# Comparing Sentinel-2A and Landsat 7 and 8 Using Surface Reflectance over Australia
## 3 Data  
All Landsat data was downloaded from the USGS EarthExplorer website [17], as level L1T data. The imagery gaps from the failed Scan Line Corrector in Landsat-7 were treated as null areas (i.e., not gap-filled), and did not contribute to the analysis. All data was from pre-collection legacy datasets, as opposed to the newer Collection-1 data introduced during late 2016 and early 2017. All Sentinel-2A data was downloaded from the ESA as Standard Archive Format for Europe (SAFE) format zip files of level L1C data [18]. Only data processed with the ESA's version 02.04 system was used, as per the ESA's recommendations due to errors in their earlier processing software. The data was that available by February 2017. Thanks to the ESA's reprocessing efforts, there was, by this time, a large quantity of earlier imagery available as 02.04-processed output. The data searched for was from the entire holdings of Sentinel-2 imagery in the Remote Sensing Centre of the government of the Australian state of Queensland, where this work was undertaken, and covers around two thirds of the land mass of Australia. Imagery dates were in the period from August 2015 to January 2017. For the Landsat-7 comparison, there were 46 distinct cloud-free dates across 178 distinct scenes, while for the Landsat-8 comparisons, there were 49 distinct dates across 174 scenes. The average number of dates for each scene was 4.9 for Landsat-7, and 4.4 for Landsat-8. The Landsat scenes used are shown in Figure 1.  
Cloud and cloud shadow masking was performed using Fmask [19; 20]. The percentage cloud cover given by this method was used to select only dates that had less than 1% cloud. This was done in order to minimize the likely impact of undetected cloud and cloud shadow, recognising that the Fmask algorithm does not create a perfect mask. As a final filter to remove remaining undetected cloud or shadow, the ratio of the blue band in the two sensors was calculated. Any points for which this ratio was larger than 2 or smaller than 0.5 were removed, on the assumption that these represent pixels that were clear in one image but brightened by cloud or darkened by shadow in the other image. This removed approximately 0.5% of pixels. Topographic shadow masking was performed using the methods described by [PERSON] [21], and areas deemed to be in shadow were excluded from consideration. Areas of water were masked using the methods described by [PERSON] et al. [22], and omitted from consideration. The final number of points used in each comparison exercise is shown in Table 3. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Coefficient** & **Blue** & **Green** & **Red** & **NIR** & **SWIR1** & **SWIR2** \\ \hline \(c_{0}\) & 0.00447 & 0.00109 & \(-\)0.00104 & 0.000250 & 0.000124 & 0.00119 \\ \(c_{1}\) & 1.020 & 0.994 & 1.017 & 0.999 & 0.999 & 1.003 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Coefficients for NASA’s Harmonized Landsat-8 Sentinel-2 (HLS) product, to adjust Sentinel-2A reflectance to Landsat-8 reflectance. These are applied in an equation identical to Equation (1). Reproduced here from [PERSON] et al. [6]. Each point in these counts is a single 30 m pixel on a single date. It is assumed that there is no registration error between sensors. Visual inspection suggests that this is not entirely true. A small study by [PERSON] et al. [23] also indicates registration errors for imagery in South Africa, and suggests that the cause relates to the quality of ground control points used to register Landsat. Such registration errors would be dependent on location, and in the absence of a large assessment of Sentinel-Landsat co-registration errors in Australia, the assumption is made that such errors would not contribute to any apparent systematic bias in reflectance values. They could certainly increase the scatter in the comparisons, but it is difficult to see any way in which it could be so consistent as to affect the average behaviour over a large area.