Dark-object subtraction atmosphere correction for water body information extraction in Zhuhai-1 hyperspectral imagery

IF 3.7 3区 地球科学 Q2 ENVIRONMENTAL SCIENCES
Yu Guo , Ruru Deng , Yan Yan , Jiayi Li , Zhenqun Hua , Jing Wang , Yuming Tang , Bin Cao , Yeheng Liang
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引用次数: 0

Abstract

The atmospheric correction of hyperspectral data stands as a fundamental step in quantitative applications, crucial for the accurate analysis of hyperspectral information. Zhuhai-1 hyperspectral data, characterized by its high spatial and spectral resolution, holds substantial potential and advantages for the quantification of water body information. Nonetheless, the adoption of more precise physical models for atmospheric correction often demands extensive satellite and ground environmental parameters, which pose practical challenges in applying physical models The Dark Object Subtraction (DOS), leveraging the intrinsic spectral characteristics of the imagery, offers an efficient alternative for achieving improved atmospheric correction results tailored to the data and study area. In this context, this study presents a Dark Object Subtraction for Water body information extraction (DOSW), specifically designed to advance the quantification of water body information in Zhuhai-1 hyperspectral data. The proposed method is rigorously evaluated by comparing the correction results from the Foshan region and Feilaixia Reservoir with standard and measured spectra of typical objects. The results demonstrate the accuracy of DOSW in atmospheric correction, with correlation coefficients exceeding 0.7 when compared to standard spectra for three representative objects. Notably, DOSW achieves exceptional accuracy in water body correction, achieving a correlation coefficient of 0.95 and an RMSE of 0.002 in the Feilaixia Reservoir, and a correlation coefficient of 0.72 and an RMSE of 0.005 in the Foshan region. Overall, the results underscore the efficacy of DOSW in accurately addressing atmospheric correction challenges to Zhuhai-1 hyperspectral data, effectively meeting the requirements of hyperspectral quantification applications.

珠海一号高光谱图像中水体信息提取的暗物减影大气校正
高光谱数据的大气校正是定量应用的基本步骤,对于高光谱信息的准确分析至关重要。珠海一号高光谱数据具有空间和光谱分辨率高的特点,在量化水体信息方面具有巨大的潜力和优势。然而,采用更精确的物理模型进行大气校正往往需要大量的卫星和地面环境参数,这给物理模型的应用带来了实际挑战。在此背景下,本研究提出了一种水体信息提取暗物减法(DOSW),专门用于推进珠海一号高光谱数据中水体信息的量化。通过将佛山地区和飞来峡水库的校正结果与典型物体的标准光谱和实测光谱进行比较,对所提出的方法进行了严格评估。结果证明了 DOSW 在大气校正方面的准确性,与三个代表性物体的标准光谱相比,相关系数超过 0.7。值得注意的是,DOSW 在水体校正方面的精度也非常高,在飞来峡水库的相关系数为 0.95,有效误差为 0.002;在佛山地区的相关系数为 0.72,有效误差为 0.005。总之,研究结果表明,DOSW 能够准确地解决珠海一号高光谱数据所面临的大气校正难题,有效地满足了高光谱定量应用的要求。
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来源期刊
CiteScore
8.10
自引率
0.00%
发文量
85
审稿时长
48 weeks
期刊介绍: The Egyptian Journal of Remote Sensing and Space Sciences (EJRS) encompasses a comprehensive range of topics within Remote Sensing, Geographic Information Systems (GIS), planetary geology, and space technology development, including theories, applications, and modeling. EJRS aims to disseminate high-quality, peer-reviewed research focusing on the advancement of remote sensing and GIS technologies and their practical applications for effective planning, sustainable development, and environmental resource conservation. The journal particularly welcomes innovative papers with broad scientific appeal.
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