ESS-IM applied to forest fire spread prediction: Parameters tuning for a heterogeneous configuration

2016 ◽  
Author(s):  
Miguel Mendez-Garabetti ◽  
German Bianchini ◽  
Paola Caymes-Scutari ◽  
Maria Laura Tardivo
Keyword(s):  
Forest Fire ◽  
Fire Spread ◽  
Parameters Tuning ◽  
Prediction Parameters

A case study on fractal simulation of forest fire spread

2000 ◽  
Vol 43 (S1) ◽  
pp. 104-112 ◽  
Author(s):  
Qijiang Zhu ◽  
Taizong Rong ◽  
Rui Sun
Keyword(s):  
Forest Fire ◽  
Fire Spread ◽  
Fractal Simulation

The Examination of the Economical Effectiveness of Forest Fire Suppression by Using Theoretical Fire Spread Models

2016 ◽  
Vol 15 (1) ◽  
pp. 85-92
Author(s):  
Ágoston Restás
Keyword(s):  
Forest Fire ◽  
Economic Efficiency ◽  
Fire Suppression ◽  
Fire Spread ◽  
Concentric Circle ◽  
Model Based ◽  
Actual Fire ◽  
Concentric Circles ◽  
Circle Model ◽  
Rectangular Model

It is commonly known that firefighting is very expensive solution; therefore it isn’t useless to study it by the criteria of efficiency. But the meaning of efficiency for fire managers can be different from the meaning of efficiency for economists. From an economic viewpoint, it is stricter than from a technical view. Method: this research used geometric aspects of the fire spread created rectangular and concentric circles models and used basic mathematic calculations and logical conclusions. Results and discussion: The rectangular model shows the criteria of economic efficiency of firefighting. Moreover, the results from rectangular model can be transferred also to the section of concentric circles model. Based on the concentric circle model we can define both the economic efficiency of fighting forest fire and minimal criteria of successful suppression expressed by the elementary information we have regarding the actual fire.

Modeling Forest Fire Spread Through a Game Method for Modeling Based on Hexagonal Cells

2014 ◽  
pp. 321-328 ◽  
Author(s):  
Evdokia Sotirova ◽  
Emilia Velizarova ◽  
Stefka Fidanova ◽  
Krassimir Atanassov
Keyword(s):  
Forest Fire ◽  
Fire Spread

scholarly journals Estimation of Forest Fire Spread by modeling in GIS platform

2018 ◽  
Vol 11 (6) ◽  
pp. 1-6 ◽  
Author(s):  
N.M.. Rajan1 ◽  
J. Shanmugam ◽  
◽  
Keyword(s):  
Forest Fire ◽  
Fire Spread ◽  
Gis Platform

Enhancing multi-model forest fire spread prediction by exploiting multi-core parallelism

2014 ◽  
Vol 70 (2) ◽  
pp. 721-732 ◽  
Author(s):  
Carlos Brun ◽  
Tomàs Margalef ◽  
Ana Cortés ◽  
Anna Sikora
Keyword(s):  
Forest Fire ◽  
Fire Spread

On the Game Method for the forest fire spread modelling with considering the wind effect

2012 ◽  
Author(s):  
Emiliya Velizarova ◽  
Evdokia Sotirova ◽  
Krassimir Atanassov ◽  
Peter Vassilev ◽  
Stefka Fidanova
Keyword(s):  
Forest Fire ◽  
Fire Spread ◽  
Wind Effect

Forest fire risk assessment using point process modelling of fire occurrence and Monte Carlo fire simulation

2017 ◽  
Vol 26 (9) ◽  
pp. 789 ◽  
Author(s):  
Hyeyoung Woo ◽  
Woodam Chung ◽  
Jonathan M. Graham ◽  
Byungdoo Lee
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Forest Fire ◽  
Fire Risk ◽  
Fire Spread ◽  
Fire Occurrence ◽  
Occurrence Probability ◽  
Burn Probability ◽  
Forest Fire Risk ◽  
Fire Ignition

Risk assessment of forest fires requires an integrated estimation of fire occurrence probability and burn probability because fire spread is largely influenced by ignition locations as well as fuels, weather, topography and other environmental factors. This study aims to assess forest fire risk over a large forested landscape using both fire occurrence and burn probabilities. First, we use a spatial point processing method to generate a fire occurrence probability surface. We then perform a Monte Carlo fire spread simulation using multiple fire ignition points generated from the fire occurrence surface to compute burn probability across the landscape. Potential loss per land parcel due to forest fire is assessed as the combination of burn probability and government-appraised property values. We applied our methodology to the municipal boundary of Gyeongju in the Republic of Korea. The results show that the density of fire occurrence is positively associated with low elevation, moderate slope, coniferous land cover, distance to roads, high density of tombs and interaction among fire ignition locations. A correlation analysis among fire occurrence probability, burn probability, land property value and potential value loss indicates that fire risk in the study landscape is largely associated with the spatial pattern of burn probability.

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