TL;DR
This paper introduces sen2nbar, an open-source Python package that simplifies converting Sentinel-2 surface reflectance data to Nadir BRDF Adjusted Reflectance, enhancing data consistency and usability across various Earth observation applications.
Contribution
The paper presents a new Python tool, sen2nbar, enabling efficient and standardized conversion of Sentinel-2 SR data to NBAR for individual images and Earth System Data Cubes.
Findings
sen2nbar effectively converts S2 SR to NBAR with a single function
Supports both SAFE files and ESDCs from STAC
Facilitates data harmonization and standardization
Abstract
The Sentinel-2 (S2) mission from the European Space Agency's Copernicus program provides essential data for Earth surface analysis. Its Level-2A products deliver high-to-medium resolution (10-60 m) surface reflectance (SR) data through the MultiSpectral Instrument (MSI). To enhance the accuracy and comparability of SR data, adjustments simulating a nadir viewing perspective are essential. These corrections address the anisotropic nature of SR and the variability in sun and observation angles, ensuring consistent image comparisons over time and under different conditions. The -factor method, a simple yet effective algorithm, adjusts observed S2 SR by using the MODIS BRDF model to achieve Nadir BRDF Adjusted Reflectance (NBAR). Despite the straightforward application of the -factor to individual images, a cohesive Python framework for its application across multiple S2 images and…
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