Forest Fire Management using GIS

Gis developmentAbstract

Wild fire - destroys human wealth Avoid Wild fire Using forest fire simulation

Factorso Wind velocityo Direction

Gis developmentIntroduction

Applicationo Hazard map productiono Forest fire simulation & Resource management

Information layers such as Digital Elevation Model (DEM)

Index of flammability

Gis developmentForest Fire

Natural fire Prescribed burning the one which starts by human

Gis developmentForest Fire and GIS

GIS in fire risk/probability assessment

GIS in prescribed burn planning

GIS in preventing fire and its spread

GIS in fire simulation GIS in post fire assessment

and monitoring GIS in disaster management

Gis developmentSimulation

Simulation of a phenomenon is the operation that consists of studying its behaviour in situations generated by virtual data in order to better understand the behaviour of the phenomenon in the real world.

Parameters of forest fire simulation

Wind Vegetation coverage Topography Fire starting point Temperature

Gis developmentCombined EffectsCombined effect of wind and topography: wind increases the flame of a burning cell and decreases resistance to fire. If the aspect of a cell is against the wind, the effect of wind is increased and if it is toward the wind, the effect of wind is decreased and even sometimes it can be neglected. Effect of the wind can be evaluated by determining the angle between normal vector (perpendicular to the surface) of a cell and vector of wind direction.

Gis developmentCombined EffectsCombined effect of wind, topography and temperature:

Another effect of wind is to accelerate cooling. In the case of adjacent cells to the burning ones, wind increases the loss of received energy. If the aspect of a cell is against the wind direction, the cooling effect of the wind will increase and reduction of temperature makes this effect more severe.

Gis developmentModels for SimulationConcentric model

R=x a Vf T

Concentric model, two circles show fire spread prediction after 1 and 2 hours.

where, T is the time in hour, Vf is wind velocity in kilometer per hour, a is a unit less coefficient, x is a coefficient which falls between 0 and 1 and is related to index of flammability and finally R is the radius of circles in kilometer.

Gis developmentModels for SimulationConcentric model

ADVANTAGES:•It is the simplest model for forest fire simulation.

DISADVANTAGES:•This model not onlt has some technical problem s but also experiment have show that fire spread is never circular•So it is nit always reliable.

Gis developmentModels for SimulationPseudo-conical Model

pseudo-conical model, two conics show fire spread prediction after 1 and 2 hours

In pseudo-conical model fire is assumed to spread in a flat conic shape which its vertex is located at the starting point of fire and its extension is along the direction of wind.

Gis developmentModels for SimulationPseudo-conical Model

ADVANTAGES:•More accurate than concentric model.

DISADVANTAGES:•This model has no perticular information layer.•This model is not base on GIS.

Gis developmentModels for SimulationPolygonal model

If q is the angle measured anticlockwise from x axes of a Cartesian coordinate system then the coordinates of each vertex can be calculated by:

Where Yd, Xd are the coordinates of fire starting point, Vf is wind velocity in kilometer per hour, T is the time in hour, Dv is wind direction, Ic is the flammability index, Mt is a parameter for DEM, q is sampling angle, ai is a set of three coefficients that sum of them is equal to 1 and shows the relative effect of slope, flammability and wind, and finally X and Y are the coordinates of sampling vertex.

Gis developmentModels for Simulation

Fire spread after 1 and 2 hours predicted by polygonal model , when wind velocity is severe.

Fire spread after 1 and 2 hours predicted by polygonal model , when wind velocity is not severe.

Gis developmentModels for SimulationPolygonal model

ADVANTAGES:•This is most accurate model.•It takes more information like starting point, wind velocity, direction of wind, flammability.

DISADVANTAGES:•The value of sampling angle is not obvious effect of DEM and flammability index is average or determination of correct value for is very difficult if not impossible and even if not determine it will not be correct after any changes in environment situation.

Gis developmentModels for SimulationNetwork model

•This model uses a grid-based DEM and considers burning area as cells in a raster network.• Each burning cell has a burning period and in this period emits heat to its adjacent cells (four cells which have common edge with it).• Also each cell has a flammability degree and if a cell receives more energy than its degree of flammability, it will begin to burn. •So the process of burning continues until no cell is left for burning.•The importance of this model is that it considers individual cells and follows the process of burning.

Gis developmentModels for SimulationNetwork model

ADVANTAGES:•It consider individual cell and follows the process of burning.

DISADVANTAGES:•It takes just few parameters which are not enough such as topography,velocity,direction of wind are negleted.

Gis developmentModels for SimulationImplemented model (Normal model)

fire life in a cell is assumed to follow a normal PDF curve. During fire life, a burning cell emits heat to its neighbouring cells. If the received heat by a cell is more than its degree of flammability,

it begins to burn and this process goes go.

Input Data Main information layers in this model are: DEM and index of

flammability. DEM is used in grid form. Index of flammability or combustibility is a

map. Wind velocity and direction are two other main parameters in this

model.

Gis developmentModels for Simulation

Algorithm1. Capturing and setting parameters 2. Loading DEM and index of flammability 3. Calculating normal vector for the whole cells 4. Acquisition of fire starting point 5. Performing main fire loop up to the end of burning 6. Illustration of the fire spread prediction 7. Providing statistical information about fire

Gis developmentModels for SimulationAlgorithmThe main part of this algorithm is fire loop which work as following: This loop becomes active when the fire starts and becomes inactive when the

fire stops. The input for this loop is the fire starting point and as a function of time

calculates the amount of heat for the burning cell according to the normal cure. Meanwhile, the heat of the burning cell is emitted to the adjacent cells and if

the received heat is more than the degree of flammability, adjacent cells start to burn too.

Cells adjacent to one or more burning cells receive heat continuously but do not absorb all of the received heat. Some of the received heat is continuously lost.

Temperature of a burning cell, value of heat transfer to the adjacent cells and value of heat loss are all depended on some factors which are set by parameters.

Fire loop continues till no burning cell exists. After the loop is over, the cells are mainly divided into two categories: burnt and not burnt.

Gis developmentFire Decision Support Tools

Increasing Situational Awareness and Providing Firefighter SafetyResponse

• Where is the fire located?• What is the best way to access the fire?• What is the terrain and fuel type?• Where are the evacuation routes?• What are the hazards to responding units?• What are the values at risk?• Whose jurisdiction is the incident within?

Gis developmentFire Decision Support Tools

Recovery Rapid and accurate

damage assessment Using GIS integration

platforms for the collection, analysis, and

display of various types of postincident

data Can collect accurate

damageinformation from the field.

Gis developmentFire Decision Support Tools

The GIS map provides an overall viewof damage and recovery needs withlocation-specific photos and reportsincluding• Severity of damage to buildings• Status of infrastructure and utilities• Condition of landscapes• Impact on natural resources

Gis development Simulation of a forest fire is a real challenge. For example velocity and direction of the wind can vary

continuously but real time determination of these variations is almost impossible.

On the other hand, the combined effect of wind and topography can not be easily determined.

More assessment on the relative effect of the fire parameters is one of the requirements of this model in the future. In case a real forest fire record exists, setting coefficients with artificial neural networks seems to be appropriate.

Also because of the similar effect of fire in all directions, one can use a network with hexagonal cells instead of square ones.

Conclusion