改进的'清水'大气校正算法在Landsat-5传感器中的应用

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"A simple “clear water” atmospheric correction algorithm for Landsat-5 sensors" 这篇研究文章介绍了一种针对Landsat-5传感器的简单大气校正算法，称为改进型“清澈水体”大气校正算法（Improved Clear Water Algorithm for Broad-band sensors, 简称ICAB算法）。大气校正是遥感图像处理中的关键步骤，旨在消除大气条件对地表反射率的影响，以准确获取地表特征信息。在ICAB算法中，研究者利用查找表方法估计了在三个可见光波段和一个近红外（NIR）波段的瑞利散射贡献。瑞利散射是大气中存在的气体分子对光线的散射现象，尤其是在短波段影响显著。此外，他们运用“清澈水”方法来估算NIR波段与气溶胶散射相关的遥感反射率。气溶胶是大气中的悬浮颗粒物，对遥感图像的准确性有显著影响。接下来，研究者采用了安格尔斯特龙指数模型（Angstrom Exponential Model）将NIR波段的气溶胶散射贡献外推到可见光波段。这个模型常用于描述气溶胶粒子大小分布对散射光强的影响。他们还建立了一个创新的实证光谱关系，即485nm波长与560nm波长之间的关系，以估计安格尔斯特龙指数模型的指数系数。通过在中国太湖进行的案例研究，结果显示ICAB算法计算出的光谱特性在形状和幅度上与典型的水体光谱相当接近。不过，该算法在三个可见光波段和NIR波段的不确定性分别为7.45%，10.57%，13.51%和17.14%。这些不确定性值表明，尽管ICAB算法在大气校正方面取得了良好效果，但仍有改进的空间。 ICAB算法为Landsat-5传感器的数据处理提供了一种有效的方法，有助于提高地表反射率的精度，特别是在水体监测和环境分析等领域。该算法的成功应用依赖于对大气条件、瑞利散射和气溶胶散射的精确建模，以及对安格尔斯特龙指数的有效估算。尽管存在一定的误差，但ICAB算法仍为大气校正提供了实用且相对简单的解决方案。

4 J. Chen et al.

120.4º E120.2º E120º E

120.4º

120.2º E

Taihu Lake

120º E

31º N 31.2º N 31.4º N

31º

N 31.2º N 31.4º N

Figure 1. Transects of R

(TM2) at ﬁve synchronous ﬁeld stations.

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COLOUR

FIGURE

using the Environment for Visualizing Images (ENVI) image processing software. The

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pixels associated with R

(TM2) around ﬁve synchronous ﬁeld stations were selected; the

corresponding transects are shown in Figure 1. It was found that the R

(TM2) around the

ﬁeld station was very uniform, which also supports the authors’ previous determination in

135

bio-optical experiments that the observation sites of a validation data set should be chosen

in a large area in which a generally homogeneous water colour exists.

2.3. Field measurements

The ﬁeld measurements of three data sets were performed from 10:00 to 14:00 local time.

At each station, normalized water-leaving reﬂectance measurements were recorded from a

140

boat. The reﬂectance was measured with a spectroradiometer with 5

◦

ﬁbre-optic, covering

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the spectral range of 350–2500 nm (Spectral Devices, Boulder, CO, ASD). Although data

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were collected in the range of 350-2500 nm, with a spectral resolution of 3 nm (full width

at half-maximum, FWHM) and a 1.4 nm sampling interval for the 350-1050 nm spectral

range (ASD 1999), the main data used in this study were those in the range of 400-900 nm,

145

which is the generally used wavelength for water colour remote sensing (Deng and Li 2003;

Gons, Auer, and Efﬂer 2008; Ouaidrai and Vermote 1999). During the recording of the

measurements, the tip of the optical ﬁbre was kept ∼1 m above the water surface by means

of a 3 m long, hand-held black pole. Radiance of both the water surface (L

(λ)) and a

standard grey board (L

(λ)) was measured (λ is the wavelength). Ten curves were acquired 150

for each target. In order to effectively avoid the interference of the ship with the water

surface and the inﬂuence of direct solar radiation, the instrument was positioned at an

angle β of 90–135

◦

to the plane of the incident radiation and away from the Sun, as shown

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in Figure 2 (Mueller et al. 2003; Mueller and Fargion 2002). The viewing angle of the water

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surface, α, was controlled between 30

◦

and 45

◦

with the ver tical direction. In this way most

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155

of the direct sunlight was eliminated while the impact of the ship’s shadow was minimized

(Mueller et al. 2003; Mueller and Fargion 2002). Immediately after measuring the water

radiance, the spectroradiometer was rotated upwards by 90

◦

–120

◦

to measure skylight. The

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