Assessment of the applicability of atmospheric correction algorithms for Type I and Type II water bodies based on in-situ data - a case study using sentinel data

ABSTRACT

The application of remote sensing technology in the retrieval of marine biophysical and physical parameters is becoming increasingly widespread. Accurate atmospheric correction is an essential prerequisite for subsequent retrieval of biophysical and physical parameters of water bodies. However, different atmospheric correction algorithms exhibit significant regional applicability variations across various water body types, requiring researchers to select suitable atmospheric correction algorithms for their study areas. In this study, utilizing Sentinel-2 and Sentinel-3 satellite data sources, global publicly available datasets, and in-situ synchronous measured reflectance data for Type I and Type II water bodies, we evaluated the accuracy of atmospheric correction using three types of algorithms based on radiative transfer, dark spectrum fitting, and neural networks. We analysed the sources of algorithm errors and their applicability from both algorithm principles and water body properties, providing criteria for selecting suitable atmospheric correction algorithms for different characteristic water bodies and proposing recommendations for improving correction accuracy.

KEYWORDS:

• Atmospheric correction
• radiative transfer
• dark spectrum fitting
• neural networks
• Type I water
• Type II water

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was funded by the National Natural Science Foundation of China under Grant [U1906217], [62071491] and the Fundamental Research Funds for the Central Universities [22CX01004A-5], [22CX01004A-4].