Remote Sensing in Wildfire Management

 

 

 

 

We depend on forests for our survival, from the air we breathe to the wood we use. Besides providing habitats for animals and livelihoods for humans, forests also offer watershed protection, prevent soil erosion and mitigate climate change. Yet, despite our dependence on forests, we are still allowing them to disappear.

 

 

Wildfires can be forest fires, bush fires, grass fires or peat fires. Wildfires are an integral part of so many ecosystems across the world. A wildfire moves at speeds of up to 14 miles an hour, consuming everything—trees, brush, homes, even humans—in its path.

 

 

Fuel, oxygen and heat source are the three basic factors for promoting wild fires. Fuel include any flammable material like, trees, grasses, brush, even homes. Air supplies the oxygen needed to burn and heat source help spark the wild fire. Lightning, burning campfires or cigarettes, hot winds, and even the sun can all provide sufficient heat to spark a wildfire.

 

 

Remote sensing as optical, thermal, hyper spectral, active and passive microwave is used in various ways to analyse the wildfires and to mitigate its effects.

 

 

A complete prevention of the wildfires is not possible but it is possible to reduce the damage by consulting forest fire risk map. These maps are created using satellite imageries. They include elevation range, average elevation, slope range and the kind of vegetation that occur in study area. Inputs that are used to create such maps include forest vegetation structures, topographic features, climatic parameters and forest management maps. 

 

 

In recent decades, satellite based remote sensing is widely used to study fire danger. This system is adopted as it acquire imageries continuously in the remote areas. These images are processed in different ways and methods to create some indexes. Fire potential index (FPI) is created based on Relative Greenness (RG) and Normalized Difference Vegetation Index (NDVI). This is used to determine distribution of three fire related components – total number of fires, total fires with specific size and probability of those fires which has a certain size. Enhanced Vegetation Index (EVI) and daily surface temperature are used for predict fire danger conditions.

 

 

The estimation of forest Fuel Moisture Content (FMC) is important for predicting forest fire danger. With    use of remote sensing sensors, it is possible to retrieve vegetation water content. The spectral features in reflectance spectra of green vegetation in 1300–2500 nm regions are mainly dominated by the liquid water absorption. Normalized Difference Water Index (NDWI) has potential applicability for FMC detection.

 

 

Several pre-fire conditions can be monitored using remote sensing. The first one is related to the fuel type, which can be mapped, like classical vegetation mapping, from high spatial resolution optical or radar images. These maps can then be linked, within a wildfire threat analysis system. 

 

GPS data with GIS is used to rapidly get crucial information about the location under fire. Tactical response planning in an urban setting requires street network data, information on hazardous materials locations, and pre-fire survey information such as floor plans or hydrant location and capacity data. These kind of data are available in the form of a GIS.

 

 

We depend on forests for our survival, from the air we breathe to the wood we use. Wildfires can be forest fires, bush fires, grass fires or peat fires. Wildfires are an integral part of so many ecosystems across the world. Remote sensing is playing its vital role in analysing, predicting, forecasting and fighting the wildfire.