Evaluation of spatial and temporal variability in Sentinel-2 surface reflectance on a rice paddy landscape

High spatial resolution spaceborne remote sensing systems provide a new data source for agricultural applications. As a key deliverable, surface reflectance (SR) enables immediate and non-destructive estimation of crop status, thus the demand for reliable pixelwise SR is increasing. However, the evaluations are typically conducted on pseudo-invariant areas and the reliability of pixelwise SR has not been thoroughly examined over heterogenous, dynamic surfaces. In this study, we evaluated pixelwise Sentinel-2 (S2) SR on a rice paddy landscape across seasons using drone-based hyperspectral images and tower-based continuous hyperspectral observations as the ground references. We also examined the impact of spatial and atmospheric properties on S2 SR. Overall, S2 SR showed strong linear relationships with the ground references (the overall R 2 > 0.8). The residual errors were influenced by s…