Retrieval of high spatial resolution precipitable water vapor maps using heterogeneous earth observation data

The determination of the amount of precipitable water vapor (PWV) from global navigation satellite system (GNSS) is restricted to a limited number of ground-based stations with low spatial resolution. The PWV obtained by the multi-source data fusion method has a low spatial resolution because of the low spatial resolution of the data used. Therefore, it is difficult to retrieve PWV maps with sub-km resolution. Therefore, retrieving PWV with high spatial resolution becomes the focus of this study. A dual-scale method for retrieving PWV maps, based on heterogeneous earth data, is proposed, which can obtain sub-kilometer resolution PWV, while maintaining accuracy. First, an approach for analyzing the spatial correlation between land cover types (LCT) and ground-based PWV was proposed, and the meteorological, ecological, topographic, and LCT variables affecting changes in PWV in the near-earth atmosphere were determine, Subsequently, three different regression models, including multiple linear regression (MLR), random forest (RF), and a generalized regression neural network (GRNN), were used to construct the functional model linking heterogeneous earth observation data and ground-based GNSS-derived PWV. Finally, the PWV map with sub-kilometer resolution was generated based on the dual-scale method. Unlike the PWV obtained by data fusion and remote sensing technology, the proposed dual-scale retrieval method can generate PWV maps at 300 m spatial resolution. Statistical analyses demonstrated that the RMS of the PWV derived from the proposed method was less than 2.2 mm, and the bias was close to 0, thereby filling the gap in the sub-kilometer high-precision PWV products. •Spatial correlation between land cover types and GNSS PWV was analyzed firstly.•The functional relationship between heterogeneous data and GNSS PWV is established.•A dual-scale approach for retrieving PWV with sub-kilometer resolution is proposed.•The RMS of dual-scale PWV was less than 2.2 mm, and the bias was close to 0.