Data fusing method of land subsidence monitoring based on leveling and InSAR
Wang Ai-gu
Abstract
Wang Ai-gu
Abstract
This paper analyzed advantages and disadvantages of leveling and InSAR in land subsidence.Data fusion algorithm and interpolation calculation were proposed.Data fusion method fusing leveling and InSAR can solve disadvantages of lower spatial and temporal resolution in leveling and coherent using InSAR in part of area.Fusing data can better describe the current situation of land subsidence,and better predict trend of land subsidence,further reduce subsidence disaster harm to economic and social.Fusion example about Tianjin showed that the algorithm could solve the shortcomings of single data.Fusing data had the advantages of multiple data,which could provide a rich data to further predict trend of land subsidence.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper analyzed advantages and disadvantages of leveling and InSAR in land subsidence.Data fusion algorithm and interpolation calculation were proposed.Data fusion method fusing leveling and InSAR can solve disadvantages of lower spatial and temporal resolution in leveling and coherent using InSAR in part of area.Fusing data can better describe the current situation of land subsidence,and better predict trend of land subsidence,further reduce subsidence disaster harm to economic and social.Fusion example about Tianjin showed that the algorithm could solve the shortcomings of single data.Fusing data had the advantages of multiple data,which could provide a rich data to further predict trend of land subsidence.
Key concepts: Interferometric synthetic aperture radar, Interpolation (computer graphics), Remote sensing, Sensor fusion, Subsidence, Data mining, Computer science, Environmental science