An integrated approach for risk assessment of land subsidence in Xi'an, China using optical and radar satellite images

Land subsidence, induced by the over-exploitation of groundwater resources, is becoming a huge hazard in many large cities around the world. Risk assessment of the infrastructure under the threat of land subsidence plays a vital role in urban planning and design. In this study, an integrated approach that combines the land subsidence, the ground fissures, and the elements at risk is proposed. The ground surface deformation is studied with timeseries Interferometric Synthetic Aperture Radar (InSAR), and the differential settlement is assessed by an index of angular distortion. Then, the elements that are potentially affected by the land subsidence are recognized through a land use classification analysis, which is based on a synergetic use of optical and radar images using an object-based approach. Finally, the risk due to land subsidence is assessed using a risk matrix that integrates the differential settlement, the ground fissures, and the land use classification results. To demonstrate the effectiveness of the proposed method, a risk assessment of the land subsidence in the City of Xi'an, China is conducted. Our results also illustrate the advantages of the synergetic land use classification over the pixel-based classification.

Automated summary

Land subsidence caused by over-exploitation of groundwater resources poses a significant hazard in many large cities globally. Assessing infrastructure risks under the threat of land subsidence is crucial for urban planning and design. This study proposes an integrated approach combining land subsidence, ground fissures, and elements at risk. Time-series Interferometric Synthetic Aperture Radar (InSAR) is used to study ground surface deformation, and differential settlement is assessed using an angular distortion index. Land use classification analysis is conducted to identify potentially affected elements using optical and radar images with an object-based approach. Finally, a risk matrix integrating differential settlement, ground fissures, and land use classification results is employed to assess land subsidence risk. The effectiveness of the proposed method is demonstrated through a risk assessment of land subsidence in Xi'an, China, and the advantages of synergetic land use classification over pixel-based classification are illustrated.