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Remote Sensing
Volume 15
Issue 22
10.3390/rs15225382
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Article

GF-1 WFV Surface Reflectance Quality Evaluation in Countries along “the Belt and Road”

by
Yaozong Ding
1,2,
Xingfa Gu
1,2,3,
Yan Liu
1,*,
Hu Zhang
4,
Tianhai Cheng
1,2,
Juan Li
1,
Xiangqin Wei
1,
Min Gao
1,2,
Man Liang
1,2 and
Qian Zhang
1,2
1
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
4
School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(22), 5382; https://doi.org/10.3390/rs15225382
Submission received: 26 September 2023 / Revised: 6 November 2023 / Accepted: 7 November 2023 / Published: 16 November 2023
(This article belongs to the Special Issue Quantitative Inversion and Validation of Satellite Remote Sensing Products)
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Abstract

The GaoFen-1 wide field of view (GF-1 WFV) has produced level 1 digital number data globally; however, most applications have focused on China, and data quality outside China has not been validated. This study presents a preliminary assessment of the 2020 GF-1 WFV surface reflectance data for Nepal, Azerbaijan, Kenya, and Sri Lanka along “the Belt and Road” route using Sentinel-2 Multi-Spectral Instrument (MSI), Landsat-8 Operational Land Image (OLI), and Moderate Resolution Imaging Spectroradiometer (MODIS) data. A method for obtaining the GF-1 WFV surface reflectance data was also proposed, with steps including atmospheric correction, cross-radiation calibration, and bidirectional reflectance distribution function correction. The results showed that WFV surface reflectance data was not significantly different from MSI, OLI, and MODIS surface reflectance data. In the visible and near-infrared bands, for most landcover types, the bias was less than 0.02, and the precision and root mean square error were less than 0.04. When the landcover types were forest and water, the MSI, OLI, and MODIS surface reflectance data were higher than that of WFV in the near-infrared band. The results of this study provide a basis for assessing the global application potential of GF-1 WFV.
Keywords: GF-1 WFV; surface reflectance; quality evaluation; “the Belt and Road” GF-1 WFV; surface reflectance; quality evaluation; “the Belt and Road”
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MDPI and ACS Style

Ding, Y.; Gu, X.; Liu, Y.; Zhang, H.; Cheng, T.; Li, J.; Wei, X.; Gao, M.; Liang, M.; Zhang, Q. GF-1 WFV Surface Reflectance Quality Evaluation in Countries along “the Belt and Road”. Remote Sens. 2023, 15, 5382. https://doi.org/10.3390/rs15225382

AMA Style

Ding Y, Gu X, Liu Y, Zhang H, Cheng T, Li J, Wei X, Gao M, Liang M, Zhang Q. GF-1 WFV Surface Reflectance Quality Evaluation in Countries along “the Belt and Road”. Remote Sensing. 2023; 15(22):5382. https://doi.org/10.3390/rs15225382

Chicago/Turabian Style

Ding, Yaozong, Xingfa Gu, Yan Liu, Hu Zhang, Tianhai Cheng, Juan Li, Xiangqin Wei, Min Gao, Man Liang, and Qian Zhang. 2023. "GF-1 WFV Surface Reflectance Quality Evaluation in Countries along “the Belt and Road”" Remote Sensing 15, no. 22: 5382. https://doi.org/10.3390/rs15225382

APA Style

Ding, Y., Gu, X., Liu, Y., Zhang, H., Cheng, T., Li, J., Wei, X., Gao, M., Liang, M., & Zhang, Q. (2023). GF-1 WFV Surface Reflectance Quality Evaluation in Countries along “the Belt and Road”. Remote Sensing, 15(22), 5382. https://doi.org/10.3390/rs15225382

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