Time series data of snow area ratio in the Arctic (2000-2019)

The fraction snow cover (FSC) is the ratio of the snow cover area SCA to the pixel space. The data set covers the Arctic region (35 ° to 90 ° north latitude). Using Google Earth engine platform, the initial data is the global surface reflectance product with a resolution of 1000m with mod09ga, and the data preparation time is from February 24, 2000 to November 18, 2019. The methods are as follows: in the training sample area, the reference data set of FSC is prepared by using Landsat 8 surface reflectance data and snomap algorithm, and the data set is taken as the true value of FSC in the training sample area, so as to establish the linear regression model between FSC in the training sample area and NDSI based on MODIS surface reflectance products. Using this model, MODIS global surface reflectance product is used as input to prepare snow area ratio time series data in the Arctic region. The data set can provide quantitative information of snow distribution for regional climate simulation and hydrological model.

雪覆盖面积比例（FSC）是指雪覆盖面积（SCA）与像素空间的比率。该数据集涵盖了北极地区（北纬35°至90°）。利用谷歌地球引擎平台，初始数据是全球地表反射率产品，分辨率为1000米，数据源为mod09ga，数据准备时间从2000年2月24日至2019年11月18日。具体方法如下：在训练样本区域，通过使用Landsat 8地表反射率数据和snomap算法准备FSC的参考数据集，并将该数据集作为训练样本区域的FSC真实值，从而建立训练样本区域的FSC与基于MODIS地表反射率产品计算得到的归一化差异指数（NDSI）之间的线性回归模型。利用此模型，将MODIS全球地表反射率产品作为输入，准备北极地区的雪面积比时间序列数据。该数据集能够为区域气候模拟和水文模型提供雪分布的定量信息。