October 2017, fourteen wildfires developed rapidly during a strong Diablo wind event in northern California including the Tubbs Fire, which travelled over 19 km in 3.25 h. Here, we applied the CAWFE® coupled numerical weather prediction-fire modeling system to investigate the airflow regime and extreme wind peaks underlying the extreme fire behavior using simulations that refine from a 10 km to a 185 m horizontal grid spacing. We found that as Diablo winds travelled south down the Sacramento Valley and fanned out southwestward over the Wine Country, their strength waxed and waned and their direction wavered, creating varying locations near fire origins where wind overrunning topography reached 30–40 m/s, along with streaks and bursts of strong winds in the lee of some topographic features and stagnation downstream of others. Despite a statically stable layer in the lowest 1.5 km, the high Froude number flow sometimes resembled a hydraulic jump. Elsewhere, the flow behaved similarly to neutrally-stratified flow over small hills, creating wind extrema that exceeded 40 m/s at the crest of some lesser hills including near the Tubbs fire ignition, but which shed bursts of high speed winds that travel downstream at approximately 5–7-min intervals. Nonetheless, simulated fire growth lagged satellite detection of fire arrival in Santa Rosa by up to 1 h, although whether the data detect fire line or spotting is ambiguous. A forecast simulation with a 370 m horizontal grid spacing produced an on-time fire line arrival in Santa Rosa, with calculations executed 4 times faster than real time on a single computer processor.

Approximation Algorithms for the Geometric Firefighter and Budget Fence Problems

Let R denote a connected region inside a simple polygon, P. By building barriers (typically straight-line segments) in P \ R , we want to separate from R part(s) of P of maximum area. All edges of the boundary of P are assumed to be already constructed or natural barriers. In this paper we introduce two versions of this problem. In the budget fence version the region R is static, and there is an upper bound on the total length of barriers we may build. In the basic geometric firefighter version we assume that R represents a fire that is spreading over P at constant speed (varying speed can also be handled). Building a barrier takes time proportional to its length, and each barrier must be completed before the fire arrives. In this paper we are assuming that barriers are chosen from a given set B that satisfies certain conditions. Even for simple cases (e.g., P is a convex polygon and B the set of all diagonals), both problems are shown to be NP-hard. Our main result is an efficient ≈11.65 approximation algorithm for the firefighter problem, where the set B of allowed barriers is any set of straight-line segments with all endpoints on the boundary of P and pairwise disjoint interiors. Since this algorithm solves a much more general problem—a hybrid of scheduling and maximum coverage—it may find wider applications. We also provide a polynomial-time approximation scheme for the budget fence problem, for the case where barriers chosen from a set of straight-line cuts of the polygon must not cross.

Estimation of Forest Fire Spread by modeling in GIS platform

Fire has been a source of disturbance for thousands of years. It has been found through research that forest fires mostly happen due to human interactions with the forests. The disturbances from humans mostly affect the forest areas that are nearer to the human habitations and roads. Statistical estimates infer that Tamil Nadu is one of the Indian states which is also frequently disturbed by forest fires. A spatial extent of about 4230.94 km2 of Tamil Nadu is vulnerable to human interventions from all the roads and settlements that can cause forest fires. This means that, no afforestation practice in future should be carried out within these areas. Instead, such practices in future could be encouraged in areas wherein there is ‘zero’ risk due to anthropogenic threats. This is essential to ensure the safer survival of any artificial plantations. If ‘Forest Fire Spread Model’ is prepared for these areas, the same will prove to be helpful in finding out the direction of fire in the event of a fire-spread from a spot. For any forest area, the factors that is responsible for the spread of a fire are, Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Aspect, Slope, and Land Surface Temperature (LST). Objective: To prepare a ‘forest fire spread model’ that could be used for predicting the direction of fire movement and estimating the area of fire spread after a stipulated time. Method: In this research, firstly a ‘Fire reach susceptibility index’ map has been prepared which could then be fed to a model that has be prepared using Python customizing facility in QGIS, to estimate the ‘forest fire spread’ in a course of time. The factors that have been considered in this study were Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Aspect, Slope, and Land Surface Temperature (LST). Findings: The ‘FRSI’ Map preparation phase considers all the necessary factors as suggested by the previously conducted researches. The hence prepared map has also been undergone through ‘accuracy assessment’ to ensure its reliability in its usage for the estimation of forest fire spread. This has been done by checking the correlation between the number of fire incidences and each district’s corresponding average FRSI value. This map and the number of fire incidences have a correlation coefficient of ‘0.94’, thereby making this map to achieve an accuracy of 97.43%. Thus, the average FRSI value and the number of fire incidences are relevant, which means that the prepared FRSI map is reliable. With the help of this map, ‘fire spread model’ has been prepared from which it has been estimated that, for a safer region in Tirunelveli district, the fire could spread to an extent of 38.56 km2 in 9 hours. Application: The ‘Forest Fire Spread Model’ prepared for these areas would prove to be helpful in finding out the direction of fire in the event of a fire-spread from a spot. Hence, this model could be useful to ‘Tamil Nadu Forest Department’ in predicting the most expected spot of arrival of fire in a time duration. This could ensure that plantations nearby are safeguarded from any possible adverse effects of human interventions. Keywords: Forest-fire spread, FRSI, LST, NDVI, NDWI

Short-term fire front spread prediction using inverse modelling and airborne infrared images

A wildfire forecasting tool capable of estimating the fire perimeter position sufficiently in advance of the actual fire arrival will assist firefighting operations and optimise available resources. However, owing to limited knowledge of fire event characteristics (e.g. fuel distribution and characteristics, weather variability) and the short time available to deliver a forecast, most of the current models only provide a rough approximation of the forthcoming fire positions and dynamics. The problem can be tackled by coupling data assimilation and inverse modelling techniques. We present an inverse modelling-based algorithm that uses infrared airborne images to forecast short-term wildfire dynamics with a positive lead time. The algorithm is applied to two real-scale mallee-heath shrubland fire experiments, of 9 and 25 ha, successfully forecasting the fire perimeter shape and position in the short term. Forecast dependency on the assimilation windows is explored to prepare the system to meet real scenario constraints. It is envisaged the system will be applied at larger time and space scales.

Mobile-Phone Dispatch of Laypersons for CPR in Out-of-Hospital Cardiac Arrest

BackgroundCardiopulmonary resuscitation (CPR) performed by bystanders is associated with increased survival rates among persons with out-of-hospital cardiac arrest. We investigated whether rates of bystander-initiated CPR could be increased with the use of a mobile-phone positioning system that could instantly locate mobile-phone users and dispatch lay volunteers who were trained in CPR to a patient nearby with out-of-hospital cardiac arrest.MethodsWe conducted a blinded, randomized, controlled trial in Stockholm from April 2012 through December 2013. A mobile-phone positioning system that was activated when ambulance, fire, and police services were dispatched was used to locate trained volunteers who were within 500 m of patients with out-of-hospital cardiac arrest; volunteers were then dispatched to the patients (the intervention group) or not dispatched to them (the control group). The primary outcome was bystander-initiated CPR before the arrival of ambulance, fire, and police services.ResultsA total of 5989 lay volunteers who were trained in CPR were recruited initially, and overall 9828 were recruited during the study. The mobile-phone positioning system was activated in 667 out-of-hospital cardiac arrests: 46% (306 patients) in the intervention group and 54% (361 patients) in the control group. The rate of bystander-initiated CPR was 62% (188 of 305 patients) in the intervention group and 48% (172 of 360 patients) in the control group (absolute difference for intervention vs. control, 14 percentage points; 95% confidence interval, 6 to 21; P<0.001).ConclusionsA mobile-phone positioning system to dispatch lay volunteers who were trained in CPR was associated with significantly increased rates of bystander-initiated CPR among persons with out-of-hospital cardiac arrest. (Funded by the Swedish Heart–Lung Foundation and Stockholm County; ClinicalTrials.gov number, NCT01789554.)

Temperatures below leaf litter during winter prescribed burns: implications for litter-roosting bats

Some bat species, including eastern red bats (Lasiurus borealis), roost for short periods beneath leaf litter on the forest floor during winter in the south-eastern USA, a region subjected to frequent fire. The variability in fuel consumption, the heterogeneous nature of burns, and the effects of litter and duff moisture on forest-floor temperatures during winter burning could influence potential survival for bats beneath the leaf litter if they are unable to escape on-coming flames. We measured temperatures below leaf litter in 64 south-slope plots during nine controlled burns in the Ouachita Mountains of Arkansas to determine the probability of survival. Maximum temperature recorded under leaf litter at each plot averaged 292°C (±20 s.e.) and ranged from 10 to 717°C. Only three (5%) of the plots experienced temperatures that were deemed survivable (&lt;60°C sustained for 60 s) during burns on warmer winter days (air temperatures 15.0–26.1°C). Temperatures below the leaf litter measured just before the arrival of fire (average = 19.6°C) suggested that if bats were roosting in plots they would have been in shallow torpor, which would have enabled faster escape from approaching flames. Burning during the warmer periods of winter (e.g. ≥15°C) and during afternoons could potentially improve survival by bats roosting under leaf litter by reducing arousal and escape times.

