Inter-class variance based MODIS forest fire point detection method

Abstract

The invention provides an inter-class variance MODIS forest fire point detection method, which comprises the following steps: pretreating original data required from an MODIS satellite receiving station, acquiring brightness temperature or reflectivity of each channel, and excluding illegal data; identifying image elements of cloud and water; identifying a smog mask; extracting potential fire points from excluded image elements of the cloud, the water and the illegal data; calculating inter-class variance yield of each potential fire point and effective background image elements in a background window; verifying fire points according to the threshold value of the inter-class variance and the smog mask; and outputting an MODIS image containing the fire points. By adopting lower threshold value, the potential fire points comprise true fire points as well as comprise certain false fire points of which the underlying surfaces have higher temperature so as to avoid omission; the threshold value of the inter-class variance is adopted to judge and remove the false fire points so as to prevent from being misjudged; moreover, information of the underlying surfaces around the fire points is considered fully, so that the method can adapt to different areas and seasons.

Description

technical field [0001] The invention relates to the field of fire science, in particular to a fire detection technology. Background technique [0002] Forest fire is a worldwide natural disaster, which has been paid more and more attention by governments of various countries. Satellite remote sensing technology provides effective means for real-time monitoring, positioning and post-disaster assessment of forest fires. The Moderate Resolution Imaging Spectroradiometer (MODIS), which is widely used in Earth observation satellites, has 36 spectral channels, covering the range from visible light to far-infrared bands, and is more sensitive to high temperature on the surface. The AVHRR data are then used as primary data for forest fire monitoring. The basic principle of detecting fire spots based on MODIS data is to use the brightness temperature of the 4 μm and 11 μm bands (that is, the 21st and 31st channels in the MODIS data), according to the difference between the backgrou...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to at least solve one of the above-mentioned technical defects, especially solve the problems of false positives, false negatives and poor adaptability in different regions and seasons

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