森林火灾微光遥感识别新方法—增强夜光火灾扰动指数
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沈阳市中青年科技创新人才支持计划(RC210431),风云卫星应用先行计划二期(FY-APP-2021.0302)


A new method for low-light remote sensing identification of forest fires—Enhanced Noctilucent Fire Disturbance Index
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Supported by the Shenyang young and middle-aged scientific and technological innovation talents support program(RC210431), and Feng Yun satellite application advance plan(FY-APP-2021.0302)

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    摘要:

    随着光电技术的发展,低照度条件下的微光成像技术及其应用成为近年来的研究热点之一。在微光遥感影像上,很难单纯依靠辐射亮度或温度,充分地分离森林火灾与工业燃烧、城市热源等,同时由于微光波段频繁的数据饱和问题,目前火灾产品仅提供探测信息。为了在各种高亮度异质热源中实现森林火灾识别,进一步推进火灾探测产品像素级表征,基于地表温度随植被密度增加而降低的原理,以及植被和城市表面呈负相关的程式化事实,提出了一种新的光谱指数—增强夜光火灾扰动指数(ENFDI)。结果表明:ENFDI可以增强森林火灾与城市灯光之间的光谱特征差异,提高微光条件下森林火灾识别能力,森林火灾ENFDI在1.073以上,明显高于城市灯光区域ENFDI(0.840~1.073);它能够有效降低NTL易饱和的影响,ENFDI指数与中远红外亮温差的相关性R高达0.94~0.97,明显高于NTL与中远红外亮温差的相关性(0.82~0.83);ENFDI具有一定的稳定性,它不受月相变化的影响,在有无月光情况下夜间森林火灾均被识别;ENFDI识别的森林火灾与NPP /VIIRS主动火灾产品(VNP14IMG)具有良好的总体对应关系,定位偏差在628 m以内。因此,ENFDI指数对森林火灾的识别具有敏感性、稳定性和准确性,为进一步实现火灾像素级表征提供可行性参考。

    Abstract:

    With the development of optoelectronic technology, low-light-level (LLL) imaging technology and its application have recently become a research focus.In LLL remote sensing images,it is difficult to completely separate forest fires from industrial combustion and urban heat sources based on radiance or temperature alone. Meanwhile,because of frequent data saturation in the low-light band, the existing fire detection products only provide detection information. To identify forest fires among various heterogeneous heat sources with high brightness and further improve the pixel-level characterization of fire detection products, a new spectral index, the enhanced noctilucent fire disturbance index (ENFDI),is proposed based on the principle that surface temperature decreases with the increasing vegetation density and the fact that vegetation and urban surfaces are negatively correlated. According to the results, ENFDI enhances the differences in spectral characteristics between forest fires and city lights and improves the ability of forest fire identification under low-light conditions. The ENFDI of forest fires is greater than1.073, which is considerably higher than that of urban lighting areas (0.840–1.073). This index can also effectively reduce the impact of easy saturation of night-time light (NTL). The correlation (R) between ENFDI and the mid-and far-infrared brightness temperature difference is as high as 0.94–0.97, which is considerably higher than that of NTL (0.82–0.83). Moreover, ENFDI is relatively stable and is not affected by lunar phases; forest fires at night are identified with or without moonlight. The forest fires identified using the ENFDI show a good overall correspondence with the NPP/VIIRS active fire product (VNP14IMG), with a positional tolerance of within 628 m. Therefore, ENFDI is sensitive, stable and accurate for identifying forest fires. Further, it may serve as a feasible reference for achieving further pixel-level characterization of fires.

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  • 收稿日期:2022-08-21
  • 最后修改日期:2022-10-25
  • 录用日期:2022-11-17
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