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在多光谱遥感图像中对水体进行多尺度放射性稳定性分析.

Yanze Yang1, Xiankun Ge1, Jingjing Chen1

  • 1School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Hefei 230009, China.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
概括

在水域遥感中进行空间重新采样可以引入放射测量不确定性. 节流再采样提供了卓越的放射性稳定性,并保留了不同尺度的水辐射特征.

科学领域:

  • 环境遥感 环境遥感
  • 水上光学 水上光学
  • 放射测量是一种放射测量.

背景情况:

  • 多传感器数据融合对于环境监测至关重要,需要将空间重新采样到一个共同的尺度.
  • 再抽样可以引入显著的放射性不确定性,特别是在异质的水生环境中,影响数据的准确性.
  • 现有的重新采样方法在尺度转换过程中可能无法充分保持放射性准确度.

研究的目的:

  • 为了评估多尺度水生遥感中的重新采样诱导的放射性不确定性.
  • 与其他方法相比,评估节流再采样的物理优势.
  • 开发基于放射性稳定性的框架,用于评估重新采样技术.

主要方法:

  • 使用Landsat 8 OLI数据作为放射性稳定性的参考.
  • 开发了一个框架来评估使用雷利散射校准的多尺度重新采样方法.
  • 在各种空间尺度中比较了四种重新采样方法.
  • 采用太阳光谱 (6S) 模型中的卫星信号获取规范化的脱水辐射,并与AERONET-OC数据验证.

主要成果:

  • 随着空间尺度的增加,放射测量的一致性会降低.
  • 节流的重新采样显示出更高的放射性稳定性和更好的保存水辐射.
关键词:
节约流量的重新采样辐射稳定性的放射性稳定性雷利散射 雷利散射 雷利散射空间尺度转换的变化

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  • 拟议的框架有效评估了重新采样方法,并突出了依赖规模的不确定性.

    • 结论:

    • 节流的重新采样对于在多尺度水域遥感中保持放射学准确性至关重要.
    • 开发的框架为评估数据融合和定量反转中的重新采样方法提供了可靠的参考.
    • 仔细选择重新采样技术对于使用遥感数据进行准确的环境监测至关重要.