Improving the prediction of wildfire potential in boreal Alaska with satellite imaging radar
Alaska currently relies on the Canadian Fire Weather Index (FWI) System for the assessment of the potential for wildfire and although it provides invaluable information it is designed as a single system that does not account for the varied fuel types and drying conditions (day length, permafrost, decomposition rate, and soil type) that occur across the North American boreal forest. The FWI System is completely weather-based using noontime measurements of precipitation, relative humidity, temperature and wind speed. The most common problem observed with the FWI system is in the initialisation and need for calibration of one of the moisture codes that make up the FWI system, the Drought Code (DC), which is representative of the deeper organic soil layers and has a 53 day lag period. SAR data represent an innovative tool to improve the current weather-based fire danger system of interior Alaska by initialising the spring values of DC, calibrating the codes throughout the season and providing additional point-source data. Using radar backscatter values from several recently burned boreal forests, an algorithm was developed that related backscatter to DC. The authors then demonstrated the application and validation of this algorithm at independent test sites with good correlation to in situ soil moisture and rainfall variations.
Improving the prediction of wildfire potential in boreal Alaska with satellite imaging radar.
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© 2007 Cambridge University Press. Publisher's version or record: http://dx.doi.org/10.1017/S0032247407006535