北极积雪面积比例时序数据（2000-2019）

积雪面积比例（fractional snow cover， FSC）是定量描述单位像元内积雪覆盖面积（Snow Cover Area SCA）与像元空间范围的比值。本数据集涵盖区域为北极地区（北纬35°至北纬90°），使用Google Earth Engine平台，采用的初始数据为MOD09GA 分辨率为1000m的全球地表反射率产品，数据制备时间为2000年2月24日至2019年11月18日。方法为：在训练样本区域，使用Landsat 8地表反射率的数据和SNOMAP算法制备FSC的参考数据集，将该数据集作为训练样本区域FSC真值，从而建立训练样本区域FSC与基于MODIS地表反射率产品的雪被指数NDSI之间的线性回归模型。使用该模型，将MODIS全球地表反射率产品作为输入，制备北极地区积雪面积比例时序数据。该数据集可为区域气候模拟、水文模型等提供积雪分布的定量信息。

Fractional Snow Cover (FSC) is a quantitative ratio that describes the proportion of snow cover area (SCA) within a single pixel relative to the total spatial extent of the pixel. This dataset covers the Arctic region ranging from 35°N to 90°N. It was developed using the Google Earth Engine platform, with the initial data being the MOD09GA global surface reflectance product with a spatial resolution of 1000 m. The data production period spans from February 24, 2000 to November 18, 2019. The production workflow is as follows: First, a reference FSC dataset for the training sample regions was generated using Landsat 8 surface reflectance data and the SNOMAP algorithm, which was treated as the ground truth of FSC in these regions. Subsequently, a linear regression model was built between the FSC values of the training sample regions and the Normalized Difference Snow Index (NDSI) calculated from the MODIS surface reflectance product. Using this model and taking the MODIS global surface reflectance product as input, the time-series FSC dataset for the Arctic region was generated. This dataset can provide quantitative information on snow cover distribution for regional climate simulation, hydrological modeling and other relevant research applications.

搜集汇总

背景与挑战

背景概述

该数据集提供北极地区2000-2019年每日的积雪面积比例数据，空间分辨率100m-1km，基于MODIS和Landsat 8数据通过回归模型生成，适用于气候和水文研究。