华东师范大学学报(自然科学版) ›› 2017, Vol. 2017 ›› Issue (6): 136-146.doi: 10.3969/j.issn.1000-5641.2017.06.013

• 地理学 • 上一篇    下一篇

GF-1 WFV与Landsat-8 OLI和Sentinel-2A MSI遥感图像光谱信息转换研究

杨天鹏1,2, 闫文佳1,2, 张远1,2   

  1. 1. 华东师范大学 地理信息科学教育部重点实验室, 上海 200241;
    2. 华东师范大学 地理科学学院, 上海 200241
  • 收稿日期:2017-01-13 出版日期:2017-11-25 发布日期:2017-11-25
  • 通讯作者: 张远,男,博士,副教授,研究方向为生态遥感.E-mail:yzhang@geo.ecnu.edu.cn E-mail:yzhang@geo.ecnu.edu.cn
  • 作者简介:杨天鹏,男,硕士研究生,研究方向为GIS与遥感应用.E-mail:932032777@qq.com.
  • 基金资助:
    国家自然科学基金（41571410）；上海市自然科学基金（15ZR1411800）

Conversion study on multi-spectral information of remote sensing images GF-1 WFV, Landsat-8 OLI and Sentinel-2A MSI

YANG Tian-peng1,2, YAN Wen-jia1,2, ZHANG Yuan1,2   

  1. 1. Key Laboratory of Geographic Information Science(Ministry of Education), East China Normal University, Shanghai 200241, China;
    2. School of Geographic Sciences, East China Normal University, Shanghai 200241, China
  • Received:2017-01-13 Online:2017-11-25 Published:2017-11-25

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摘要： 地表环境的宏观动态监测研究中，受卫星回归周期及天气的影响，单颗卫星难以获取长期、连续的光学遥感数据，因此，定量分析多平台遥感数据的光谱信息关系是十分必要的.本研究基于两组同日过境的无云卫星影像（GF-1与Landsat-8和Sentinel-2A），结合地面调查数据，进行了不同传感器影像间对应波段的光谱信息对比，并通过统计回归分析获得了两组卫星对应波段（蓝、绿、红和近红外）的反射率转换方程.研究结果显示，GF-1与Landsat-8和GF-1与Sentinel-2A对应波段的反射率都具有很强的相关性，得到的转换方程能够对上述三种卫星数据间对应波段的光谱信息实现高精度的转换.本研究能够实现同日多光谱遥感数据的光谱信息转换及协同应用，并为区域资源环境的长期定量遥感监测提供技术支持.

关键词: GF-1, Landsat-8, Sentinel-2A, 遥感, 传感器, 反射率, 转换方程

Abstract: Owing to the restrictions in weather conditions and revisit cycle of satellites, single satellite can't successively acquire effective optical RS data for long-term monitoring the terrestrial environments. Therefore, it is crucial important to analyze the multi-spectral information of multi-source RS data. In this study, two groups of clear RS images (GF-1 and Landsat-8, GF-1 and Sentinel-2A), in along with ground survey data, were respectively acquired on identical date. Four bands, blue, green, red and near infrared (NIR), were selected to compare their spectral characteristics. At the same time, conversion equation for reflectance of four corresponding spectral bands was derived respectively via statistical regression method. The result shows that each pair of bands in the two comparing groups has a strong correlation. And, these conversion equations can effectively converse spectral information in between each band of two comparing groups with a better precision. This study provides a useful technological approach for the identical date information integration and syngeneic application of multi-spectral RS data from the same day, as well as quantitatively monitoring the long-term dynamics in environments and resources at regional scale.

Key words: GF-1, Landsat-8, Sentinel-2A, remote sensing, sensor, reflectance, conversion equation

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