Sentinel-1 SAR Wet snow maps for Southern Norway, 2016-2020

Sentinel-1 Synthetic Aperture Radar data have been processed to produce daily maps of wet snow for Southern Norway for the period 2016-2020. This study makes use of the Interferometric-wide (IW) swath mode which has a swath width of 250 km and nominal pixel spacing of 10 m. We use the S1 IW ground-range detected (GRD) product with co- (“VV”) and cross- (“VH”) polarizations, and pixels are aggregated to a spacing of 100 m to reduce noise. The SAR backscatter images have been processed to produce daily wet snow maps using the Nagler and Rott (2016) approach which utilises backscatter from both VV and VH polarizations and a weighting to the contributions is applied to represent an incident angle correction. SAR image pixels are classified by applying a threshold to the difference between the SAR backscatter and its reference value. These reference values are produced for each sensor and geometry by calculating the average radar backscatter per pixel, based on data acquired in the period November 1st - April 30th during which snow condition is assumed to be dry.

本数据集由经处理的哨兵1号（Sentinel-1）合成孔径雷达（SAR）数据生成，涵盖2016-2020年挪威南部地区的每日湿雪空间分布图。
本研究采用幅宽250 km、标称像素间距10 m的干涉宽幅（IW）条带模式，使用搭载同极化（VV）与交叉极化（VH）通道的S1 IW地面距离检测（GRD）产品，并将像素聚合至100 m的像素间距以降低噪声。
研究采用内格勒与罗特（2016）提出的算法，结合VV与VH极化的SAR后向散射数据，并通过对两类极化的后向散射贡献施加权重以实现入射角校正，将SAR后向散射影像处理为每日湿雪分布图。
该算法通过对SAR后向散射值与其参考值的差值设置阈值，完成对影像像素的分类。上述参考值针对每个传感器与观测几何构型生成：基于11月1日至4月30日期间采集的、该时段内积雪状态被假定为干雪的观测数据，计算每个像素的平均雷达后向散射值得到。