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Acta Optica Sinica, Volume. 44, Issue 8, 0828001(2024)

Nighttime Tiny Fire Recognition Algorithm by Joint Low-Light-Assisted Infrared Remote Sensing Data

Hui Liu1, Yuqing He1、*, Xiuqing Hu2,3、**, and Chunli Sun1
Author Affiliations
  • 1Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
  • 2Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China
  • 3Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China
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    Flow chart of FRJLI algorithm

    Fig. 1. Flow chart of FRJLI algorithm

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    Scatter diagram of fusion urban light radiation value and NOAA light radiation value in February 2022

    Fig. 2. Scatter diagram of fusion urban light radiation value and NOAA light radiation value in February 2022

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    Data before and after fire point pretreatment in Republic of Korea on March 5, 2022. (a) Brightness temperature diagram before pretreatment; (b) monthly fusion diagram of urban light; (c) brightness temperature diagram after pretreatment

    Fig. 3. Data before and after fire point pretreatment in Republic of Korea on March 5, 2022. (a) Brightness temperature diagram before pretreatment; (b) monthly fusion diagram of urban light; (c) brightness temperature diagram after pretreatment

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    Pixel screening results. (a) Potential fire pixel recognition results; (b) recognition results by joint algorithm

    Fig. 4. Pixel screening results. (a) Potential fire pixel recognition results; (b) recognition results by joint algorithm

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    Recognition results of fire points at night. (a) Republic of Korea, 2022-03-04T01:48; (b) Republic of Korea, 2022-03-05T03:06; (c) Republic of Korea, 2022-03-06T02:48; (d) Republic of Korea, 2022-03-07T02:30; (e) Republic of Korea, 2022-03-08T02:12; (f) Republic of Korea, 2022-03-09T01:54; (g) Republic of Korea, 2022-03-10T01:36; (h) Republic of Korea, 2022-03-11T02:54; (i) Republic of Korea, 2022-03-12T02:36; (j) Republic of Korea, 2022-03-13T02:18; (k) Mongolia, 2022-04-18T01:24; (l) Mongolia, 2022-04-18T03:00; (m) Mongolia, 2022-04-19T01:00; (n) Mongolia, 2022-04-19T02:42

    Fig. 5. Recognition results of fire points at night. (a) Republic of Korea, 2022-03-04T01:48; (b) Republic of Korea, 2022-03-05T03:06; (c) Republic of Korea, 2022-03-06T02:48; (d) Republic of Korea, 2022-03-07T02:30; (e) Republic of Korea, 2022-03-08T02:12; (f) Republic of Korea, 2022-03-09T01:54; (g) Republic of Korea, 2022-03-10T01:36; (h) Republic of Korea, 2022-03-11T02:54; (i) Republic of Korea, 2022-03-12T02:36; (j) Republic of Korea, 2022-03-13T02:18; (k) Mongolia, 2022-04-18T01:24; (l) Mongolia, 2022-04-18T03:00; (m) Mongolia, 2022-04-19T01:00; (n) Mongolia, 2022-04-19T02:42

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    False color image at night. (a) Republic of Korea, 2022-03-04T01:48; (b) Republic of Korea, 2022-03-05T03:06; (c) Republic of Korea, 2022-03-06T02:48; (d) Republic of Korea, 2022-03-07T02:30; (e) Republic of Korea, 2022-03-08T02:12; (f) Republic of Korea, 2022-03-09T01:54; (g) Republic of Korea, 2022-03-10T01:36; (h) Republic of Korea, 2022-03-11T02:54; (i) Republic of Korea, 2022-03-12T02:36; (j) Republic of Korea, 2022-03-13T02:18; (k) Mongolia, 2022-04-18T01:24; (l) Mongolia, 2022-04-18T03:00; (m) Mongolia, 2022-04-19T01:00; (n) Mongolia, 2022-04-19T02:42

    Fig. 6. False color image at night. (a) Republic of Korea, 2022-03-04T01:48; (b) Republic of Korea, 2022-03-05T03:06; (c) Republic of Korea, 2022-03-06T02:48; (d) Republic of Korea, 2022-03-07T02:30; (e) Republic of Korea, 2022-03-08T02:12; (f) Republic of Korea, 2022-03-09T01:54; (g) Republic of Korea, 2022-03-10T01:36; (h) Republic of Korea, 2022-03-11T02:54; (i) Republic of Korea, 2022-03-12T02:36; (j) Republic of Korea, 2022-03-13T02:18; (k) Mongolia, 2022-04-18T01:24; (l) Mongolia, 2022-04-18T03:00; (m) Mongolia, 2022-04-19T01:00; (n) Mongolia, 2022-04-19T02:42

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    NBR data and data difference before and after the fire in Mongolia. (a) NBR data before fire; (b) NBR data after fire; (c) NBR data difference before and after fire

