Effectiveness evaluation of DS-InSAR method fused PS points in surface deformation monitoring: a case study of Hongta District, Yuxi City, China

Abstract

InSAR technology provides a powerful tool for detecting large-scale surface deformation. In particular, the newly developed DS-InSAR method fused PS points has obvious advantages in monitoring bare land and vegetation covered areas, but at present, there is a lack of effectiveness evaluation of this method. Therefore, this paper takes Hongta District of Yuxi City as an example. The 29 scenes sentinel-1A data from January 2019 to December 2019 were processed and analyzed using the DS-InSAR method fused PS points. The research results show that the position and deformation trend of the inversion results of the three methods are highly consistent, the correlation between DS-InSAR method fused PS points and PS- InSAR and SBAS-InSAR methods is 0.9473 and 0.8583, respectively. But the spatial density of the measurement points (MPs) obtained by the DS-InSAR method of PS points is 11 times and 4 times that of the PS-InSAR method and SBAS-InSAR method respectively. It clearly shows that DS-InSAR method fused PS points has greater advantages than PS-InSAR and SBAS-InSAR methods in deformation mapping displacement, because the MPs density is higher. It is conducive to the detailed analysis of the spatio-temporal characteristics and deformation mechanism of deformation.

Keywords:

• DS-InSAR
• surface subsidence monitoring
• sentinel-1A
• feature decomposition
• phase optimization

Acknowledgments

The sentinel-1A datasets were freely provided by the European Space Agency (ESA) and freely downloaded from the website https://vertex.daac.asf.alaska.edu. The NASA for providing the SRTM-1 DEM data and freely downloaded from the website http://rmw.recordist.com/index.html. The Precipitation Orbit Data (POD) was freely downloaded from the website https://qc.sentinel1.eo.esa.int/. The Rainfall data were freely downloaded from the website https://disc.gsfc.nasa.gov/.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are available from the first author, Yongfa Li, upon reasonable request.

Additional information

Funding

This study was supported by National Natural Science Foundation of China(42161067 and 42004006).