BACI: System State Vector (SSV) land surface time series dataset for the Denmark fast track site, 2000-2015, v1.0

The BACI Surface State Vector (SSV) dataset for Denmark provides a description of the surface state from a combination of satellite observations across wavelength domains i.e. albedo (visible), Land Surface Temperature (LST) (passive/thermal microwave) and backscatter (active microwave). The dataset contains a unique spatially and temporally consistent (as far as the observations allow) series of observations of the land surface, across optical and microwave domains. The innovation of this approach is in providing a SSV in a common space/time framework, containing information from multiple, independent data streams, with associated uncertainty. The methods used can be used to combine data from multiple different satellite sources. The resulting dataset is intended to make the best use of all available observations to detect changes in the land surface state: the combination of data is likely to show changes that would not be apparent from data in a single wavelength region. The inclusion of uncertainty also allows the strength of the resulting changes to be properly quantified.

丹麦BACI地表状态向量（Surface State Vector，SSV）数据集结合多波段域卫星观测数据，对丹麦地表状态进行描述，观测类型涵盖反照率（可见光波段）、地表温度（Land Surface Temperature，LST，被动/热微波波段）以及后向散射（主动微波波段）。本数据集包含一套在观测允许范围内实现空间与时间一致性的独特陆地表面观测序列，覆盖光学与微波波段域。该研究方法的创新点在于，在统一的时空框架下生成地表状态向量，整合多套独立数据源的信息并附带对应的不确定性。所采用的方法可用于融合多类不同卫星数据源的数据。本数据集旨在充分利用所有可用观测数据以检测地表状态变化：多波段数据融合可识别出单一波段观测无法显现的地表变化。附带的不确定性信息还可实现对检测到的地表变化强度的准确量化。