Abstract:Since its on-orbit operation in April 2013, the wide field of view (WFV) sensors onboard Gaofen-1 (GF-1), where "Gaofen" means high resolution in Chinese, have continuously collected multispectral imagery of the Earth's surface. The GF-1 WFV sensors have provided abundant data sources for many fields including ecology. The fact that insufficient site calibration (i.e. once a year) as well as the updates lag of calibration parameters might limit the quantitative application of the GF-1 WFV imagery to a certain extent. However, current literature has only mentioned radiometric calibration of the GF-1 WFV images as a pre-processing procedure, whereas has rarely discussed the possible impacts caused by improper selection or misuse of calibration parameters. Based on the radiometric calibration parameters published for the GF-1 WFV imagery (from 2014 to 2021) and four scenes of the Level1A data products, the issue on radiometric calibration bias was investigated. Furthermore, impacts of the radiometric calibration bias on the top of atmosphere (TOA) reflectance and on several vegetation indices commonly used were discussed accordingly. It showed that, generally, even the calibration difference between two neighboring years were considered, in most cases, improper selection of the calibration parameters could result in a significantly relative bias in the TOA reflectance. The bias in TOA reflectance further challenged different types of vegetation indices with varying degrees of patterns in practice. In particular, mainly due to the radiometric calibration biases, the obvious errors were more likely in the normalized difference vegetation index based on two bands, for monitoring sparse vegetation coverage area. Actually, the normalized difference vegetation index has been commonly used in assessing vegetation status as well as surface dynamics. At the same time, for monitoring high vegetation coverage area, the simple ratio vegetation index with two bands was possibly confronted with greater challenges. Consequently, to make full use of the GF-1 WFV Level1A products, it is critical to solve the radiometric calibration problems. In this study, a time weighted linear interpolation method was proposed. In the interpolation process for a specific GF-1 WFV imagery, both radiometric parameters obtained closely before and after the imagery acquisition were integrated. A case study suggested the effectiveness of the proposed processing to improve the radiometric calibration of the GF-1 WFV images in Level1A products, as compared against the results obtained merely based on public calibration parameters. Finally, general users should pay much attention to the radiometric calibration of satellite remotely sensed data (e.g., the GF-1 WFV multispectral imagery) for their quantitative applications, as discussed in this investigation.