Paper
8 March 2018 The investigation of identifying method on grass fire by FY-3 VIRR images
Author Affiliations +
Proceedings Volume 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 106110E (2018) https://doi.org/10.1117/12.2285292
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
Abstract
Grassland fire has the characteristics of fierce fire and rapid spreading, and many fires occur in sparsely populated places. Satellite remote sensing has the characteristics of fast imaging period and wide coverage, and plays an important role in the rapid monitoring and evaluation of grassland fire. FY-3 satellite has been widely used since its launch in September 2008, and this paper uses the fire information of Gansu grassland from 2011 to 2016, based on the more mature MODIS and NOAA-AVHRR fire identification method. The results show that the accuracy of FY-3/VIRR satellite data fire detection are higher than that of NOAA-AVHRR satellite, and the accuracy of FY-3/VIRR satellite data is described. There is a greater improvement, the ability to identify slightly worse than the MODIS satellite, the region is relatively large fire detection accuracy is higher.
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Youyan Jiang, Tao Han, and Dawei Wang "The investigation of identifying method on grass fire by FY-3 VIRR images", Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 106110E (8 March 2018); https://doi.org/10.1117/12.2285292
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KEYWORDS
Satellites

MODIS

Vegetation

Satellite imaging

Clouds

Remote sensing

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