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Using MODIS land surface temperature to evaluate forest fire risk of northeast China

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2 Author(s)
Quo Guangmeng ; Inst. of Geogr. Sci. & Natural Resource, Chinese Acad. of Sci., Beijing, China ; Zhou Mei

A neural network method was developed with the Moderate-resolution Imaging Spectroradiometer (MODIS) land surface temperature product as training and validation datasets, and it was used to retrieve land surface temperatures (LSTs) from direct-broadcast MODIS data in Northeast China in April and May 2003 before fire events. The result shows that LST increases as the day gets closer to the fire day, and this trend can be observed about three days before the fire day. This is similar to the result of fire potential index, so the LST can also be used to evaluate forest fire risk.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:1 ,  Issue: 2 )