Wind-blown snow particles often contaminate Terrestrial Laser Scanning (TLS) data of snow covered terrain. However, common filtering techniques fail to filter wind-blown snow and incorrectly filter data from the true surface due to the spatial distribution of wind-blown snow and the TLS scanning geometry. We present FlakeOut, a filter designed specifically to filter wind-blown snowflakes from TLS data. A key aspect of FlakeOut is a low false positive rate of 2.8x10^-4—an order of magnitude lower than standard filtering techniques—which greatly reduces the number of true ground points that are incorrectly removed. This low false positive rate makes FlakeOut appropriate for applications requiring quantitative measurements of the snow surface in light to moderate blowing snow conditions. Additionally, we provide mathematical and software tools to efficiently estimate the false positive rate of filters applied for the purpose of removing erroneous data points that occur very infrequently in a dataset.

风吹雪颗粒经常污染积雪地形的地面激光扫描 (TLS) 数据。然而，由于风吹雪的空间分布和 TLS 扫描几何结构，常见的过滤技术无法过滤风吹雪并错误地过滤来自真实表面的数据。我们展示了 FlakeOut，这是一个专门设计用于从 TLS 数据中过滤风吹雪花的过滤器。^{FlakeOut 的一个关键方面是 2.8x10 -4}的低误报率- 比标准过滤技术低一个数量级 - 这大大减少了被错误删除的真实地面点的数量。这种低误报率使得 FlakeOut 适用于需要在轻度到中度吹雪条件下对雪面进行定量测量的应用。此外，我们提供数学和软件工具来有效地估计过滤器的误报率，这些过滤器用于删除数据集中很少出现的错误数据点。