DocumentCode :
966363
Title :
Using MODIS land surface temperature to evaluate forest fire risk of northeast China
Author :
Guangmeng, Guo ; Mei, Zhou
Author_Institution :
Inst. of Geogr. Sci. & Natural Resource, Chinese Acad. of Sci., Beijing, China
Volume :
1
Issue :
2
fYear :
2004
fDate :
4/1/2004 12:00:00 AM
Firstpage :
98
Lastpage :
100
Abstract :
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.
Keywords :
forestry; program verification; training; AD 2003 4 to 5; Northeast China; fire day; forest fire risk; land surface temperature; moderate-resolution imaging spectroradiometry; validation; Fires; Information retrieval; Land surface; Land surface temperature; MODIS; Neural networks; Ocean temperature; Remote monitoring; Sea surface; Surface morphology;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
Publisher :
ieee
ISSN :
1545-598X
Type :
jour
DOI :
10.1109/LGRS.2004.826550
Filename :
1291390
Link To Document :
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