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Global urbanization is occurring rapidly, and numerous moderate resolution remote sensing data are being used to monitor this process. Landsat 8 OLI and Sentinel-2 MSI data are combined in many applications but few studies haves focused on either urban change or consistency between these two data in time series. To evaluate the varying correlation between the two sensors in a time series, the correlation coefficient (R) and root-mean-square deviation (RMSD) of seven band pairs and three indices (NDVI, NDBI, and MNDWI) were calculated in this study and the results of the built-up area identified by IBI derived from the above three indices were compared. It was found that the correlation between the two sensors (R &gt; 0.8534, p &lt; 0.0001) was good in most bands but not as good for indices (in half of the results, R &lt; 0.9). Meanwhile, the correlation of the two sensors of both bands and indices fluctuated between seasons and the comparative results of built-up area identification between the two data are relative to this variation. Therefore, when the OLI and MSI data are used in future collaboration applications, the data and threshold selection should consider the consistency and the fluctuation between the two data, especially in both time series studies and urban detection.

Preliminary Evaluation of the Consistency of Landsat 8 and Sentinel-2 Time Series Products in An Urban Area—An Example in Beijing, China