    Fig. 7. NBR data and data difference before and after the fire in Mongolia. (a) NBR data before fire; (b) NBR data after fire; (c) NBR data difference before and after fire

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    Recognition results of fire points in Mongolia after NBR classification. (a) 2022-04-18T01:24; (b) 2022-04-18T03:00; (c) 2022-04-19T01:00; (d) 2022-04-19T02:42

    Fig. 8. Recognition results of fire points in Mongolia after NBR classification. (a) 2022-04-18T01:24; (b) 2022-04-18T03:00; (c) 2022-04-19T01:00; (d) 2022-04-19T02:42

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    Recognition results of proposed algorithm and three other algorithms. (a) FRJLI algorithm; (b) NASA official algorithm; (c) MODIS Collection 4 algorithm; (d) FILDA algorithm

    Fig. 9. Recognition results of proposed algorithm and three other algorithms. (a) FRJLI algorithm; (b) NASA official algorithm; (c) MODIS Collection 4 algorithm; (d) FILDA algorithm

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    Recognition results of four algorithms during the fire in Republic of Korea and Mongolia. (a) Number of fire points during the fire in Republic of Korea; (b) number of fire points during the fire in Mongolia; (c) fire area in Republic of Korea; (d) fire area in Mongolia

    Fig. 10. Recognition results of four algorithms during the fire in Republic of Korea and Mongolia. (a) Number of fire points during the fire in Republic of Korea; (b) number of fire points during the fire in Mongolia; (c) fire area in Republic of Korea; (d) fire area in Mongolia

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    NASA official recognition results for the fire points in Republic of Korea. (a) March 10, 2022; (b) March 11, 2022

    Fig. 11. NASA official recognition results for the fire points in Republic of Korea. (a) March 10, 2022; (b) March 11, 2022

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    Time series diagram of average brightness temperature, average radiance, and number of fire points

    Fig. 12. Time series diagram of average brightness temperature, average radiance, and number of fire points

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    Raw data of the fire in Republic of Korea on 4 March, 2022. (a) Mid-infrared brightness temperature; (b) low light radiance

    Fig. 13. Raw data of the fire in Republic of Korea on 4 March, 2022. (a) Mid-infrared brightness temperature; (b) low light radiance

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    Scatter diagram of infrared brightness temperature and low-light radiation for identifying fire points during the fire in Republic of Korea

    Fig. 14. Scatter diagram of infrared brightness temperature and low-light radiation for identifying fire points during the fire in Republic of Korea

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    Actual distribution of four types of fire points on 6 March, 2022

    Fig. 15. Actual distribution of four types of fire points on 6 March, 2022

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    • Table 1. Relevant parameters of the band for proposed algorithm

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      Table 1. Relevant parameters of the band for proposed algorithm

      BandCentral wavelength /μmWavelength range /μmNadir pixel size along track & cross track /(km×km)Primary application
      M134.053.973-4.1280.742×0.259SST, fires
      M1510.76310.263-11.2630.742×0.776SST
      M1612.01311.538-12.4880.742×0.776Cloud imagery
      DNB0.70.5-0.90.742×0.742Imagery

    • Table 2. Number of fire points identified by FRJLI algorithm at night during Republic of Korea fire and Mongolia fire

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      Table 2. Number of fire points identified by FRJLI algorithm at night during Republic of Korea fire and Mongolia fire

      RegionDateNumber of fire pointsRegionDateNumber of fire points
      Republic of Korea2022-03-04T01：482Republic of Korea2022-03-11T02：5422
      Republic of Korea2022-03-05T03：06111Republic of Korea2022-03-12T02：366
      Republic of Korea2022-03-06T02：4885Republic of Korea2022-03-13T02：183
      Republic of Korea2022-03-07T02：3039Mongolia2022-04-18T01：24160
      Republic of Korea2022-03-08T02：1250Mongolia2022-04-18T03：00177
      Republic of Korea2022-03-09T01：5425Mongolia2022-04-19T01：00884
      Republic of Korea2022-03-10T01：362Mongolia2022-04-19T02：42887
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    Hui Liu, Yuqing He, Xiuqing Hu, Chunli Sun. Nighttime Tiny Fire Recognition Algorithm by Joint Low-Light-Assisted Infrared Remote Sensing Data[J]. Acta Optica Sinica, 2024, 44(8): 0828001

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Dec. 15, 2023

    Accepted: Feb. 2, 2024

    Published Online: Apr. 18, 2024

    The Author Email: He Yuqing (yuqinghe@bit.edu.cn), Hu Xiuqing (huxq@cma.gov.cn)

    DOI:10.3788/AOS231939

    CSTR:32393.14.AOS231939

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology