Download or read book Predicting Forest Fire Occurrence in Ontario microform written by Brian Michael Wotton and published by Library and Archives Canada = Bibliothèque et Archives Canada. This book was released on 2004 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation documents the investigation and identification of factors influencing forest fire occurrence and describes the development and structure of models of forest fire occurrence in the forests of Ontario. An exploratory analysis of lightning strike density and rainfall relationships was carried out to determine if such a relationship could be used to improve inter-station rainfall estimation: only weak relationships between lightning and rainfall could be identified. A new moisture index, the Sheltered Duff Moisture Code (SDMC), was developed to improve lightning fire prediction capability across the country. This new index tracks forest floor moisture content at heavily sheltered areas of a stand (where lightning ignitions generally occur) better than the currently used Duff Moisture Code of the Canadian Forest Fire Weather Index (FWI) System. The SDMC can be integrated easily with the FWI System, and be adopted immediately by fire management agencies in Ontario and across the country. Logistic regression models of the probability of a lightning strike igniting a fire were developed for Ontario's fire region. The SDMC was shown to be a strong and consistent predictor in each of these models, while the presence of positive lightning strikes in an area, the timing of a lightning storm, and weather and fuel moisture conditions following a storm were also shown to have significant influence on the probability of lightning fire ignition. These daily models of lightning fire occurrence capture both low and extremely high periods of lightning fire activity well. Poisson regression methods were used to develop people-caused fire occurrence prediction models for each of the ecoregions in Ontario's fire region. Fuel moisture indices and an index of the probability of sustained flaming were identified as significant predictors of people-caused fire activity. The application of these newly developed predictive models of lightning- and people-caused fire occurrence are discussed in detail in terms of both the current daily operations of a fire management agency and the development of climate change impacts scenarios.
Download or read book Development of Mathematical Models for Predicting Daily People caused Forest Fire Occurrence in Ontario written by David Leigh Martell and published by . This book was released on 1985 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Logistic Model for Predicting Daily People caused Forest Fire Occurrence in Ontario written by David L. Martell and published by . This book was released on 1987 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Climate Change and the Future Fire Environment in Ontario written by Mike Wotton and published by Sault Ste Marie : Ontario Ministry of Natural Resources, Applied Research and Development. This book was released on 2005 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increased fi re load is expected to increase the cost of fi re management in the province 16% by the year 2040 and 54% by the year 2090 over year 2000 costs, exclusive of infl ation or other factors. [...] In addition to increases in seasonal fi re severity indices, a number of these studies also predict increases in the frequency of occurrence of extreme fi re danger in some areas of the country (e.g., Stocks et al. [...] This study uses lightning- and people-caused fi re occurrence models developed specifi cally for Ontario with GCM projections of future climate and Ontario's level of protection analysis software, LEOPARDS (see McAlpine and Hirsch 1999) to estimate the impacts of climate change on the fi re management organization both in terms of numbers of escaped fi res and with respect to changes in operationa [...] The sites of the GCM grid cell centres and OMNR weather stations used are shown in Figure 1. Fire Weather and Fire Danger To create the fi re climate of a future decade, the monthly anomalies were applied to the daily data from the OMNR fi re weather station archive from the years 1992-2001 (corresponding to the period over which lightning records were available). [...] The Fire Behaviour Prediction (FBP) System (Forestry Canada Fire Danger Group 1992) was used in conjunction with the Initial Spread Index (ISI), the Build-up Index (BUI) (calculated on the detection date of the fi re using the FWI System), and the fuel type associated with the fi re to estimate an initial rate of spread for each fi re.
Download or read book A System to Predict the Occurrence of Lightning caused Forest Fires written by P. H. Kourtz and published by 1974.. This book was released on 1974 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Predicting the Daily Occurrence of Lightning caused Forest Fires written by Peter H. Kourtz and published by Chalk River, Ont. : Petawawa National Forestry Institute. This book was released on 1991 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Forest Fire Danger Prediction Using Deterministic Probabilistic Approach written by Baranovskiy, Nikolay Viktorovich and published by IGI Global. This book was released on 2021-05-21 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forest fires cause ecological, economic, and social damage to various states of the international community. The causes of forest fires are rather varied, but the main factor is human activity in settlements, industrial facilities, objects of transport infrastructure, and intensively developed territories (in other words, anthropogenic load). In turn, storm activity is also a basic reason for forest fires in remote territories. Therefore, scientists across the world have developed methods, approaches, and systems to predict forest fire danger, including the impact of human and storm activity on forested territories. An important and comprehensive point of research is on the complex deterministic-probabilistic approach, which combines mathematical models of forest fuel ignition by various sources of high temperature and probabilistic criteria of forest fire occurrence. Forest Fire Danger Prediction Using Deterministic-Probabilistic Approach provides a comprehensive approach of forest fire danger prediction using mathematical models of forest fuel with consideration to anthropogenic load, storm activity, and meteorological parameters. Specifically, it uses the deterministic-probabilistic approach to predict forest fire danger and improve forest protection from fires. The chapters will cover various tree types, mathematical models, and solutions for reducing the destructive consequences of forest fires on ecosystems. This book is ideal for professionals and researchers working in the field of forestry, forest fire danger researchers, executives, computer engineers, practitioners, government officials, policymakers, academicians, and students looking for a new system to predict forest fire danger.
