Automatic steppe burn scar detection method based on MODIS data

A technology of scars and fires, applied in the field of automatic detection of grassland fire scars using MODIS data, can solve the problems of lag in grassland fire research, immature fire scars, and unclear spectral properties of fire scars. , the effect of accurate extraction

Inactive Publication Date: 2008-08-13
INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI
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Problems solved by technology

But in general, the current research on extracting fire traces using single-day remote sensing data is not mature enough, mainly because the spectral properties of fire traces of different vegetation cover types are not clear enough
In addition, most of the remote sensing monitoring researches on fires are carried out in forest areas, while the research on grassland fires is relatively lagging behind.

Method used

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  • Automatic steppe burn scar detection method based on MODIS data
  • Automatic steppe burn scar detection method based on MODIS data
  • Automatic steppe burn scar detection method based on MODIS data

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Embodiment

[0043] The present invention uses the fire point detection method provided by the MODIS fire product to extract the fire point. This algorithm combines the advantages of the multi-band fixed threshold and background threshold algorithms. Using the brightness temperature of MODIS around 4 μm and 11 μm, T 4 and T 11 express. T 4 Calculated from band 21 and band 22, where the saturation value of band 21 is 500K, and the saturation value of band 22 is 331K. Since band 22 is less noisy (Table 1), try to use band 22 to calculate T 4 , if T 4 >331, switch to band 21. T 11 Calculated from band 31, its saturation value is 400K. For daytime MODIS data, the fire point pixel must meet at least one of the following conditions:

[0044] a.T 4 >360K or

[0045] b.{T 4 >mean(T 4 )+3SD(T 4 ) or T 4 >330K} and (3)

[0046] {T 4 -T 11 >median(T 4 -T 11 )+3SD(T 4 -T 11 ) or T 4 -T 11 >25K}

[0047] where mean, median and SD represent the mean, median and standard deviati...

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Abstract

The invention discloses a MODIS data self-detection method of grassland fire hazard land, which comprises the following steps: MODIS data receiving step from satellite, fire hazard land index GEMI-B construction step, fire point detection step, point sequence step, comparison step. If the comparison result doesn't approximate the statistic feature value, the data removes from the seed point sequence; if approximates, the data spreads outsides at the center of land pixel and adds the pixel into the seed sequence, which is removed from the seed point sequence. If the seed point quantity is not zero, the operation returns to the comparison step; if zero, the operation precedes the land image output step.

Description

technical field [0001] The invention relates to a method for detecting grassland fire traces using MODIS (Moderate Resolution Imaging Spectrometer) data, in particular to a method for automatically detecting grassland fire traces using MODIS data. Background technique [0002] Wild fire is a natural phenomenon in the process of ecosystem succession, but it also has a serious impact on regional ecosystems and the global climate system. The performance is as follows: (1) The burning of plants emits a large amount of greenhouse gases (CO 2 , CO, CH 4 , NO x etc.) and aerosols, which not only change the chemical composition of the atmosphere, but also may directly affect the radiation balance and the global climate system; (2) destroy the production function of the regional ecosystem, resulting in the reduction of animal habitats and biodiversity; (3) change the vegetation Succession patterns and biotrophic cycles. In view of the important role of fire scars in ecosystem man...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/48G01S17/89
Inventor 陈晋陈仲新谭明艳王利民曹鑫
Owner INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI
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