The rapid mapping of flood inundation is essential for timely assessment of damage and post-disaster recovery. Remote sensing technology provides clear spatial information for mapping flood inundation, but its real-time (RT) images are often not available due to the severe weather conditions during the disaster events; the combination of RT data can better compensate for the deficiency. In this study, a near RT (NRT) flood inundation probability mapping method based on post-event NRT remote sensing data combined with RT volunteer geographic information (VGI) was proposed for mapping the 2019 flood in Linhai City, Zhejiang Province. First, a probabilistic index distribution (PID) layer was constructed from high-resolution digital elevation model data using an inverse distance-weighted height filter based on each VGI point. Then, a quality evaluation method for non-reference data was introduced to evaluate the validity of the VGI data. The final flood probability map was generated by PID weighting. The results show that, by fusing NRT images and RT data, the proposed model for mapping flood inundation probability is more robust and enhances the spatial characteristics of the flood inundation probability index, allowing it to enable emergency responders to quickly identify areas requiring urgent attention.
New radar altimeters have supported elevation modeling with greater accuracy and extended periods in recent years. Sentinel-3 has been rarely used in previous studies for monitoring the Antarctic ice sheet. The CryoSat-2 and Sentinel-3 satellite radar altimeter data were combined to extract the elevation changes in the Antarctic ice sheet. First, a subregional data filtering method based on a clustering algorithm was proposed to improve the accuracy of the elevation change results for the outliers in the original measurements. Next, an improved model-fitting model that incorporated multiple parameters was used to extract elevation changes, and the results were validated using airborne laser altimetry data and ICESat-2 data. The average changes in the Antarctic ice sheet elevation from 2016 to 2019 were −4.3 ± 0.9 cm / y. The elevation changes of the ice shelf edges with large slopes and complex topography were much larger than the interior. Some specific areas showed substantial elevation changes. The most significant surface decreases occurred at the Pine Island Glacier and the Totten Glacier, while a pronounced surface heightening existed at the Kamb Ice Stream. We reveal an effective method for combining Antarctic ice sheet data from new radar altimeters. This method supports the long-term monitoring of the Antarctic ice sheet and global climate change in the future.
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