Sentinel-2A与Landsat 8 OLI逐像元辐射归一化方法研究

doi:10.13474/j.cnki.11-2246.2019.0319

测绘通报 ›› 2019, Vol. 0 ›› Issue (10): 61-66.doi: 10.13474/j.cnki.11-2246.2019.0319

Sentinel-2A与Landsat 8 OLI逐像元辐射归一化方法研究

徐玉雯¹, 张浩², 陈正超², 景海涛¹

1. 河南理工大学测绘与国土信息工程学院, 河南焦作 454003;
2. 中国科学院遥感与数字地球研究所数字地球重点实验室, 北京 100094

收稿日期:2019-01-22 修回日期:2019-03-29 出版日期:2019-10-25 发布日期:2019-10-26
通讯作者: 张浩。E-mail:zhanghao612@radi.ac.cn E-mail:zhanghao612@radi.ac.cn
作者简介:徐玉雯(1994-),女,硕士生,主要从事大气校正、辐射归一化方面的研究。E-mail:1277300408@qq.com
基金资助:
国家自然科学基金（41771397）

A case study on pixel-by-pixel radiometric normalization between Sentinel-2A and Landsat 8 OLI

XU Yuwen¹, ZHANG Hao², CHEN Zhengchao², JING Haitao¹

1. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China;
2. Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing 100094, China

Received:2019-01-22 Revised:2019-03-29 Online:2019-10-25 Published:2019-10-26

摘要/Abstract

摘要： 考虑不同传感器光谱响应函数差异及不同地物类型反射率光谱的差异，提出了一种逐像元辐射归一化方法，并以2017年7月17日内蒙古达里诺尔湖地区准同步过境的Sentinel-2A及Landsat 8数据为例，对两类数据可见-近红外波段（VNIR）地表反射率结果进行归一化。首先采用Sen2cor方法及NASA官方提供大气校正算法，分别对Sentinel-2A及Landsat 8 OLI影像进行大气校正并重采样到同一空间分辨率；然后基于光谱库计算匹配因子并构建图像与光谱库之间的匹配转换模型，实现像元尺度上从Sentinel-2影像到Landsat 8影像地表反射率相似波段之间的转换。结果表明，经逐像元归一化的影像相比原始影像及经HLS光谱归一化的影像，与Landsat 8 VNIR波段的相关性明显提高，辐射一致性增强。该转换模型为多源中高分辨率遥感图像高精度辐射归一化提供了新思路。

关键词: 地表反射率, 逐像元辐射归一化, 混合像元分解, 光谱库, HLS

Abstract: Taking the spectral response of different remote sensors and the spectral differences of ground objects into account, this paper presents a pixel-by-pixel radiometric normalization method. The data with similar bands visible-near infrared (VNIR) of Sentinel-2A and Landsat 8 OLI are taken as an example, which are acquired over quasi-simultaneously in Gudarinor Lake area of Inner Mongolia province, on July 17, 2017. Firstly, the surface reflectance is derived from Sentinel-2A and Landsat 8 OLI images by the Sen2cor method and the NASA officially atmospheric correction algorithm respectively, and resampled to the same spatial resolution. Then, the matching factor is calculated based on the spectral library and the transformation model between the image and the spectral library is constructed to covert the surface reflectance from the Sentinel-2A image into the Landsat 8 image pixel-by-pixel. The results show that compared with the original image and the HLS spectral normalized image, the correlation of VNIR band between the pixel-by-pixel normalized image and the Landsat 8 VNIR is significantly improved and the radiation consistency is enhanced. This transformation model provides a new idea for high precision radiation normalization of multi-source medium-to-high resolution remote sensing images.

Key words: surface reflectance, pixel-by-pixel radiometric normalization, mixed pixel decomposition, spectral library, HLS

中图分类号:

P237

徐玉雯, 张浩, 陈正超, 景海涛. Sentinel-2A与Landsat 8 OLI逐像元辐射归一化方法研究[J]. 测绘通报, 2019, 0(10): 61-66.

XU Yuwen, ZHANG Hao, CHEN Zhengchao, JING Haitao. A case study on pixel-by-pixel radiometric normalization between Sentinel-2A and Landsat 8 OLI[J]. 测绘通报, 2019, 0(10): 61-66.

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Sentinel-2A与Landsat 8 OLI逐像元辐射归一化方法研究

A case study on pixel-by-pixel radiometric normalization between Sentinel-2A and Landsat 8 OLI

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