Download or read book Fireinform written by Fatima Anwer and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every year, thousands of forest fires occur in Canada; these fires pose risks to people's lives, health, and property and incur huge fire suppression costs. Accurate prediction of fire occurrences at finer temporal and spatial resolutions could aid in deploying fire-fighting resources efficiently. Timely deployment of resources at precise locations could help control fires at an earlier stage, which would reduce damage. We propose an approach to predicting forest fire occurrences at hourly intervals in small rectangular regions across Saskatchewan. To make these predictions, we pre- pared a suitable dataset, trained three machine learning classification models, namely Decision Tree, K-Nearest Neighbor (KNN), and Hidden Markov Model (HMM), and evaluated them using six performance measures. The hourly weather, vegetation, and forest fire ignitions datasets were integrated, cleaned, and transformed into time series classification format, to form the forest re occurrence (FFO) dataset. Any values missing from the instances were estimated using appropriate imputation techniques. To remove class imbalance from the FFO dataset, we applied a domain-specific undersampling approach. Predicting whether or not a fire will occur at the current hour at a given location is a binary classification problem. A model is used to predict a label, either fire or non-fire. The inputs to the model are, the weather conditions for the previous 24 hours and the current hour, as well as the vegetation type at the location. Predicting fire occurrences is an imbalanced learning problem because the ratio of non-fires to fires is very high. Our experiments studied the performance of machine learning classifiers as this ratio was increased. The experiments used two training regimes. With imbalanced training (IMB), the ratio is identical for the training and testing sets. With balanced training (BAL), the ratio for the training set is fixed at 50:50 while the ratio for the testing set is varied. Our results show that the Decision Tree and KNN-IMB models are better suited to forest fire occurrence prediction for finer temporal and spatial resolutions than are the KNN-BAL and HMM models. In particular, Decision Tree and KNN-IMB provide the highest F1-Scores.
Download or read book Mapping Wildfire Susceptibility with the BURN P3 Simulation Model written by Marc-André Parisien and published by . This book was released on 2005 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resource management in fire-dominated ecosystems requires an understanding of the probability of wildfire occurring & spreading at different points in a landscape. This report describes an approach to evaluating wildfire susceptibility, or burn probability, for fire-prone landscapes such as the boreal forest of North America. The approach involves use of the BURN-P3 (probability, prediction, & planning) landscape-level simulation model, which combines deterministic fire growth based on the Canadian Fire Behaviour Prediction System and spatial data for forest fuels & topography with probabilistic fire ignitions & spread events derived from historical fire & weather data. A case study of the application of BURN-P3 is undertaken for a boreal mixedwood area of central Saskatchewan. The results presented highlight the importance of landscape features to wildfire susceptibility and indicate whether assessments based solely on stand-level characteristics are adequate.
Download or read book Canadian Forest Fire Behavior Prediction FBP System written by Kelvin G. Hirsch and published by UBC Press. This book was released on 1996 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Field Guide to the Canadian Forest Fire Behaviour Prediction FBP System written by Stephen William Taylor and published by Canadian Forest Service, Northern Forestry Centre. This book was released on 1997 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Forest Fires in the Computer written by Forest Fire Research Institute (Canada) and published by . This book was released on 1977 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A System to Predict the Occurrence of Lighting caused Forest Fires written by P. H. Kourtz and published by . This book was released on 1974 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forest fire Research Note written by Canada. Forestry Branch and published by . This book was released on 1948 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Development and Structure of the Canadian Forest Fire Behavior Prediction System written by Canada. Forestry Canada. Fire Danger Group and published by . This book was released on 1992 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Weather Forest Vegetation and Fire Suppression Influences on Area Burned by Forest Fires in Ontario written by Justin Joseph Podur and published by . This book was released on 2006 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using several models of fire growth and fire suppression, this study shows how area burned by forest fires is influenced by weather and forest vegetation (or fuel) and is reduced by fire suppression. Previous attempts to characterize the relationship between fire suppression and area burned have focused on the initial attack process. Although the vast majority of forest fires are contained by initial attack forces while they are still small, most of the area burned in Canada is due to those few fires that escape initial attack and become large. This study focuses on these large fires. First, I used the concept of 'spread events' to refine the fire growth predictions of physical and empirical fire growth simulation models developed by Van Wagner (1969), and by Tymstra et al. (2005). I was able reduce prediction errors of fire sizes from overestimates several times too large to errors of 10-40% in some cases. Second, by calculating the fuel composition of area burned by real fires and comparing these compositions with those of area burned by simulated fires in Ontario using the WILDFIRE growth model (Todd et al. 1999), I showed how fires 'prefer' more flammable fuels as predicted by the Canadian Forest Fire Behaviour Prediction (FBP) System (Forestry Canada 1992). By developing a discrete event simulation model for the growth and suppression of large fires in the province of Ontario for multiple weather and fire suppression scenarios, I found that, while severe weather limits suppression effectiveness, suppression has an important effect even during severe seasons. For example, my model predicts that a 50% increase in suppression resources would reduce area burned by up to 55% during a severe fire season (1988), while the same increase in suppression resources would only reduce area burned by 0.4% during a mild season (1990). Decreases in fire suppression resources have more severe effects: a 50% decrease in fire suppression resources during a severe season would increase area burned by 65%, and even during a mild season (1990), a 50% decrease in resources would increase area burned by 40%. These findings were consistent with a simple probabilistic model of annual area burned, fire weather, and suppression, which I developed to validate the more complex discrete event simulation.
Download or read book Forest Fire Management in Ontario written by Ontario. Ministry of Natural Resources and published by Aviation and Fire Management Centre. This book was released on 1986 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
