Abstract
GF-4 Satellite Fire Detection With an Improved Contextual Algorithm
Highlights
Landscape combustion fires, including “wild fire” and “active combustion,” widely interfere with the balance of the biological ecological environment [1,2,3,4]
A single threshold condition cannot account for the seasonal changes in land surface temperature, and in some relatively complex areas, the land surface temperature cannot be divided according to the same standard
Considering the influence of simultaneous interpreting of different parameters and different observation conditions on fire point recognition, a series of modified algorithm based on MODIS fire point recognition method is proposed
Summary
Landscape combustion fires, including “wild fire” and “active combustion,” widely interfere with the balance of the biological ecological environment [1,2,3,4]. On the basis of the Contextual Method, Giglio [21,22] proposed an improved method to compensate for the partial condition of sacrificing the information of small fire detection in the contextual algorithm and used the method for fire monitoring based on MODIS data. Considering influencing factors such as direct sunlight, cloud-related effects, and coastal boundaries, the fire point algorithm incorporates cloud removal, desert boundaries, coastal boundaries, and solar flares. The characteristics of GF-4 satellite high-frequency observation provide a good application scenario for the multi-temporal data requirements of this method
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