Optimal resource allocation in a serotinous non‐resprouting plant species under different fire regimes

Summary Serotiny, the retention of mature seeds in closed fruits within the canopy for over a year, is a common trait in fire‐prone environments. When competition with adult plants prevents seedling establishment between fire events and in the absence of post‐release soil seed dormancy, strong serotiny, i.e. the retention of all seeds until the next fire, appears as the best strategy. Despite the low levels of inter‐fire seed recruitment for several species in both Australian and South African fire‐prone environments, considerable variation in the duration of fruit retention is nevertheless observed among species. Our aim is to predict optimal age‐specific reproductive schedules in a perennial, serotinous species, when cone maintenance is costly. We focus on species where adults are killed by fire, without a soil seed‐bank. We explicitly consider a trade‐off between growth (which determines plant survival), seed production and seed maintenance. In our model recruitment relies upon fire events. We use dynamic programming to determine, for given fire regimes, the optimal pattern of resource allocation. We further study the effect of changes in fire regime on the viability of populations adapted to some historical fire regime. We find that, whenever maximal plant survival probability is low, the optimal strategy consists in reducing resource allocation to seed maintenance while increasing resource allocation to annual seed production. This illustrates a trade‐off between current and future reproduction. A low rather than a strong level of serotiny should evolve whenever the variance of fire intervals is large and the mean fire interval is low. Low levels of serotiny could constitute a bet‐hedging strategy with decreasing predictability of the arrival of fire. Once adapted to some historical fire regime, serotinous populations are highly sensitive to a change in mean fire frequency and to an increase in the variance of fire intervals. Populations adapted to a historically high level of variance in fire return are more robust to changes in fire regime. Synthesis: Life‐history trade‐offs and low predictability of fire intervals may favour low rather than strong levels of serotiny even when recruitment essentially occurs just after fire events.

Stay and defend or leave early: Policy problems and experiences during the 2003 Victorian bushfires

Australian state and territory fire authorities advise residents to make a decision to prepare, stay and defend their properties from bushfires or leave well before the fire arrives in their area. The ‘Stay and defend or leave early’ policy is underpinned by strong evidence that well-prepared houses can be successfully defended and that late evacuation is a dangerous strategy. This paper presents the results of a study of the policy's implementation during the 2003 bushfires in North East Victoria and East Gippsland. Results suggest that despite high levels of awareness and support for the policy, there is some confusion over what it means to ‘stay and defend’ and ‘leave early’.

Forest landowner decisions and the value of information under fire risk

We estimate the value of three types of information about fire risk to a nonindustrial forest landowner: the relationship between fire arrival rates and stand age, the magnitude of fire arrival rates, and the efficacy of fuel reduction treatment. Our model incorporates planting density and the level and timing of fuel reduction treatment as landowner decisions. These factors affect, among other things, the loss a landowner incurs should fire arrive before harvesting. The value of information depends on the nature and combination of mistakes a landowner makes, the relationship between fire arrival and stand age, and on whether the landowner undertakes fuel treatment and values nontimber benefits. Information of various types is of most value to a landowner who does not undertake fuel treatment. The value of information about the magnitude of fire risk is also more than twice as high when the landowner underestimates fire risk, rather than overestimating it. For a landowner who undertakes fuel treatment but makes multiple mistakes, the asymmetry between overestimating and underestimating fire risk and efficacy of fuel reduction is even more pronounced.

Nonindustrial private landowners, fires, and the wildland–urban interface

Abstract We estimate the value to a non-industrial forest landowner of information about the magnitude of fire arrival rates. A simulation based on a model from Amacher et al. [Amacher, G., Malik, A., Haight, R., in press. Not getting burned: the importance of fire prevention in forest management. Land Economics] is used to assess the cost of mistakes made by a landowner when stand management decisions are made without perfect knowledge of the fire arrival probability. These costs are reflected in the higher losses incurred by a landowner if fire arrives during a rotation. The representative landowner studied in the simulation is assumed to value nontimber benefits, and to make rotation age, planting density and fuel reduction decisions. We find that the value of information about the overall magnitude of fire risk is more than twice as high when the landowner underestimates fire risk, rather than overestimating it.