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

doi:10.13474/j.cnki.11-2246.2019.0319

Abstract

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

CLC Number:

P237

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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