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Burned area mapping with MERIS post-fire image

机译:带有MERIS射击后图像的燃烧区域映射

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摘要

MERIS (Medium Resolution Imaging Spectrometer) offers a good balance between spectral, temporal and spatial resolution for mapping burned areas at a regional scale. In this article MERIS images were used to map fire-affected areas in the north-west of Spain, where extensive burning occurred in the summer of 2006. MERIS spectral indices and their ability to discriminate burned area signals have been assessed in this article. Additionally, the potentials of the spectral angle images (SAI) for mapping fire-affected areas were explored. SAI was used to measure the differences between pixels and reference spectra. The reference spectra were obtained from pure burned pixels in the image as well as from field spectral measurements. The MERIS burned area maps were then validated with visually digitized fire perimeters, produced from Advanced Wide Field Sensor, with 60 m pixel size. The Pareto boundary method was used to evaluate the errors from the error matrix, taking into account the spatial resolution of the sensor. This made it possible to discriminate between the errors caused by the spatial resolution and those caused by the limitations of the classification technique. Finally, the Euclidean distance between the errors and the Pareto boundary function was calculated in order to select the best result in an objective way. The ;/ index, a component of the Global Environmental Monitoring Index, showed the best performance among the input indices, with distance values of 3.3 in the fires related to a reference fire polygon; followed by SAI computed from the spectrum obtained from the image with a distance value of 5.7.
机译:MERIS(中分辨率成像光谱仪)在光谱,时间和空间分辨率之间实现了良好的平衡,可绘制区域范围内的燃烧区域。在本文中,MERIS图像用于绘制西班牙西北部受火灾的地区的地图,该地区在2006年夏季发生了大规模燃烧。本文评估了MERIS光谱指数及其区分燃烧区域信号的能力。此外,探索了光谱角度图像(SAI)用于绘制受灾地区的潜力。 SAI用于测量像素和参考光谱之间的差异。参考光谱是从图像中的纯烧像素以及现场光谱测量获得的。然后,使用高级宽视场传感器产生的视觉数字化火圈,对60米像素大小的MERIS燃烧区域图进行验证。考虑到传感器的空间分辨率,使用帕累托边界法评估误差矩阵中的误差。这使得可以区分由空间分辨率引起的误差和由分类技术的局限性引起的误差。最后,计算误差与帕累托边界函数之间的欧几里得距离,以便客观地选择最佳结果。 ; /指数是全球环境监测指数的组成部分,在输入的指数中表现最佳,与参考火灾多边形相关的火灾中距离值为3.3。然后是SAI,该SAI是从距离值为5.7的图像光谱中计算出来的。

著录项

  • 来源
    《International journal of remote sensing 》 |2011年第16期| p.4175-4201| 共27页
  • 作者单位

    Department of Geography, University of Alcala, Calle Colegios 2, 28801 Alcala de Henares, Spain;

    Institute of Economics, Geography and Demography, Spanish Natural Research Council (CSIC), Madrid, Spain;

    Department of Geography, University of Alcala, Calle Colegios 2, 28801 Alcala de Henares, Spain;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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