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Proceedings of the 16th Conference (November 12-16, 2018, Moscow, Russia)
Methods for Wildfire Spread Prediction and Their Integration With Remote Sensing Data
Sergey A. Khvostikov, Sergey A. Bartalev
Space Research Institute, Russian Academy of Sciences, Moscow, Russia
khvostikov@d902.iki.rssi.ru
DOI 10.21046/rorse2018.42
This short review article presents description of a field of wildfire modelling and use of remote sensing in this field. There are many wildfire models based on various approaches (physical, empirical, mathematical). Development of remote sensing in recent decades provided vast array of data that can be used by wildfire models and can help evaluate their accuracy. Joint use of remote sensing data and wildfire models can help to tune models and increase their accuracy and opens a way to create automatic just-in-time wildfire danger prediction system. Also in last 10 years there was a notable development in methods of remote sensing data assimilation into wildfire models, which leads to better estimation of wildfire state and higher accuracy of forecast.
Keywords: wildfires, fire spread modelling, remote sensing, data assimilation
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Section 1. Methods of modeling various phenomena focused on assimilation of remote sensing data
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