## 6 Conclusions  
In this paper, a semi-automated scheme is proposed for extracting valuable information from wide-area surface deformation data to identify features that are prone to deformation on urban surfaces. This scheme successfully realizes the dynamic monitoring and information extraction of surface deformation-prone features during the rainy season during the 7-20 extraordinary rainstorm by studying the Sentinel-1A SAR data and the Sentinel-2 10 m resolution land cover products transiting through Zhengzhou City, using singular spectrum analysis and the box-and-line diagram criterion. At the same time, remote sensing was fused with building contour data in Zhengzhou City to identify sensitive buildings with urban surface deformation under the influence of flooding, demonstrating the capability and application of multi-source SAR data to acquire disaster spatio-temporal information from multiple angles. The program found that (1) the change in the area of sensitive features in Zhengzhou City is similar to the change in precipitation, and the larger the precipitation, the larger the sensitive area. (2) In the rainy season with extreme precipitation, the area of highly sensitive areas accounted for a very small proportion of Zhengzhou City, and, in addition, the highly sensitive areas are more often characterized by the phenomenon of anomalous subsidence and are dominated by agricultural land and grassland, but the authenticity of the area of these two features is for reference only. (3) In the rainy season where 7-20 is located, the number of houses with highly sensitive surface deformation is 955, and the number of buildings with anomaly settlement is slightly more than that of anomaly uplift; these highly sensitive houses are mainly distributed in the old urban areas, and after sampling and comparing with the actual situation, it was found that the main characteristics of these highly sensitive houses are the age of the houses or their own unstable structure, and the credibility of this program to identify sensitive buildings with surface deformation is relatively high. Conceptualization, L.H., L.C., Q.W., J.H. and B.Y. ; methodology, L.H., Q.W. and L.C. ; software, L.H., B.Y. and Q.W. ; validation, L.H. and J.H. ; formal analysis, L.H. ; investigation, L.H. ; resources, J.H, L.H. and L.C. ; data curation, L.H. and J.H. ; writing--original draft preparation, L.H. ; writing--review and editing, L.H. and L.C. ; visualization, L.H. ; supervision, L.C. ; project administration, L.C. ; funding acquisition, L.C. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China (Nos. 41971241) and Key Science and Technology Program of Henan Province China (222102320281). Not applicable. Data Availability Statement: Sentinel-1A ([[https://search.asf.alaska.edu/#/](https://search.asf.alaska.edu/#/)]([https://search.asf.alaska.edu/#/](https://search.asf.alaska.edu/#/)), accessed on 10 October 2023), SRTIM DEM ([[http://srtm.csi.cgiar.org/srtmdata](http://srtm.csi.cgiar.org/srtmdata)]([http://srtm.csi.cgiar.org/srtmdata](http://srtm.csi.cgiar.org/srtmdata)), accessed on 10 October 2023). Satellite precise orbit data ([[https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-1](https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-1)]([https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-1](https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-1)), accessed on 10 October 2023).