Zhao Zhi-qiang, Li Ai-nong, Bian Jin-hu, Huang Cheng-quan
Guang Pu Xue Yu Guang Pu Fen Xi. 2015 Jun;35(6):1479-87.
Domestic HJ CCD imaging applications in environment and disaster monitoring and prediction has great potential. But, HJ CCD image lack of Mid-Nir band can not directly retrieve Aerosol Optical Thickness (AOT) by the traditional Dark Dense Vegetation (DDV) method, and the mountain AOT changes in space-time dramatically affected by the mountain environment, which reduces the accuracy of atmospheric correction. Based on wide distribution of mountainous dark dense forest, the red band histogram threshold method was introduced to identify the mountainous DDV pixels. Subsequently, the AOT of DDV pixels were retrieved by lookup table constructed by 6S radiative transfer model with assumption of constant ratio between surface reflectance in red and blue bands, and then were interpolated to whole image. MODIS aerosol product and the retrieved AOT by the proposed algorithm had very good consistency in spatial distribution, and HJ CCD image was more suitable for the remote sensing monitoring of aerosol in mountain areas, which had higher spatial resolution. Their fitting curve of scatterplot was y = 0.828 6x-0.01 and R2 was 0.984 3 respectively. Which indicate the improved DDV method can effectively retrieve AOT, and its precision can satisfy the atmospheric correction and terrain radiation correction for Hj CCD image in mountainous areas. The improvement of traditional DDV method can effectively solve the insufficient information problem of the HJ CCD image which have only visible light and near infrared band, when solving radiative transfer equation. Meanwhile, the improved method fully considered the influence of mountainous terrain environment. It lays a solid foundation for the HJ CCD image atmospheric correction in the mountainous areas, and offers the possibility for its automated processing. In addition, the red band histogram threshold method was better than NDVI method to identify mountain DDV pixels. And, the lookup table and ratio between surface reflectance between red and blue bands were the important influence factor for AOT retrieval. These will be the important research directions to further improve algorithm and improve the retrieve accuracy.
国产HJ CCD影像在环境与灾害监测及预报中的应用潜力巨大。但是，HJ CCD影像缺乏中红外波段，无法采用传统的暗密植被（DDV）方法直接反演气溶胶光学厚度（AOT），且山区AOT在时空上受山地环境影响变化剧烈，降低了大气校正的精度。基于山区暗密森林分布广泛的特点，引入红波段直方图阈值法来识别山区DDV像元。随后，在假设红、蓝波段地表反射率比值恒定的情况下，利用6S辐射传输模型构建查找表反演DDV像元的AOT，并将其插值到整幅影像。MODIS气溶胶产品与本文算法反演得到的AOT在空间分布上具有很好的一致性，HJ CCD影像更适合山区气溶胶的遥感监测，其空间分辨率更高。它们的散点拟合曲线分别为y = 0.828 6x - 0.01和R2 = 0.984 3。这表明改进后的DDV方法能有效反演AOT，其精度能够满足山区HJ CCD影像的大气校正和地形辐射校正。传统DDV方法的改进有效解决了HJ CCD影像只有可见光和近红外波段在求解辐射传输方程时信息不足的问题。同时，改进后的方法充分考虑了山地地形环境的影响。为山区HJ CCD影像的大气校正奠定了坚实基础，为其自动化处理提供了可能。此外，红波段直方图阈值法在识别山区DDV像元方面优于归一化植被指数（NDVI）法。并且，查找表以及红、蓝波段地表反射率比值是AOT反演的重要影响因素。这些将是进一步改进算法、提高反演精度的重要研究方向。
