Can Satellites Save the Landscapes from Burning?

NASA researchers have created a fire forecasting model. The Global Fire Weather Database (GFWED) is very useful to predict fire outcomes. This model incorporates various climatic factors and satellite-based precipitation measurements. 

Can Satellites Save the Landscapes from Burning?
Image: DigitalGlobe

Can Satellites Save the Landscapes from Burning?

Satellites are continuously watching us. They are keeping an eye on our planet day and night. From communication to navigation and from flooding to fires, everything is being tracked. When it comes to vegetation or forest fires, there may be several reasons for it. But the outcome is always devastating and hazardous. A recent example is of massive Australian fires that resulted in the killing of many wild species. Apart from burning trees and loss of lives, there is lots of smoke and pollution in the atmosphere due to fires. 

Fire hazard mapping and forecasting

It is essential to track and monitor the deadly fires. They turn forests into ashes within minutes. They can be very severe depending upon the density of vegetation, the dryness, wind direction, and speed. The climate and weather have an essential role in the spread of fires. For example, if there is no rain for months, the vegetation is likely to be drier. 

Various factors affect the spread of fires. The presence of humidity in the atmosphere, direction, and speed of local winds, temperature, precipitation, etc. are standard terms that are discussed when we talk about the formation of fires. 

Using these factors, NASA researchers have created a fire forecasting model. The Global Fire Weather Database (GFWED) is very useful to predict fire outcomes. This model incorporates various climatic factors and satellite-based precipitation measurements. 

More about model

The model predicts the intensity of the fire in a particular area. It analyses various data sets and produces a rating the same as some firefighting agencies do. 

In the prediction process, historical data is also useful. The fires from the past are studied for the circumstances that result in tragedy. This information, combined with Real-time data helps in predicting the current fire danger. 

GFWED model also uses data from various sources like NASA's MERRA-2 dataset of GMAO( Global Modelling and Assimilation Office), rainfall data from rain-gauge stations, and data from the Integrated Multi-Satellite Retrievals (IMERG). 

Fire Weather Index 

The model uses various weather factors that influence the likelihood of a vegetation fire based on the Fire Weather Index (FWI) system. 

The FWI system developed in Canada integrates three moisture codes and three fire behavior indices. The moisture codes are useful in capturing the moisture content of the generalized fuel classes. The fire behavior indices determine the spread rate and intensity of fire along with the overall fuel consumption. 

Calibration of local fire environment with FWI results in more precise fire danger classification. There are many other techniques too that monitor the spread of fire, such as machine learning algorithms, NBR (Normalized Burn Ratio), and NDVI (Normalized Difference Vegetation Index) from LANDSAT TM/ETM images. 

National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) data are also useful for fire detection. They have a high temporal resolution that helps in detecting fire in remote areas. Forecasting of fire is very crucial to save lives and the environment. Every data is useful when it comes to prevention.