Sentinel-2 Barest Earth mosaic

The Sentinel-2 Bare Earth thematic product provides the first national scale mosaic of the Australian continent to support improved mapping of soil and geology. The bare earth algorithm using all available Sentinel-2 A and Sentinel-2 B observations up to September 2020 preferentially weights bare pixels through time to significantly reduce the effect of seasonal vegetation in the imagery. The result are image pixels that are more likely to reflect the mineralogy and/or geochemistry of soil and bedrock. The algorithm uses a high-dimensional weighted geometric median approach that maintains the spectral relationships across all Sentinel-2 bands. A similar bare earth algorithm has been applied to Geoscience Australia’s deeper Landsat time series archive (please search for "Landsat barest Earth". Both bare earth products have spectral bands in the visible near infrared and shortwave infrared region of the electromagnetic spectrum. However, the main visible and near-infrared Sentinel-2 bands have a spatial resolution of 10 meters compared to 30m for the Landsat TM equivalents. The weighted median approach is robust to outliers (such as cloud, shadows, saturation, corrupted pixels) and also maintains the relationship between all the spectral wavelengths in the spectra observed through time. Not all the sentinel-2 bands have been processed - we have excluded atmospheric bands including 1, 9 and 10. The remaining bands have been re-number 1-10 and these bands correlate to the original bands in brackets below:1 = blue (2) , 2 = green (3) , 3 = red (4), 4 = vegetation red edge (5), 5 = vegetation red edge (6), 6= vegetation red edge (7), 7 = NIR(8), 8 = Narrow NIR (8a), 9 = SWIR1 (11) and 10 = SWIR2(12).All 10 bands have been resampled to 10 meters to facilitate band integration and use in machine learning.

哨兵-2号（Sentinel-2）裸土专题产品首次生成了覆盖澳大利亚大陆的全国级镶嵌影像，旨在助力土壤与地质制图工作的优化升级。
该裸土算法基于截至2020年9月的所有可用哨兵-2A（Sentinel-2A）与哨兵-2B（Sentinel-2B）观测数据，通过对时序上的裸地像元赋予优先权重，显著削弱了影像中季节性植被的干扰影响。
最终生成的影像像元能够更精准地反映土壤与基岩的矿物组成及/或地球化学特征。
该算法采用高维加权几何中位数方法，可保留哨兵-2号所有波段间的光谱关联关系。
澳大利亚地球科学局（Geoscience Australia）的长时序陆地卫星（Landsat）档案数据集也应用了类似的裸土算法，相关信息可搜索“Landsat barest Earth”获取。
两款裸土产品的光谱波段均覆盖电磁波谱的可见光、近红外以及短波红外波段范围。
但哨兵-2号的主要可见光与近红外波段空间分辨率为10米，而对应波段的陆地卫星TM数据空间分辨率仅为30米。
该加权中位数算法对异常值（如云、阴影、饱和像元、损坏像素）具有较强鲁棒性，同时可保留时序观测光谱中所有光谱波长间的关联关系。
并非所有哨兵-2号波段均参与了数据处理——我们剔除了包括波段1、9和10在内的大气校正波段。
剩余波段被重新编号为1至10，各新编号波段与原波段的对应关系如下（括号内为原波段编号）：1=蓝光波段（原波段2）、2=绿光波段（原波段3）、3=红光波段（原波段4）、4=植被红边波段（原波段5）、5=植被红边波段（原波段6）、6=植被红边波段（原波段7）、7=近红外波段（原波段8）、8=窄带近红外波段（原波段8a）、9=短波红外1波段（原波段11）、10=短波红外2波段（原波段12）。
所有10个波段均被重采样至10米分辨率，以方便波段整合及机器学习应用。